The present study had its limitations. One of the main limitations is related to the small sample size, which makes any generalizations based on the results difficult. However, considering that the sample is from professional players, is almost impossible to have larger samples. Other study limitation can be related with variation in environmental conditions occurred during the period of intervention. Another limitation is the fact that only a brief period during the initial phase of the season was analyzed. These limitations may influence the results, since no dose-response relationship was analyzed in the later stage of the season, and possibly different results can be found. Future studies should analyze a more longitudinal period to make better generalizations.

Considering the lack of studies and the conflicting evidence surrounding the doserelationships between internal and external loads with physical fitness changes, the present study revealed some interesting findings. As practical implications, this study suggests that despite field tests may show relationships between them, it does not mean that they present similar dose-response relationships with internal and external training loads. Therefore, different dimensions of load may produce different impact in fitness of players. However, conclusions should be interpreted carefully, since the limitations and small sample may affect the generalizability of the findings.

#### **5. Conclusions**

The present study revealed significant improvements of VIFT, VVameval, CMJ and 20-m sprint tests after the training intervention. Despite very large relationships between VIFT and VVameval, the VIFT showed great sensitivity to track small changes. Also, these two measures revealed dose-response relationships with different dimensions of training load quantification. Objective internal and external load measures seem to be better suited for tracking VIFT changes. While subjective internal loads are better suited to track changes in aerobic endurance from VVameval, at least during the initial phases of the season. For those reasons, coaches and practitioners should use objective internal and external loads to track aerobic power related changes from VIFT.

**Author Contributions:** S.Y., A.R., F.M.C. and A.J.F. lead the project, collected the data, treated the data, wrote the statistical report and revised the original manuscript. R.S. and H.S. wrote and revised the original manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the ESDL-IPVC (CTC-ESDL-CE00118).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Acknowledgments:** Filipe Manuel Clemente: This work is funded by Fundação para a Ciência e Tecnologia/ Ministério da Ciência, Tecnologia e Ensino Superior through national funds and when applicable co-funded EU funds under the project UIDB /50008/2020. Rui Silva: This study made part of one curricular unit of Master in Sports Training at Escola Superior de Desporto e Lazer, Instituto Politécnico de Viana do Castelo, Portugal. Hugo Sarmento also gratefully acknowledge the support of a Spanish government subproject Integration ways between qualitative and quantitative data, multiple case development, and synthesis review as main axis for an innovative future in physical activity and sports research [PGC2018-098742-B-C31] (Ministerio de Economía y Competitividad, Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema I+D+i), that is part of the coordinated project 'New approach of research in physical activity and sport from mixed methods perspective (NARPAS\_MM) [SPGC201800X098742CV0]'.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

### *Article* **Can Rules in Technical-Tactical Decisions Influence on Physical and Mental Load during Soccer Training? A Pilot Study**

**Tomás García-Calvo 1,\*, Juan José Pulido 1, José Carlos Ponce-Bordón 1, Miguel Ángel López-Gajardo 1, Israel Teoldo Costa 2 and Jesús Díaz-García 1**

**Abstract:** This study aimed to analyze the effects of rules limitations in pass decisions during soccer tasks on physical and mental load reported by players. Participants were 40 semiprofessional Spanish soccer players (*M*age = 22.40, *SD* = 2.25) from two male teams. Two training sessions with four tasks (same tasks with different score system: two maintaining ball possession games with goalkeepers, and two maintaining ball possession games) in counterbalanced order between teams were completed. To achieve a goal during limitation tasks, a minimum number of players had to participate in the passes before the goal. Internal (perceived effort and heart rate) and external physical load (distances), mental load (validated adaptation of the NASA-TXL) and fatigue (VASfatigue) were quantified. Paired t-test and magnitude-based inference were conducted. The results showed significantly higher mean speeds (*p* < 0.01), effort perception (*p* < 0.001), and mental fatigue (very likely positive) during possession games with restrictions. Additionally, performance satisfaction obtained significantly higher values with goalkeepers and pass restrictions (very likely positive). External physical load showed no significant differences between situations. The influence of mental fatigue on internal load and the complexity of the tasks could explain these results. Coaches can use this information to manipulate the training load in ecological conditions.

**Keywords:** monitoring; soccer constraints; small-sided games; training interventions; training load

#### **1. Introduction**

Specific soccer strategies such as the number of players involved, the scoring system, or the size and orientation of the pitch could vary according to the coach's objectives during training tasks [1]. Although these changes have usually been designed for technical-tactical objectives, this also allows the intentional manipulation of the training load by coaches in ecological conditions [2]. Thus, knowledge about the effects of these soccer strategies on training load can optimize the training process [3–5]. One frequently used strategy is to include constraints in pass decisions; however, no study has assessed the effect of rules in pass decisions on physical and mental load during soccer tasks. This study proposed to examine the effects of this strategy on load during soccer training tasks.

Within the current soccer training approach, physiological, psychological, and technicaltactical elements are interrelated [6] to obtain greater specific adaptations in ecological conditions [7]. In this approach, coaches use constraints to enhance their training objectives, i.e., the maintaining ball possession games (MBPG), where teams have to achieve a certain number of consecutive passes, producing different player responses in comparison with the same tasks with goalkeepers and regular goals (MBPG-G) [8]. This is an example of how coaches could manipulate the load through the use of task constraints [9,10], such as an unbalance in the number of players for each team, specific rules in games and tasks,

**Citation:** García-Calvo, T.; Pulido, J.J.; Ponce-Bordón, J.C.; López-Gajardo, M.Á.; Teoldo Costa, I.; Díaz-García, J. Can Rules in Technical-Tactical Decisions Influence on Physical and Mental Load during Soccer Training? A Pilot Study. *Int. J. Environ. Res. Public Health* **2021**, *18*, 4313. https://doi.org/10.3390/ ijerph18084313

Academic Editor: Paul Tchounwou

Received: 9 February 2021 Accepted: 15 April 2021 Published: 19 April 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

or modifying the field dimensions. These coaches' modifications can differentiate task characteristics, demands, and training goals [9]. Therefore, to control the load caused by these types of tasks, it is necessary to know the specific influence of each constraint on mental and physical load [5]. This information allows a correct distribution and application of the training load [11,12].

It has been shown that larger pitch size increases the physical load of the soccer tasks in terms of total distance and heart rate [3,13,14]. Additionally, the presence of jokers decreases the physical load with higher values of walking time [15,16], whereas the presence of goalkeepers increases the distance covered during tasks [17]. However, the condition in which each player can perform a maximum number of touches on the ball decreases the walking time and distance compared to normal touch conditions [15,18]. On the contrary, to our knowledge, few studies [10,19–21] have analyzed the influence of these soccer-specific strategies on mental load and fatigue, although, it is demonstrated that mental fatigue decreases specific soccer performance during small-sided Games. Specifically, mental fatigue increases the number of soccer technical errors [22], impairs the spatial distribution (distances between players) [23], and decreases the physical performance and accuracy of technical-tactical decisions [4,24,25]. In this regard, it has been shown that awarding an extra point (at the beginning) or a double extra point (in the final minutes) when the points were obtained in certain time intervals produces higher levels of mental load than the habitual scores [10]. Additionally, the MBPG-G score system showed higher values in the mental load than the MBPG [19]. Furthermore, coaches' active participation through the use of general encouragement increases mental fatigue compared to tasks where coaches adopt a passive attitude [20]. In addition, the time constrains to achieve the goal modifying the score of training matches and tasks duration also increases mental fatigue [21].

However, to our knowledge no previous studies have analyzed the influence of added rules in pass decisions (e.g., all players must touch the ball to score a valid goal) on physical and mental load, although this strategy is frequently used during soccer tasks. First, we hypothesize (1) that the restrictions in pass decisions will increase the internal and external physical load of the soccer tasks. To justify this hypothesis, we highlight that previous studies that used constraints like the limitation of ball touches or unbalance have observed an increase in one vs. one duels, the distance covered, and Rated Perceived Exertion Scale (RPE) values [15,26,27]. Additionally, in our opinion, to achieve the objectives during pass limitations tasks, players must optimize the space and increase the speed of the ball, which can increase the physical demands [27]. Secondly, we hypothesize (2) that the mental load and mental fatigue of the soccer tasks will increase with the use of the constraint in pass decisions. This assumption is based on previous studies reporting increases in the attention level [5] and cognitive demands in highly-complex environments [10] or decreases in the motivation levels [28] due to the frustration caused by worse performance. Moreover, the increases in mental fatigue (2) could have negative effects on physical performance (1) [29,30].

We consider that the present study could contribute information about how restrictions in pass decisions may affect the training load. This information can increase the control of the load changes produced by this frequently used constraint, so it can be important for coaches and practitioners. This study aimed to analyze the effects of rules in pass decisions on the physical and mental load and fatigue of soccer training tasks.

#### **2. Materials and Methods**

#### *2.1. Participants*

Participants were 40 semi-professional soccer players from two Spanish male teams (*M*age = 22.90, *SD* = 5.60) belonging to the Third Spanish League (*n =* 20) and the u-18 First Spanish League (*n* = 20). All of them participated voluntarily in the study. The two teams performed four training sessions per week (ranging between 90 to 100 min), and all players had a minimum soccer experience of 14 years. Respect to the inclusion criteria of the players, we consulted previous experts [24,25]. The criteria for players' inclusion were: (1) players who regularly attended training sessions, and (2) players optimally accustomed to demanding training sessions, without recent injuries. According to these criteria, eight players (three players belonging to the senior team and five players belonging to the u-18 team) were excluded.

#### *2.2. Instruments*

#### 2.2.1. Polar Team Pro System (Polar Electro, Finland)

To analyze mean and peak heart rate, mean and peak speed, distance/minute, and the number of sprints (accelerations over 2.8 m/s2), the Polar Team Pro, a global position system (GPS) was used. This technology is based on a signal concentration system of different Polar brand sensors, designed for the control and monitoring of physical activity in collective sports like soccer or basketball. This technology has been validated [31,32] and used in previous studies that registered the physical load of soccer tasks [10,19] and is currently one of the most used instruments for the quantification of the physical load in this context [33].

#### 2.2.2. Rate of Perceived Exertion

The Rated Perceived Exertion Scale (RPE) was used to quantify the perception of effort by soccer players. This instrument has been used to control the internal physical load, through the registration of the player's exhaustion level after a physical or sports activity. The RPE includes values ranging from 0 (*not at all tired*) to 10 (*maximum exhaustion*), and its use and accuracy in soccer tasks has been proved [34].

#### 2.2.3. NASA-Task Load Index

To analyze the mental load, an adaptation of the NASA-Task Load Index (NASA-TLX) was used. The original NASA- TXL is one of the most used scales in organizational psychology. Specifically, this adaptation asked about specific soccer-related mental and physical effort, time pressure, performance satisfaction, general effort, unsafety, and interaction. This instrument includes values from 0 (*no load*) to 10 (*maximum load*) for each item described. The validity of this instrument in soccer has been demonstrated in previous studies [10,19] and it was validated [35,36]. The internal consistency (obtained by the mean value of these two times) of this scale was acceptable (Cronbach's alpha = 0.75) with adequate temporal stability (test–retest r = 0.90).

#### 2.2.4. Visual Analog Scale (VASfatigue)

The Visual Analogue Scale 100 (VAS100) was used to quantify the mental fatigue perception of the players [37]. Originally, this procedure established a scale that includes values from 0 (*no fatigue perceived*) to 100 (*maximum fatigue perceived*) and players indicated their general fatigue perception. Participants were instructed to "Please mark the point in the line that represents your current state of mental fatigue." The accuracy of this scale has been proven in soccer samples for the purpose described herein [38].

#### *2.3. Study Design and Procedures*

All research procedures were conducted in accordance with the Declaration of Helsinki (World Medical Association, 2013) and had the approval of Ethics Committee for Research with Human Beings. (approval number: 93/2020). All participants were informed about the objective of the study and signed informed consent.

Two training sessions (A and B) with four tasks were completed by each team. This intervention was carried out at the mid-season phase (from January to March in the Spanish national competitions). The first experimental session was developed three days after the last match (on Wednesday), whereas the next match was played three days after the first experimental session had finished. The second experimental session was performed exactly one week after (also on Wednesday) the first session was performed, with the same preand post-match rest days, as explained. These training sessions included the same type of

task with a modification in the score system constraint: Tasks 1 and 2 were MBPG, whereas Tasks 3 and 4 were MBPG-G. A restriction in pass decisions was included in one of each type of task per session (one MBGP and MBPG-G with pass limitations and one MBPG and MBPG-G without pass limitations per session). The manipulation of the limitation in pass decision was implemented by the next condition: a minimum number of players (at least three jokers, in this case) had to participate in the passes before achieving the goal (goal was not valid if this condition was not met). Additionally, to control the residual effects, the tasks were presented in counterbalanced order (see Table 1) between the teams (Team 1: Session A–B; Team 2: B–A). The inter-task rest time was two minutes between T1–T2, and T2–T3, and four minutes between T3–T4, and T4–T5. The inter-task time was used by the players to complete the VAS-100, the adaptation of the NASA-TXL, and RPE. The sample had previously experience with these instruments, as they completed an initial measure, which was not taken into account for the investigation, and this ensured that the scales were understood.

**Table 1.** Design of the investigation. Task description and order.

*Note*: T1 = Task 1, T2 = Task 2, T3 = Task 3, T4 = Task 4.

#### *2.4. Data Analysis*

The statistical program SPSS 25.0 (2017) and Hopkins' (2017) specific pre-post crossover spreadsheet were used to analyze the data obtained [39]. Data were expressed as mean and standard deviation values for all variables described. A paired t-Test was performed for each variable and pair of tasks (e.g., mental load in Task 1 of Session A and Task 2 of Session B compared with mental load in Task 2 of Session A and Task 1 of Session B). Significant levels were set at 0.1%, 1%, and 5%. Additionally, the magnitude of change in terms of effect sizes (ES) [40], was calculated with the spreadsheet named [37]. The ES were classified as: trivial (<0.2), small (0.2–0.6), moderate (0.6–1.2), large (1.2–2.0) and very large (>2.0) [41]. Magnitude-based inferences (MBI), using the confidence intervals, were used to determine the possible benefit, like positive or negative changes, of the mental and physical load and fatigue between tasks. The smallest worthwhile change (SWC) to assess the change for variables between tasks was set at an ES of 0.2 [41]. Moreover, a qualitative analysis of the changes was performed: 0.5% to 5%, very unlikely; 5% to 25%, unlikely; 25% to 75%, possibly; 75% to 95%, likely; 95% to 99.5%, very likely; and > 99.5%, most likely [42]. The use of these two types of statistical analysis (*p*-values and MBI) is based on Holgado et al.'s affirmation according to previously reported data about the statistical negative effects of mental fatigue on physical performance or the fatigue that could have been caused by statistical errors [43].

#### **3. Results**

#### *3.1. Internal Physical Load*

The comparison between internal physical load values is shown in Table 2. Significant differences were found in peak heart rate and RPE during MBPG between the two conditions, with higher values in MBPG tasks with the use of pass constraint. For internal physical load values, no significant differences were found for MBPG-G between normal and pass restriction conditions. These results agree with the results shown by the MBI between these two conditions.

**Table 2.** Internal physical load results between pairs of tasks.

*Note*. T1 = Task 1, T2 = Task 2, T3 = Task 3, T4 = Task 4. NOPR = no pass restriction, PR = pass restriction. ES = effect size, QI = qualitative inference, +ive = positive. \*\*\* *p* < 0.001, \*\* *p* < 0.01.

#### *3.2. External Physical Load*

Table 3 presents the results of external physical load. Distance/minute and mean speed presented significant changes in the MBPG score system. In this case, distance/minute showed higher values without pass limitations, whereas the mean speed was higher in MBPG with pass limitations. No significant differences in the MBPG-G score system was observed in these variables between the two conditions. The results obtained by the MBI analysis supported the findings with unclear changes in peak speed and number of sprints for MBPG and all variables during the MBPG-G.

**Table 3.** External physical load results between pairs of tasks.

*Note*. T1 = Task 1, T2 = Task 2, T3 = Task 3, T4 = Task 4. NOPR = no pass restriction, PR = pass restriction. ES = effect size, QI = qualitative inference, +ive = positive, –ive = negative. \*\*\* *p* < 0.001. \*\* *p* < 0.01, \* *p* < 0.05.

#### *3.3. Mental Load and Fatigue*

Finally, descriptive values and the comparison of pairs of tasks for mental variables are presented in Table 4. According to the *p*-value analysis, only time pressure in the MBPG showed significant changes, with higher values in the limitation tasks. However, according to the MBI analysis, mental effort and fatigue for MBPG and performance satisfaction during MBPG-G showed very or most likely changes with higher values in tasks with pass limitations. Mental effort represents the real mental resources that the players use to achieve the goal and it produces mental fatigue Thus, the relation between these variables is clear. The rest of the mental variables (unsafety and interaction) compared for these two types of tasks did not show relevant differences (either with *p*-values or MBI analysis), although all results were higher for these variables in pass limitation conditions, both in the MBPG and the MBPG-G score system.

*Note*. T1 = Task 1, T2 = Task 2, T3 = Task 3, T4 = Task 4. NOPR = no pass restriction, PR = pass restriction. ES = effect size, QI = qualitative inference, +ive = positive. \*\*\* *p* < 0.001.

#### **4. Discussion**

The purpose of this study was to analyze the effects of limiting pass decisions on physical and mental load and fatigue during soccer training tasks through a rule stating that the goal is only valid if a minimum number of players participate in the passes before achieving the goal. Thus, we proposed two training sessions with the same tasks (with or without the constraint) and compared their results. The main findings of the study suggested that RPE and mental fatigue levels were affected by these constraints because higher values were found in these variables using the limitation, especially during the MBPG score system tasks. However, the external physical load reported by players was not affected or decreased by the use of constraints in pass decisions, either in MBPG or MBPG-G.

We expected (Hypotheses (1) that the limitation in pass decisions would increase internal and external physical values. Indeed, internal load results were higher during the limitation tasks. However, contrary to the hypothesis, most of the external physical values were higher or unchanged in no-limitation tasks. Previous research showed synergistic increases/decreases both in internal and external physical load with the use of soccer constraints like the size of the pitch [2,11,15]. However, we cannot consider these constraints as similar to pass constraints decisions. Other previous constraints and tactical behaviors more closely related to this constraint such as player's unbalanced or the limitation in the ball touches can increase the external physical load through the players' distributions, the increase in the speed of the ball or the type of defender marking derived from the tasks and limitations. These constraints showed increases both in internal and external load [15,26]. However, the level of the participants (semi-professionals) or the complexity of the task designed could be the key to the results of the present study, due to a greater number of errors in the pass and less effective time of practice [44]. This could explain the important decreases shown in the MBI analysis for distance/minute.

On another hand, the disagreement between the decreases in external load and the increases in the internal load values could be explained by the mediated effect of mental fatigue. This explanation is justified by the psychobiological model. This model is characterized by increases in internal load (RPE) values without increases in external load [45]. According to this model, the increase in internal physical load (RPE) observed during these situations is mediated by the mental load increases, and according to these authors, the external physical not changed. These statements agree with the results of the present study, which showed unchanged/decreased values for external load and important increases in the internal load values. Another possible explanation is that the decreases in the distances covered with tactical objectives are caused by the effects of mental fatigue on physical performance. This behavior was observed by Coutinho et al. (2018) but, in our opinion, this explanation is improbable in the present study due to (i) the duration of the task and (ii) the team's tactical behavior is more influenced by the objective of the task.

 Specifically, the results confirmed that mental and physical effort, time pressure, and mental fatigue increased in MBPG. Additionally, positive and significant changes in performance satisfaction were obtained for MBPG-G. The increases in mental load values due to the pass decision constraint could be influenced by the extra mental effort that this limitation produces in players because they must increase their attention and cognitive levels to achieve the objectives and conditions of the training tasks. Other previous studies confirmed that the task's entropy can increase with the use of soccer constraints like the scoring system [10] or the task's objective [19]. However, contrary to the results shown by Ponce-Bordon et al. (2020), these constraints have a higher effect in MBPG than in MBPG-G. These results could be explained by the increase in the complexity of the development or the higher level of stress caused by these types of tasks [46]. These statements coincide with the increases in performance satisfaction during MBPG-G.

Concerning mental fatigue, it is difficult to find studies to discuss the results found, because most of the studies published do not use specific soccer strategies. In this sense, Thompson et al. (2020) proved that the use of Stroop tasks before measuring sports performance has increased knowledge about mental fatigue, but mental fatigue accumulation does not occur before matches; the accumulation of mental fatigue occurs during and after soccer matches. The importance of studies that increase the information and practical applications about how coaches can manipulate mental fatigue with specific soccer strategies has been highlighted by these authors. Moreover, the control of these types of fatigue is very important because an important increase in the accumulation of mental fatigue levels can reduce soccer performance [12].

#### *4.1. Study Limitations and Future Research*

Probably, the main limitations of the study were the exclusion of the previous training mental fatigue levels and the effective time of practice. In future research, the quantification of prior mental fatigue levels (before the task) could increase the information obtained. Additionally, the inclusion of the effective time of practice and information about all types of fatigue. Another interesting aspect is the implementation of this intervention at different moments of the season (early, mid, or end-season), because the training load is not the same during the whole season. The different influence of this constraint on the types of tasks may also be considerable.

On the other hand, in future studies it could be interesting to analyze the implementation of this constraint during more training sessions or other types of tasks, different from MBPG and MBPG-G, comparing the types of tasks. Additionally, it would be interesting to compare the fatigue that different tasks induced. Future research should examine the differences between these results and the findings obtained with professional players or even the quantification of the effective practice time.

#### *4.2. Practical Implications*

In our opinion, these results add important information for researchers, practitioners, and coaches about the use of this constraint. The use of this limitation in pass decisions is a frequently used strategy during soccer training sessions, and based on the effects reported in this research, coaches can use this specific soccer constraint to manipulate the load according to their objectives.

#### **5. Conclusions**

The present study confirmed that the use of pass restrictions during soccer tasks may modify the effort perceptions and mental fatigue reported by players during soccer training sessions. Specifically, these variables increase with the use of these restrictions, with higher effects in MBPG tasks than in MBPG-G. These increases are probably mediated by the effect of mental fatigue on internal physical load, because the values of the external physical load were not modified. The cause of these unchanged values of external values could be the decreases in effective practice time, which could be caused by the complexity of this constraint or the player's level.

**Author Contributions:** Conceptualization, T.G.-C., J.J.P. and J.D.-G.; methodology, T.G.-C., J.J.P., M.A.L.-G. and J.D.-G.; software, T.G.-C., J.C.P.-B., and J.D.-G.; formal analysis, T.G.-C., I.T.-C. and J.D.- G.; investigation, T.G.-C., J.J.P., J.C.P.-B., M.A.L.-G. and J.D.-G.; resources, T.G.-C., J.J.P. and J.D.-G., data curation, T.G.-C., J.C.P.-B., M.A.L.-G. and J.D.-G.; writing—original draft preparation, T.G.-C., J.J.P., J.C.P.-B., M.A.L.-G. and J.D.-G.; writing—review and editing, J.J.P. and I.T.-C.; visualization, T.G.-C., J.J.P. and I.T.-C.; supervision, T.G.-C., J.J.P. and J.D.-G.; project administration, T.G.-C., J.C.P.- B., and J.D.-G.; funding acquisition, T.G.-C., J.J.P. and J.D.-G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was funded by the Real Madrid-UEM Chair, in the 2017–2018 call. In addition, it was supported by the Assistance to Research Groups (GR18102) of the Junta de Extremadura (Ministry of Employment and Infrastructure); with the contribution of the European Union through the European Regional Development Funds (ERDF). Additionally, this research was supported by the Government of Spain (Ministry of Science and Innovation) to J.D.-G. (FPU18/03660) and J.J.P. (IJC2019-040788-I).

**Institutional Review Board Statement:** The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee for Research with Human Beings. Of the University of Extremadura, Spain (protocol code: 93/2020).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** https://osf.io/wvgxc/ (accessed on 17 April 2021).

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

### *Article* **Muscle Damage and Performance after Single and Multiple Simulated Matches in University Elite Female Soccer Players**

**Tai-Ying Chou 1,2, Kazunori Nosaka 3 and Trevor C. Chen 2,\***

**Abstract:** The present study aimed to compare changes in muscle damage and performance parameters after playing single versus multiple soccer matches to examine fixture congestion effects on performance. Twelve elite female university soccer players performed single, three and six consecutive 90-min bouts of the Loughborough Intermittent Shuttle Test (LIST) with ≥12-weeks between conditions in a pseudo-randomized order. Heart rate, blood lactate, rating of perceived exertion and covering distance in each LIST were examined. Changes in several types of muscle damage (e.g., maximal voluntary isometric torque of the knee extensors: MVC-KE) and performance measures (e.g., Yo-Yo Intermittent Recovery Test level 1: YYIR1) were taken before each LIST, 1 h, and 1–5 d after the last LIST. The total distance covered during the LIST was shorter (*p* < 0.05) in the 2nd–3rd, or 2nd–6th LISTs when compared with the 1st LIST. Changes (*p* < 0.05) in all measures were observed after the LIST, and the greatest changes were observed after the six than after the three LISTs followed by one LIST (e.g., largest changes in MVC-KE: −26 > −20 > −14%; YYIR1: −31 > −26 > −11%). Many of the variables did not recover to the baseline for 5 d after six LISTs. These suggest that fixture congestion induces greater muscle damage and performance decline than a single match.

**Keywords:** soccer; football; Loughborough Intermittent Shuttle Test; muscle soreness; maximal isometric contraction strength; countermovement jump; Yo-Yo Intermittent Recovery Test level 1

#### **1. Introduction**

Playing a soccer (football) match induces muscle damage that is represented by a combination of delayed onset muscle soreness and prolonged decreases in muscle function [1–4]. Systematic review papers have shown that a soccer match alters muscle damage markers, impairs physical performance such as sprint and jump abilities [5], and exacerbates perceptual responses for at least three days post-match [6]. Andersen et al. [1] showed significant decreases in sprint performance (−3%), countermovement jump (CMJ) height (−4%), peak concentric contraction torque of knee extension (−7%) and flexion (−9%), and increases in serum creatine kinase (CK) activity (+152%) and muscle soreness in Swedish and Norwegian female players after the first friendly international soccer match of the season in the highest division, and CMJ height was still reduced (−3%) at the beginning of the second match performed three days later. Moreover, Hughes et al. [4] found that muscle soreness and increased plasma CK activity lasted for seven days after an official soccer match of youth female players. Additionally, Thomas et al. [3] reported that maximal voluntary isometric contraction (MVC) torque of the knee extensors (MVC-KE) and countermovement jump (CMJ) height decreased, muscle soreness developed and plasma creatine kinase (CK) activity increased for three days after 90 min of a simulated soccer match using the Loughborough Intermittent Shuttle Test (LIST) performed by 15 male

**Citation:** Chou, T.-Y.; Nosaka, K.; Chen, T.C. Muscle Damage and Performance after Single and Multiple Simulated Matches in University Elite Female Soccer Players. *Int. J. Environ. Res. Public Health* **2021**, *18*, 4134. https:// doi.org/10.3390/ijerph18084134

Academic Editor: Paul Tchounwou

Received: 15 March 2021 Accepted: 10 April 2021 Published: 14 April 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

semi-professional male soccer players. Considering the time it takes for recovery from an official or a simulated match, it appears that performance in a match is affected by a previous match if the interval between matches is short. However, the magnitude of the effects of multiple matches on muscle damage and performance have not been well documented.

Julian et al. [6] defined "fixture congestion" as a minimum of two successive official soccer matches, and examined the effects of an inter-match recovery period of ≤4 days on adult male players using a semi-automated video system and/or GPS device. They showed that fixture congestion affected variables such as the low- and moderate-intensity distance covered but did not affect the total distance covered, probably due to pacing strategies to maintain high-intensity movements. The authors suggested that with ever increasing numbers of competitive matches scheduled, more research was required using consistent measures of performance with an integration of physical, technical and tactical aspects. Although professional soccer leagues do not require their teams to play official matches over successive days, multiple soccer matches are played with short intervals in some tournaments [7,8]. A common challenge for players competing in these tournaments is that the time available for full recovery between matches is limited, thus physical performance might be reduced in successive matches, and risks of injuries may be increased.

Some studies have demonstrated that residual fatigue accumulated over three to four successive soccer matches and performance is adversely affected in junior and young male players [7–11]. Benítez-Jiménez et al. [8] reported that a significant decrease in CMJ height during three consecutive friendly soccer matches played daily over three days (match 1: −14%; match 2: −19%; match 3: −14%; two days after match 3: −15%), when compared to the baseline level in 22 youth male players. Similarly, Chaves et al. [7] showed a decrease in perceived recovery when the U−19 male players had four competitive matches in four days. Additionally, even if the match frequency was less, Saidi et al. [12] showed significant decreases in the Yo-Yo Intermittent Recovery Test level 1 (YYIR1; −35%), repeated shuttle sprint ability (−3%), and squat jump (−3%) after 10 soccer matches played over six weeks by male soccer players. Carling et al. [13] suggested a need for research to examine the extent to which players' match running profiles were compromised during intensified competition periods. It seems likely that as more matches are performed, the greater impairment of muscle and physical function is induced. However, no previous study has systematically investigated the effects of playing multiple soccer matches with short intervals on muscle damage and fatigue and performance of female players.

Therefore, the aim of the present study was to investigate changes in indirect markers of muscle damage and performance variables after multiple (three and six) simulated soccer matches (90-min LIST) performed by elite female university soccer players in comparisn to a single LIST condition. In the present study, the same players performed a LIST or three or six LISTs on consecutive days, and performance in the LIST, several indirect markers of muscle damage, and soccer-specific performance measures were taken before every LIST, one hour, and one to five days after the last LIST. The six LIST conditions were included as a possible worst-case scenario. It was hypothesized that the recovery and changes in muscle damage and performance variables would be slower and greater in the order of six LISTs, three LISTs, and the single LIST.

#### **2. Materials and Methods**

#### *2.1. Experimental Approach and Study Design*

In order to simulate soccer matches, a 90-min LIST protocol was used to mimic a typical soccer match [3,14,15]. In a pseudo-randomized, counterbalanced design, 12 elite female university soccer players played a single LIST, three LISTs and six LISTs, with more than 12 weeks between conditions (Figure 1A). The LISTs were performed in the same indoor facility in which the environmental temperature was 30–34 ◦C and relative humidity was 77–85% for all conditions. Six days before the first session, the participants were familiarized with all test procedures. They also performed a maximal oxygen consumption (VO2max) test three to four days before the first session to calculate the speeds (55% and 95% VO2max) applied during the LIST. To examine the effects of the LISTs on muscle damage and performance, MVC-KE and maximal voluntary isometric contraction torque of knee flexors (MVC-KF), muscle soreness of the knee extensors (SOR-KE) and flexors (SOR-KF), plasma CK activity, CMJ, 30-m dash, 30-m timed hop, balance, agility *t*-test, 6 × 10-m shuttle run and YYIR1 were measured one to two days before the 1st LIST (baseline) and one hour after each LIST, and one to five days after the last LIST (Figure 1B). Changes in the variables were compared among the conditions (single LIST, three LISTs, six LISTs) by two-way repeated measures of analysis of variance (ANOVA).

**Figure 1.** Experimental design and testing procedures of the study. (**A**): Three conditions were based on the number of Loughborough Intermittent Shuttle Tests (LISTs) performed consecutively by 12 participants: one (1LIST), three (3LISTs) and six (6LISTs). The order of the three conditions was semi-counterbalanced among the participants such that 1LIST–3 LISTs–6LISTs (*n* = 4), 3LISTs–6LISTs– 1LIST (*n* = 4), and 6LISTs–1LIST–3LISTs (*n* = 4). (**B**): Time course of measurements for 1LIST, 3LISTs and 6LISTs conditions. FAM: familiarization session. V˙ O2max: maximal oxygen consumption test. PM: physiological markers including heart rate, rating of perceived exertion (RPE) and blood lactate concentration measures during the LIST. CD: total covered distance during the LIST. MD: muscle damage markers including maximal voluntary isometric contraction torque of the knee extensors (KEs) and flexors (KFs), muscle soreness of KEs and KFs, countermovement jump height, and plasma creatine kinase activity. *p*: performance parameters consisting of 30-m dash, 30-m timed hop, balance, agility *t*-test, 6 × 10-m shuttle run and Yo-Yo Intermittent Recovery Test level 1 tests.

#### *2.2. Participants*

The sample size was estimated using the data from our pilot study in which the effects of a single LIST versus three LISTs over three days on maximal voluntary isometric contraction torque of the dominant knee extensors (MVC-KE) were compared in six female soccer players. Based on the effect size of 1 for a difference in MVC-KE change post-match between the two conditions, it was estimated that at least 11 participants were necessary for each condition, with an alpha level of 0.05 and power (1 − β) of 0.80 [16]. Considering a possible drop-out and an estimation error, 12 players were recruited for the study.

Twelve elite female university soccer players who were selected for the Chinese Taipei Team of the 2018 Asian University Football Tournament provided informed consents to participate in the present study, which had been approved by the Research Ethics Committee of National Taiwan Normal University, Taiwan (Approval #: 201812HM023). The study was conducted in conformity with the policy statement regarding the use of

human subjects by the Declaration of Helsinki. None of them had injuries during the period of the data collection and completed the three conditions. They played 17–20 official matches during the experimental period of 40 weeks and had training sessions five days a week (2.5–3 h per session). The present study was performed when the players had not had an official match for more than five days before the 1st LIST, and each condition (single, three and six LISTs) was preceded by at least five days of rest. All of the players had experienced three official matches in a row, and some of them had played an official match every day for five days.

#### *2.3. Maximal Oxygen Uptake Test*

The participants performed an incremental continuous run test on a treadmill (Mercury, h/p/cosmos, Nussdorf, Traunstein, Germany) until the point of volitional fatigue to determine maximal oxygen uptake (VO2max) and maximal heart rate (HRmax). An automatic gas analysis system (Vmax29c, SensorMedics, Yorba Linda, CA, USA) was used to measure oxygen consumption. Participants warmed up at a speed of 6.4 km/h on a gradient of 1% for 5 min, and the speed was increased by 1.6 km/h every 3 min while a gradient of 1% was kept [17–20]. From the VO2max, running speeds corresponding to 55% and 95% VO2max were calculated. Thereafter, the participants performed and practiced the running corresponding to 55% and 95% VO2max on the treadmill for 5 min for each intensity.

#### *2.4. The Loughborough Intermittent Shuttle Test (LIST)*

The LIST for 90 min was performed in a sports hall according to Nicholas et al. [15]. The details of the LIST can be found elsewhere [15], but briefly, the participants were instructed to run between two lines, 20 m apart, at various velocities dictated by an audio signal for two parts: Part A and Part B.

Part A was of a fixed duration and consisted of five 15-min exercise periods separated by 3 min of recovery. The exercise periods consisted of the set pattern of intermittent high-intensity running shown below and were designed to be similar to the activity pattern typically recorded for a soccer match-play.

Part B was an open-ended period of intermittent shuttle running, designed to exhaust the participants within approximately 10 min. The participants were required to run at speeds corresponding to 55% and 95% of predicted VO2max, the speed alternating every 20 m. This pattern of exercise was repeated continuously until the participants were unable to maintain the required speed for two consecutive shuttles at the higher of the two exercise intensities.

#### *2.5. Familiarization Session*

In the familiarization session, the participants experienced the measurements of muscle soreness, countermovement jump (CMJ), sub-maximal and maximal voluntary isometric contractions at 90◦ and 30◦ of knee flexion for knee extensors and flexors, respectively, on an isokinetic dynamometer (Biodex System S4 Pro; Biodex Medical Systems, Shirley, NY, USA), 30-m dash, 30-m timed hop, balance, agility *t*-test, 6 × 10-m shuttle run and YYIR1, and performed the LIST for 20 min (Figure 1).

#### *2.6. Dependent Variables*

Heart rate (HR), rating of perceived exertion (RPE), blood lactate (LA) and distance covered during LIST.

During each LIST, heart rate (HR) was recorded by a Polar HR monitor (Polar M430, Polar Electro Oy, Kempele, Finland); rating of perceived exertion (RPE) was assessed with

a 6–20 Borg's scale [17,21]; and covering distance of each participant in each LIST was recorded manually by the investigators. Blood lactate (LA) concentration was measured by a lactate test meter (LactateScout+, h/p/cosmos, Nussdorf-Traunstein, Germany) using a capillary sample obtained from a fingertip of each participant before and 1 min after every 15 min of exercise during Part A, and 1 min after Part B of the LIST [17,22,23]. Changes in HR during each LIST were analyzed by automatic software provided by the Polar company, and all results were averaged during each LIST [3,15]. RPE was assessed immediately after each exercise period as shown in the LIST section below, and the total of six exercise periods during each LIST was averaged as the final result [3,15]. The total six different time points of blood lactate during each LIST were averaged [15].

#### *2.7. Muscle Damage Markers*

#### 2.7.1. Maximal Voluntary Isometric Contraction (MVC) Torque

MVC torque of the dominant knee extensors (MVC-KE) and flexors (MVC-KF) were adopted from our previous studies, and the details were described elsewhere [24–27]. The dominant leg was determined as the leg that was preferred for kicking a soccer ball to a target [28], and the measures were performed by the dominant leg. Each participant lay in supine and prone positions for the MVC-KE and MVC-KF measures on the platform of an isokinetic dynamometer (Biodex System S4, Shirley, NY, USA), respectively. The trunk and the dominant leg were strapped to the platform of the dynamometer. MVC-KE and MVC-KF were measured at 90◦ and 30◦ of knee flexion (0◦ = full knee extension), respectively, after gravity correction. Each participant was instructed to generate maximal force for 5 s, and this was repeated three times with 45 s rest between trials, and 5 min was provided between MVC-KE and MVC-KF measures, and the highest value of the three measurements was used for further analysis for each measure.

#### 2.7.2. Countermovement Jump (CMJ)

CMJ was considered to be a marker of muscle damage, according to previous studies [29–31], although CMJ is also used as a performance measure in soccer studies [2,32]. The participant stood erect with a knee angle of 0◦ (0◦ = full knee extension) with hands on hips and performed a countermovement until the knee angle reached an approximate 90◦ angle, followed immediately by a vertical jump as high as possible [33–35]. CMJ was performed on a jumping mat (Smart Jump, Fusion Sport, Queensland, Australia). The jumps were interspersed with a 30-s rest period, and the best jump (in cm) among three trials was used as the test result.

#### 2.7.3. Muscle Soreness

Muscle soreness was quantified by a visual analog scale that had a 100-mm continuous line with "not sore at all" on one end (0 mm) and "very, very sore" on the other end (100 mm). Muscle soreness of the dominant knee extensors and flexors was assessed, separately, when each participant performed a full squat of dominant knee extensors and flexors, respectively [18,19,36].

#### 2.7.4. Plasma CK Activity

Approximately 5 mL of venous blood was withdrawn by a standard venipuncture technique from the cubital fossa region and centrifuged for 10 min to extract plasma, and the plasma samples were stored at −80 ◦C until analyses. Plasma CK activity was assayed spectrophotometrically by an automated clinical chemistry analyzer (Model 7080, Hitachi, Co. Ltd., Tokyo, Japan) using a commercial test kit (Roche Diagnostics, Indianapolis, Indiana) [18,37].

#### *2.8. Performance Indices*

Before the tests, all the participants performed warm-up exercises consisting of jogging, specific mobility exercises and stretching routines, and three 10-m sprints in 10–15 min. All measures (30-m dash, 30-m timed hop, balance, agility *t*-test, 6 × 10-m shuttle run and YYIR1 tests) were performed indoors, and the order of measures was 30-m dash, balance, 30-m timed hop, agility *t*-test, 6 × 10-m shuttle run and YYIR1 tests with 5–10 min rest between tests. All participants had performed these tests regularly (eight times a year) for one year before the present study in a project by the Sport Administration, Ministry of Education (Taiwan); thus, they were familiar with the tests. However, performing all tests over consecutive days had not been done before the current study.

#### 2.8.1. 30-m Dash

Sprint ability was assessed using telemetric photoelectric cells placed at 0, 10, 20 and 30 m (Smart Speed, Fusion Sport, Queensland, Australia). Each participant stood 0.3 m behind the starting line, started on a verbal signal being time-activated when the player crossed the first pair of photocells, and was instructed to run as fast as possible to complete the 30-m distance [32]. Participants completed two runs interspersed by a 1-min recovery period, and the best time was used for further analysis.

#### 2.8.2. 30-m Timed Hop Test

The 30-m timed hop test was adapted from a previous study [38]. The 30-m timed hop test protocol was the same as that of the 30-m dash, but the difference was that the participants used their dominant leg to hop as fast as possible over a distance of 30 m. Participants completed two tests interspersed by a 2-min recovery period and the best time was used for further analysis.

#### 2.8.3. Balance Test

The present study used a test of eyes closed on unstable surface (ECUS) as a measure of balance ability using the Biodex BioSway Portable Balance System (Model 950–460; Biodex Medical Systems, Shirley, NY, USA). Each participant was instructed to maintain her feet on the platform for 30 s for each test and had a 30-s rest between tests. Based on the study by Collado-Mateo et al. [39], a heel-to-heel distance of 16 cm and an external rotation of 15◦ were set. The sway index (SI) quantifying sways over the 30 s was calculated as the standard deviation (SD) of the sway angle [39]. Participants completed two tests interspersed by a 30-s recovery period, and the best result (i.e., SI) was used for further analysis.

#### 2.8.4. Agility *t*-Test

An adapted version of the *t*-test by Semenick [40,41] was used. Each participant sprinted forward (9.14 m), shuffled to the left (4.57 m) and to the right (9.14 m), shuffled back to the left (4.57 m), and ran backward to the starting point. The time was measured by the same telemetric photoelectric cells as those for the 30-m dash. Two trials were performed with a 3-min rest between trials, and the better time was used for further analysis.

#### 2.8.5. 6 × 10-m Shuttle Run

The 6 × 10-m shuttle run was carried out using the same telemetric photoelectric cells placed at the start line and 10 m. Each participant stood 0.3 m behind the start line, started on a verbal signal being time-activated when the participant crossed the first pair of photocells, and was instructed to run as fast as possible to complete the 10-m distance and then returned to the starting line for six repetitions. Players completed two runs interspersed by a 5-min recovery period, and the best time was used for further analysis.

#### 2.8.6. Yo-Yo Intermittent Recovery Test Level 1 (YYIR1)

Endurance was assessed through the YYIR1, commonly used to assess endurance performance in soccer players [42]. Keeping to a series of beeps, participants were required to run 20 m shuttles, followed by a 10-s rest interval. The test's running speed increased progressively throughout until the players reached volitional exhaustion or until participants missed two beeps, resulting in the test being terminated. Participants completed one

run on each time point, and consistent verbal encouragement was given to participants during the YYIR1. Total running distance, HR and RPE during the YYIR1 were recorded.

#### *2.9. Statistical Analyses*

Data were verified by a Shapiro–Wilk test for the normality and a Levene test for the homogeneity of variance assumption. All dependent variables before the single LIST condition, the 1st LIST of the three LIST and six LIST conditions were compared by one-way ANOVA. Changes in HR, RPE, lactate concentration, total distance covered during the LIST were compared among the trials and conditions by two-way repeated measures ANOVA. Changes in each dependent variable before, 1 h after, and 1–5 d after the 1st, 3rd and 6th LIST for the single LIST, three LIST and six LIST conditions, respectively, were compared by two-way repeated measures ANOVA.

The normalized changes in muscle damage and performance measures from the baseline at 1 h and 1–5 d after the 1st LIST for the single, three and six LIST conditions were obtained and were compared by two-way repeated measures ANOVA. When a significant interaction effect was found, a Tukey's post-hoc test was performed, and η2 was calculated as a measure of effect size, which was considered as ~0.02 = small effect; ~0.13 = medium effect; and >0.26 = large effect [43]. Cohen's *d* effect size (ES) was calculated by the method of Thalheimer and Cook [44] based on the largest changes for the single versus three, three versus six, and single versus six LIST conditions, respectively. ES of 0.2, 0.5, and 0.8 were considered as a small, medium, and large effect, respectively [16]. Pearson Product-Moment Correlation coefficient (r) was used to examine the relationships between the magnitudes of decreases in MVC-KE, MVC-KF or CMJ (% change from the baseline) at 1 d after a single LIST, three LISTs and six LISTs (*n* = 36) and the magnitudes of change in peak muscle soreness of KE and KF as well as peak CK after a single LIST, three LISTs and six LISTs. Similarly, the correlation analyses were performed for the magnitude of the decreases in MVC-KE, MVC-KF or CMJ and the magnitude of changes in the 30-m dash, 30-m timed hop test, balance, agility *t*-test, 6 × 10 m shuttle run and YYIR1 at 1 d after the single LIST, three LISTs and six LISTs (*n* = 36). A significant level was set at *p* ≤ 0.05. The data were presented as mean ± SD.

#### **3. Results**

#### *3.1. Baseline Measurements*

The mean ± SD (range) age, height, body mass, percentage of body fat, and maximal oxygen consumption (VO2max) of the participants were 21.0 ± 1.1 (19–23) y, 159.1 ± 4.6 (152–165) cm, 56.2 ± 6.7 (45–65) kg, 14.4 ± 4.3 (7.3–21.5)%, and 54.1 ± 4.4 (47.9–59.2) mL/kg/min, respectively. No significant differences in the baseline MVC-KE (*p* = 0.919, η2 = 0.008), MVC-KF (*p* = 0.959, η2 = 0.004), muscle soreness of KE (*p* = 1.00, η2 = 0.000) and KF (*p* = 1.00, η2 = 0.000), plasma CK activity (*p* = 0.562, η2 = 0.051), CMJ (*p* = 0.739, η2 = 0.027), 30-m dash (*p* = 0.943, η2 = 0.005), 30-m timed hop test (*p* = 0.992, η2 = 0.001), balance (*p* = 0.909, η2 = 0.009), agility *t*-test (*p* = 0.995, η2 = 0.001), 6 × 10-m shuttle run (*p* = 0.832, η2 = 0.017), and YYIR1 (average distance: *p* = 0.850, η2 = 0.015) were evident among the single LIST, three LIST and six LIST conditions (Figures 3 and 4). Before the 1st LIST, no significant differences among the conditions were found for HR (*p* = 0.907, η2 = 0.009), RPE (*p* = 0.426, η2 = 0.075), and LA concentration (*p* = 0.398, η2 = 0.080).

#### *3.2. HR, RPE, LA and Distance Covered during LIST*

No significant differences in the total distance covered (*p* = 0.951, η2 = 0.005), HR (*p* = 0.632, η2 = 0.041), RPE (*p* = 0.637, η2 = 0.040), and post-exercise LA (*p* = 0.866, η2 = 0.013) in the 1st LIST were found among the three conditions (Figure 2). Changes in average HR (*p* = 0.632, η2 = 0.041), RPE (*p* = 0.637, η2 = 0.040) and LA (*p* = 0.866, η2 = 0.013) during the 1st LIST were similar among the conditions (Figure 2b–d). The total distances covered during the LISTs were significantly shorter (*p* < 0.001) in the 2nd to 6th LISTs (10,088 ± 493 m–10,330 ± 628 m) for six LISTs (η2 = 0.418), and the 2nd (10,277 ± 220 m)

and 3rd LISTs (9883 ± 339 m) for three LISTs (η2 = 0.580) when compared with the 1st LIST of all conditions (10,844 ± 528 m; Figure 2a).

**Figure 2.** Average changes (mean ± SD) in the total distance covered (**a**), heart rate (**b**), ratings of perceived exertion (RPE, (**c**))**,** and blood lactate concentration (LA, (**d**)) in the Loughborough Intermittent Shuttle Test (LIST) for one LIST (Single), three LISTs (Three) and six LISTs (Six) conditions. An asterisk (\*) indicates a significant difference (*p* < 0.05) between Single and Three conditions; a hash (#) indicates a significant difference (*p* < 0.05) between Single and Six conditions.

The baselines of LA (*p* = 0.012, η2 = 0.230; 2.3 ± 0.9–2.9 ± 0.8 mM/L), HR (*p* = 0.005, η2 = 0.255; 76.5 ± 6.1–78.3 ± 5.0 bpm), and RPE (*p* < 0.001, η2 = 0.546; 8.8 ± 2.0–10.3 ± 2.0) before the 2nd to 5th or 6th LIST of the six LISTs were significantly greater than those before the 1st LIST (LA: 1.9 ± 0.5 mM/L, HR: 72.8 ± 4.2 bpm, RPE: 6.8 ± 0.4). This was also the case for the baselines of LA (*p* < 0.001, η2 = 0.571; 2.8 ± 1.0–3.3 ± 1.4 mM/L), HR (*p* = 0.009, η2 = 0.347; 75.0 ± 2.8–77.9 ± 7.9 bpm) and RPE (*p* < 0.001, η2 = 0.811; 9.4 ± 1.3–10.6 ± 2.2) before the 2nd and 3rd LISTs of the three and six LISTs when compared with the 1st LIST (LA: 1.9 ± 0.5 mM/L, HR: 81.8 ± 3.8 bpm, RPE: 7.3 ± 0.8).

#### *3.3. Changes in Muscle Damage Markers*

Figure 3 shows changes in muscle damage parameters before the 1st LIST, 1 h (Day 1) after the single LIST, 1 h after each LIST for the three LISTs (Day 1–3) and six LISTs (Day 1– 6), and 1–5 d after the single LIST (Day 2–6), three LISTs (Day 4–8) and six LISTs (Day 7–11). The magnitude of decrease in MVC-KE and MVC-KF at 1 h after the LIST was greater (*p* < 0.001) after six LISTs (KE: η2 = 0.964; KF: η2 = 0.853) and three LISTs (KE: η2 = 0.724; KF: η2 = 0.633) than a single LIST, and the decreases were greater (*p* < 0.01) after six LISTs than three LISTs (KE: η2 = 0.712; KF: η2 = 0.625). The recovery of MVC-KE and MVC-KF was slower (*p* < 0.01) after six LISTs (interaction effect: KE: η2 = 0.831; KF: η2 = 0.722) and three LISTs (KE: η2 = 0.552; KF: η2 = 0.243) than a single LIST, and after six LISTs than three LISTs (KE: η2 = 0.552; η2 = 0.287).

**Figure 3.** Changes (mean ± SD) in maximal voluntary isometric contraction torque of the knee extensors (MVC-KE, (**a**)) and flexors (MVC-KF, (**b**)), muscle soreness assessed by a 100-mm visual analog scale of the KE (**c**) and KF (**d**), countermovement jump height (CMJ, (**e**)), and plasma creatine kinase (CK) activity (**f**) at baseline (0), 1 h after the Loughborough Intermittent Shuttle Test (LIST) (Day 1), and 1, 2, 3, 4 and 5 d (Day 2–6) after the LIST (Single), before the 1st LIST (0), 1 h after each LIST performed 3 d in a row (Day 1–3) and 1, 2, 3, 4 and 5 d (Day 4–8) after the 3rd LIST (Three), and before the 1st LIST (0), 1 h after each LIST performed 6 d in a row (Day 1–6) and 1, 2, 3, 4 and 5 d (Day 7–11) after the 6th LIST (Six). \* indicates a significant (*p* < 0.05) difference between groups based on the interaction effect shown by the ANOVA. # indicates a significant (*p* < 0.05) difference from the baseline value.

The magnitude of decrease in CMJ height was greater after six LISTs (*p* = 0.001, η2 = 0.641) than a single LIST, and the decreases were greater after six LISTs than three LISTs (*p* < 0.001, η2 = 0.699) without differences between three LISTs and a single LIST (*p* = 0.238, η2 = 0.124). The recovery of CMJ height was slower (*p* < 0.001) after six LISTs (η2 = 0.748) and three LISTs (η2 = 0.346) than a single LIST, and after six LISTs than three LISTs (*p* < 0.001, η2 = 0.517).

Muscle soreness of KE and KF after six LISTs (KE: *p* < 0.001, η2 = 0.400; KF: *p* < 0.001, η2 = 0.479) and three LISTs (KE: *p* = 0.022, η2 = 0.208; KF: *p* = 0.026, η2 = 0.202) was significantly greater than that after a single LIST, and after six LISTs than three LISTs (KE: *p* = 0.012, η2 = 0.228; KF: *p* = 0.016, η2 = 0.219). The extent of increases in plasma CK activity after six LISTs (η2 = 0.738) and three LISTs (η2 = 0.745) was significantly greater (*p* < 0.001) than that after a single LIST, and the increases were greater after six LISTs than three LISTs (*p* < 0.001, η2 = 0.721).

#### *3.4. Changes in Performance Indices*

As shown in Figure 4, the extent of changes in the 30-m dash (interaction effect; six LISTs: η2 = 0.735; three LISTs: η2 = 0.511), 30-m timed hop (six LISTs: η2 = 0.828; three LISTs: η2 = 0.382), balance (six LISTs: η2 = 0.957; three LISTs: η2 = 0.624), agility *t*-test (six LISTs: η2 = 0.748; three LISTs: η2 = 0.532), 6 × 10-m shuttle run (six LISTs: η2 = 0.731; three LISTs: η2 = 0.532), and YYIR1 (six LISTs: η2 = 0.696; three LISTs: η2 = 0.478) after six LISTs and three LISTs were significantly greater (*p* < 0.001) than that after single LIST, and the changes were greater (*p* < 0.001) after six LISTs than three LISTs (e.g., 30-m: η2 = 0.735; 30-m timed hop: η2 = 0.553; balance: η2 = 0.969; agility *t*-test: η2 = 0.517; 6 × 10-m shuttle run: η2 = 0.429; YYIR1: η2 = 0.445).

**Figure 4.** Changes (mean ± SD) in 30-m dash (**a**), 30-m timed hop test (**b**), balance with eyes closed on unstable surface (Balance, (**c**)), agility *t*-test (**d**), 6 × 10-m shuttle run (**e**), and Yo-Yo Intermittent Recovery Test level 1 (Yo-Yo IR1; (**f**)) at baseline (0), 1 h after the Loughborough Intermittent Shuttle Test (LIST) (Day 1), and 1, 2, 3, 4 and 5 d (Day 2–6) after the LIST (Single), before the 1st LIST (0), 1 h after each LIST performed 3 d in a row (Day 1–3) and 1, 2, 3, 4 and 5 d (Day 4–8) after the 3rd LIST (Three), and before the 1st LIST (0), 1 h after each LIST performed 6 d in a row (Day 1–6) and 1, 2, 3, 4 and 5 d (Day 7–11) after the 6th LIST (Six). \* indicates a significant (*p* < 0.05) difference between groups based on the interaction effect shown by the ANOVA. # indicates a significant (*p* < 0.05) difference from the baseline value.

Table 1 shows normalized changes in muscle damage markers relating to muscle function (MVC-KE, MVC-KF, CMJ) and all performance measures from the baseline at 1 h and 1–5 d (D1–D5) after the 1st LIST for the single, three and six LIST conditions, and summary of the statistical analysis results. It should be noted that the 2nd and 3rd LISTs were performed in the three LIST condition on D2 and D3, and the 2nd to 5th LISTs were performed on D2–D5 for the six LIST condition. A significant condition x time interaction effect was found for all variables, and performing additional LISTs made all variables worse. No indication of recovery was found for the six LIST condition in the time frame. It should be noted that the magnitude of decrease in performance varied among the variables, and relatively larger changes were observed for MVC-KE and MVC-KF torque and YYIR1.

*Int. J. Environ. Res. Public Health* **2021**, *18*, 4134

**Table 1.** Comparison among the single, three, and six Loughborough Intermittent Shuttle Test (LIST) conditions for changes (mean ± SD) in maximal voluntary isometric contraction torque of the knee extensors (MVC-KE) and flexors (MVC-KF), countermovement jump height (CMJ), 30-m dash (30-mD), 30-m timed hop (30-mTH), balance, agility *t*-test (*t*-test), 6 × 10-m shuttle run (SR) and Yo-Yo Intermittent Recovery level 1 (YYIR1) from baseline at 1 h (H1) and 1–5 d after the 1st LIST (D1–D5).

condition, #: significantly different from the Three condition.

#### *3.5. Correlations between Changes in Muscle Damage and Performance Markers*

Significant (*p* < 0.001) correlations were evident between the magnitude of decrease in MVC-KE torque at 1 d after a single LIST, three LISTs and six LISTs; CMJ height at 1 d after a single LIST, three LISTs and six LISTs (r = 0.907); peak muscle soreness of KE (r = −0.606) and KF (r = −0.762) as well as peak CK activity (r = −0.875). Significant (*p* < 0.001) correlations were also evident between MVC-KF torque and CMJ height (r = 0.880), peak muscle soreness of KE (r = −0.653) and KF (r = −0.873) and peak CK activity (r = −0.849). Peak CK activity was also correlated (*p* < 0.001) with peak soreness of KE (r = 0.708) and KF (r = 0.838).

The magnitude of changes in the measures at 1 d after the last LIST (average of single LIST, three LIST and six LIST conditions) varied (*p* < 0.005) among MVC-KE (−19 ± 7%), MVC-KF (−22 ± 7%), CMJ (−10 ± 5%), balance (16 ± 8%), 30-m dash (6 ± 3%), 30-m timed hop (12 ± 6%), agility *t*-test (7 ± 4%), 6 × 10-m shuttle run (5 ± 2%) and YYIR1 (−18 ± 8%). As shown in Figure 4, the normalized changes in MVC-KE torque at 1 d after a single LIST, three LISTs and six LISTs (*n* = 36) were correlated (*p* < 0.001) with the changes in 30-m dash (r = −0.762), 30-m timed hop (r = −0.793), balance (r = −0.793), agility *t*-test (r = −0.821), 6 × 10-m shuttle run (r = −0.822), and YYIR1 (r = 0.806) at 1 d after a single LIST, three LISTs and six LISTs. This was also the case for the normalized changes in MVC-KF and 30-m dash (r = −0.854), 30-m timed hop (r = −0.795), balance (r = −0.799), agility *t*-test (r = −0.831), 6 × 10-m shuttle run (r = −0.882) and YYIR1 (r = 0.891). The normalized changes in CMJ at 1 d after a single LIST, three LISTs and six LISTs (*n* = 36) were also correlated (*p* < 0.001) with the changes in 30-m dash (r = −0.770), 30-m timed hop (r = −0.803), balance (r = −0.836), agility *t*-test (r = −0.851), 6 × 10-m shuttle run (r = −0.889), and YYIR1 (r = 0.886) at 1 d after a single LIST, three LISTs and six LISTs (Figure 5).

#### **4. Discussion**

The results of the present study revealed that the distance covered in the 2nd–6th LISTs was shorter than that in the single or 1st LIST (Figure 2), and the multiple LISTs induced greater changes in muscle damage and performance markers than the single LIST (Figures 3 and 4, Table 1). Additionally, the magnitude of the changes in muscle damage markers significantly correlated with the magnitude of the changes in performance parameters (Figure 5). These results support the hypothesis and suggest that playing multiple soccer matches on consecutive days accumulates fatigue and muscle damage, impairing the performance of well-trained female soccer players.

The level of the female players used in the present study was considered to be high, since their physiological characteristics (e.g., VO2max: 54.1 ± 4.4 mL/kg/min, MVC-KE torque: 158 ± 18 Nm, CMJ height: 38.6 ± 2.7 cm, YYIR1: 1460 ± 244 m) were similar to those of North European elite female players reported in the previous studies [1,45]. Previous studies also used the LIST to simulate a 90-min soccer match-play and reported that the total distance covered in the 90-min LIST was similar to that of official 90-min soccer matches by male (10,000–12,000 m) [15,46] or female players at the local Premier Division standard or higher, with three National representatives in New Zealand (10,800 m) [47]. In the present study, the total distance covered in the 1st LIST from the three conditions was 9240–11,620 m (average: 10,844 ± 528 m), which was also similar to the level of elite female players.

**Figure 5.** Correlations between the magnitude of normalized changes (% pre) in maximal voluntary isometric contraction torque of knee extensors (MVC-KE) or countermovement jump (CMJ) at 1 d after one Loughborough Intermittent Shuttle Test (LIST) and the normalized changes in 30-m dash (MVC-KE: (**a**), CMJ: (**g**)), 30-m timed hop test (MVC-KE: (**b**), CMJ: (**h**)), balance with eyes closed under unstable surface (MVC-KE: (**c**), CMJ: (**i**)), agility *t*-test (MVC-KE: (**d**), CMJ: (**j**)), 6 × 10-m shuttle run (MVC-KE: (**e**), CMJ: (**k**)) and Yo-Yo Intermittent Recovery Test level 1 (MVC-KE: (**f**), CMJ: (**l**)) at 1 d after LIST with one, three, and six LIST groups combined (*n* = 36). For each figure, r value based on Pearson correlation coefficient and its significance, and a regression line are included.

As shown in Figure 2a, the distance covered in a LIST was 5–10% shorter in the 2nd and 3rd, or 2nd–6th LISTs than in the 1st LIST. This was in line with the findings of a previous study [9] reporting that the covered distance during the 3rd (8331 ± 370 m, −8.5%) and 4th matches (8227 ± 339 m, −9.6%) of junior male players was significantly shorter than that in the 1st match (9102 ± 620 m) in a 4-d (one match per day) soccer tournament. These results suggest that players do not fully recover from a previous match and their performance is reduced when the subsequent match is held on the next day. It should be noted that not only the LIST but also many other performance measures were performed every day in the three and six LIST conditions. Thus, these measures might have affected the LIST performance and recovery, although all participants were familiar with the tests. It has been reported that plasma CK and lactate dehydrogenase activities increase after a YYIR1 [48,49]; however, no previous studies have examined the effects of the other tests on muscle damage and performance measures. The effects of the multiple performance measures on LIST performance should be investigated in a future study.

Significant changes in muscle damage and performance markers were observed after the single LIST, and none of the measures returned to the baseline levels until 4–5 d post-LIST (Figures 3 and 4, Table 1). Previous studies also showed that 3–7 d were required for muscle damage and performance measures to return to the baseline values after an official match [4,50–52], a friendly match [1] or a simulated match [3] performed by well-trained players. Silva et al. [5] showed in their review paper that hamstring force production capacity (ES = −0.7), physical performance such as CMJ (ES = −0.4 to −0.6), *t*-test (ES = −0.4 to 0.5), and linear sprint time (ES = 0.4 to 0.6), CK activity in the blood (ES = 0.4), well-being (fatigue: ES = 0.3–0.9; sleep: ES = 0.2–0.3; stress: ES = 0.2–0.3) and muscle soreness (ES = 0.6–1.3) remained substantially impaired at 3 d after an official soccer match. When compared to simulation protocols, a match format (11 versus 11 players) induced greater increases in CK activity in the blood (ES = 1.8 versus 0.7), IL−6 (ES = 2.6 versus 1.1), monocytes (ES = 1.71 versus 0.95) and neutrophil counts (ES = 2.06 versus 1.04) and muscle soreness (ES = 1.5 versus 0.7). The authors concluded that a period of 3 d post-match-play would not be long enough to completely restore homeostatic balance, and the recovery period post-soccer match was not a "one size fits all" situation [5]. To the best of our knowledge, only one study investigated female players. Hughes et al. [4] found that muscle soreness and increased plasma CK activity lasted for 7 d after an official soccer match of elite female youth players. Regarding male players, Thomas et al. [3] reported that decreased MVC-KE torque and CMJ height, and increased muscle soreness and plasma CK activity were still evident at 3 d after a 90-min LIST performed by 15 semi-professional soccer players. They also reported 2% reduction in voluntary activation, and 5% decrease in quadriceps potentiated twitch force at 2 d post-LIST. In the present study, the time course of changes in muscle damage and performance parameters varied, but most of the parameters did not return to the baseline values at 4 d after a single LIST (Figures 3 and 4, Table 1). It seems reasonable to assume that the responses of the female players to the single LIST shown in the present study were comparable to those of an official soccer match. It is possible that the time course of recovery is influenced by the severity of a match; characteristics of the players such as age, fitness level, gender, and experience; and other factors such as environmental temperature and humidity [2,6]. However, it seems unlikely that even elite female players can fully recover within 3 d after an official match.

Silva et al. [5] stated that match congestion in elite soccer induces residual fatigue and underperformance due to insufficient recovery time. Using time–motion analyses, a couple of studies reported that running performance represented by distances covered was unaffected by match congestion [6,13]. Carling et al. [13] recommended analyses of movement variables including accelerations, decelerations and turns that were more metabolically taxing. Thus, the total distance covered may not be the best indicator of performance. To the best of our knowledge, the present study was the first to examine the effects of three and six LISTs played on consecutive days on muscle damage and performance parameters, and show that multiple matches performed every day negatively

affect performance in the LIST, increase muscle damage, and impair performance test results of female soccer players. The changes in muscle damage and performance markers after three LISTs and six LISTs were greater than those after a single LIST (Table 1), and most of the measures did not return to the baseline values even at 5 d after the last LIST (Figures 3 and 4). When the multiple LISTs were performed, it appeared that muscle damage was accumulated and performance got worse (Table 1). As shown in Figure 4, the extent of decreases in performance measures following the last LIST of three LISTs was significantly greater than that after a single LIST, and that following six LISTs was significantly greater than that after three LISTs. It seems that the more multiple soccer matches are performed, the greater the magnitude of muscle damage. However, it should be noted that the magnitude of muscle damage after six LISTs was not six times greater than that after a single LIST. For example, the magnitude of maximal decrease in MVC-KE torque at 1 d after a single LIST, three LISTs and six LISTs was 13%, 20% and 25%, respectively, and the magnitude of decrease in YYIR1 at 1 d after a single LIST, three LISTs and six LISTs was 11%, 19%, and 26%, respectively. It is important to note that the recovery rate of the variables after the last LIST was not largely different among the single LIST, three LISTs and six LISTs. This suggests that the magnitude of muscle damage was attenuated over multiple LISTs due to the repeated bout effect, and the recovery ability was not impaired by multiple LISTs for the well-trained players.

Although it is rare or unlikely that professional soccer players are involved in several official matches in a row, it is possible that players have three [8] or four matches [7,9,10] in a row, in school soccer competitions. The players in the present study had experienced three official matches over three days, and some had played five matches over five days. Although playing six matches in six days is rare in an official soccer tournament, Moreira et al. [11] reported that a congested match schedule such as seven matches played in seven days decreased testosterone concentration in elite Brazilian youth male players and negatively affected their mucosal immunity and impaired the capacity to perform certain technical actions such as tackles, interceptions, and passes. Since the present study used elite female university soccer players, it is not known how higher levels of players, including male professional players, would respond to multiple matches in fixture congestion periods. However, it seems likely that if teams are required to play matches on consecutive days, the time for recovery of players between matches is limited, their physical performance in a subsequent match could be impaired, and fatigue and injury risks would increase [8,11].

In the present study, 1 h after three LISTs, the 30-m dash (−5%), 30-m timed hop (−11%), balance (−16%), agility *t*-test (−5%), 6 × 10-m shuttle run (−4%), and YYIR1 (−19%) all decreased. The magnitude of the decrease in some of the variables appeared to be greater in the present study when compared with that of the previous study [12]. It should be noted that YYIR1 showed the largest decrease (average: −35%) among the performance parameters in the study of Saidi et al. [12]. As shown in Figure 2, the total distance covered in the 2nd to 3rd LISTs in the three LIST condition was 5–9% shorter when compared with the 1st LIST of the three LIST condition, but this was much smaller than the decrease in YYIR1 (Figure 4, Table 1). It should be noted that YYIR1 consists of repeated accelerations, decelerations and changes of direction, which require eccentric contractions. In the present study, no eccentric contraction strength measures were included. It may be that decreases in eccentric contraction strength affected YY1R1 greater than the LIST. This would suggest that the YYIR1 test may be a sensitive marker of soccer performance.

As shown in Figure 5, significant correlations were found between the normalized changes in MVC-KE torque and all performance measures, and this was also the case for the normalized changes in MVC-KF torque. Thus, it seems likely that the decreases in the performance measures were associated with the decreases in KE and KF muscle strength. It is important to note that the normalized changes in CMJ height also significantly correlated with the changes in all performance measures, and the r values were not largely different from those of MVC-KE torque (Figure 5). This may suggest that CMJ height can be used to assess muscle damage and its effects on physical performance in a field, when MVC torque measures are not possible.

The mechanisms underpinning the greater extent of muscle damage and impaired performance measures following multiple LISTs were not investigated in the present study. As discussed above, a single soccer match leads to acute fatigue and muscle damage characterized by a prolonged decline in maximal muscle strength and muscle soreness, which could require at least three days to fully recover (Figure 3, Table 1). Thus, if the next soccer match is performed within three days, it seems likely that players have less fitness when compared with the first match [7,9,10], thus the second match requires more effort than the first match because of the reduced muscle function. This could lead to additional fatigue and muscle damage, thus impairing the performance of the players further [6]. It seems possible that repeatedly performing eccentric actions such as changes in direction, stopping, and decelerations with weaker muscles induces more mechanical stimuli especially to lower limb muscles during a subsequent soccer match [53,54]. It is also possible that recovery of muscle glycogen, dehydration, and mental fatigue would be incomplete, if the recovery time is not long enough [2,6]. This may also exacerbate muscle damage and retard recovery. Thus, strategies for minimizing cumulative fatigue and improving recovery from muscle damage are necessary. Since eccentric muscle actions of leg muscles are performed frequently in a soccer match-play [2,55], and muscle damage is induced by unaccustomed eccentric contractions [53,56], it seems possible that regular eccentric resistance training will attenuate muscle damage [57]. Performing eccentric resistance exercise training may reduce muscle damage and attenuate performance decrement in multiple matches over days in a soccer tournament. However, this hypothesis is need to be explored further.

There are several limitations in the present study. Firstly, the participants of the study were female university soccer players, thus the results of the study may not reflect male, youth and professional players. Secondly, the changes in ovarian hormone status of these female players during the study were not recorded, and the possible effects of the hormones on the outcome measures were not controlled. Thirdly, the LIST does not include kicking a ball, tackles, maximal jumps, changes of directions, and direct contacts with opposing players, and the LIST was performed on the wooden floor of an indoor sport hall in the present study. Thus, this may be different from actual matches played on a grass pitch. Fourthly, previous studies showed that aerobic performance measurements such as YYIR1 affected the recovery of other tests such as short-sprint tests (e.g., 30-m dash) after a soccer match [2,58]. In the present study, no measurements were taken immediately after the LIST and between one and 24 h after the LIST, but many measurements (e.g., 6 × 10-m shuttle running, YYIR1) were taken daily together with the LIST, which may have affected the recovery from the LIST. In the present study, a control group with players experiencing muscle damage and performance measures without performing any LIST was not included. Thus, the effects of measurements on the variables are not known. Fifthly, all participants performed single, three and six LISTs at least 12-week intervals using a semi-counterbalance fashion, but this could potentially result in the repeated bout effect [56]. Although the order of the three conditions was pseudo-randomized among the participants and the time between the conditions was more than 12 weeks, it may be that the players who had the six LIST condition first (*n* = 4) might have had more difficulty than those who had a single LIST (*n* = 4) or three LIST condition (*n* = 4) first. Sixthly, the present study did not assess the effects of muscle damage on skill performance, which is assumed to be affected and influence a game performance. Furthermore, previous studies [59,60] reported that a hot and humid environment impaired the performance of soccer players. In the present study, the LIST was performed in an indoor facility without air-conditioning with the environmental temperature being 30–34 ◦C and relative humidity being 77–85%. However, it should be noted that the participants of the present study were used to the environment, since they trained and played matches in similar conditions year round in Taiwan. Lastly, the present study was rather descriptive, and a mechanistic approach to investigate the factors affecting muscle damage and performance was absent. Future studies are warranted to consider these limitations and examine inflammatory responses (e.g., cytokines), changes in central (e.g., transcranial magnetic stimulation) and peripheral (e.g., surface electromyography) neuromuscular parameters, and glycogen and other substances in muscles.

#### **5. Conclusions**

In conclusion, multiple LISTs resulted in greater muscle damage and impaired performance than a single LIST, and the extent of muscle damage was associated with the extent of decline in performance measures. The findings of the present study suggest that playing multiple soccer matches can impair the performance of elite female players; thus strategies to minimize muscle damage and enhance recovery are important for the players to perform better in a tournament.

**Author Contributions:** The study was designed by T.-Y.C. and T.C.C., and discussed with K.N. T.-Y.C. and T.C.C. performed data collection and analyses. All of the authors (T.-Y.C., K.N., T.C.C.) discussed and interpreted the data, contributed to drafting and revising the manuscript, and approved the final version of the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was financially supported by the Ministry of Science and Technology (MOST 108−2635-H−003−001) and the Higher Education Sprout Project by the Ministry of Education (MOE) in TAIWAN.

**Institutional Review Board Statement:** The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of the Research Ethics Committee of National Taiwan Normal University (Approval #: 2018HM023 on 9 April 2019).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The data of the current study are available from the corresponding author on reasonable request.

**Acknowledgments:** The authors thank Chung-Chan Hsieh, Kai-Jou Liang and Jin-Lian Yang for their assistance in the data collection. We would like to thank the players for their cooperation and effort throughout the study.

**Conflicts of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

#### **References**

### *Article* **Match Day-1 Reactive Strength Index and In-Game Peak Speed in Collegiate Division I Basketball**

**Adam J. Petway 1,2,\*, Tomás T. Freitas 2,3,4, Julio Calleja-González 5,6 and Pedro E. Alcaraz 2,4**

**Abstract:** Basketball is a game of repeated jumps and sprints. The objective of this study was to examine whether repeated jump assessments the day prior to competition (MD-1) could discriminate between fast and slow in-game performances the following day. Seven NCAA Division I Basketball athletes (4 guards and 3 forwards; 20 ± 1.2 years, 1.95 ± 0.09 m, and 94 ± 15 kg) performed a repeatedhop test on a force platform before and after each practice MD-1 to assess Reactive Strength Index (RSI) and Jump Height (JH). Peak speed was recorded during games via spatial tracking cameras. A median split analysis classified performance into FAST and SLOW relative to individual in-game peak speed. Paired *T*-tests were performed to assess post- to pre-practices differences. An independent sample *T*-test was used to assess the differences between FAST and SLOW performances. Cohen's d effect sizes (ES) were calculated to determine the magnitude of the differences. Statistical significance was set for *p* ≤ 0.05. Post-practice RSI and JH were significantly higher than pre-training values prior to the FAST but not the SLOW in-game performances. A significant difference was found for MD-1 RSI when comparing FAST and SLOW conditions (*p* = 0.01; ES = 0.62). No significant between-group differences were obtained in JH (*p* = 0.07; ES = 0.45). These findings could have implications on the facilitation of reactive strength qualities in conjunction with match-play. Practitioners should evaluate the placement of stimuli to potentiate athlete readiness for competition.

**Keywords:** neuromuscular; repeated jump; max speed

#### **1. Introduction**

Basketball is a court-based team sport that requires contributions from various physical parameters and bio-motor abilities [1]. These broad arrays of skills are principal components of in-game performance [2]. Particularly, basketball requires large expressions of speed and power qualities for match-play success. The technical and tactical aspects of the game put a high demand on the neuromuscular system relative to the sporting activity [3]. Therefore, the process of monitoring changes in these qualities for each individual player becomes paramount during the season (in view of the various stressors encountered by the players) [4–6], as it allows for evaluating longitudinal fluctuations over time [7] and provides insight on speed- and power-related performances.

Within basketball, standardized and repeatable jumping assessments are amongst the most popular to assess neuromuscular function [8–12]. The ability to produce substantial amounts of force onto the ground to vertically displace the center of mass is an important skill contextually within the game, since basketball athletes execute around 45 jumps per game [3]. Thus, it is logical that practitioners collect and analyze jump data throughout

**Citation:** Petway, A.J.; Freitas, T.T.; Calleja-González, J.; Alcaraz, P.E. Match Day-1 Reactive Strength Index and In-Game Peak Speed in Collegiate Division I Basketball. *Int. J. Environ. Res. Public Health* **2021**, *18*, 3259. https://doi.org/10.3390/ ijerph18063259

Academic Editors: Filipe Manuel Batista Clemente and Hugo Sarmento

Received: 20 February 2021 Accepted: 19 March 2021 Published: 22 March 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

the competitive season [13] to allow for a more in-depth neuromuscular function assessment [14–16]. This is particularly important since jump height (JH) alone does not always indicate athlete readiness as individuals may change movement strategies to achieve similar outputs [17]. In this context, the assessment of variables other than height in various jump tasks could be a suitable approach to monitor fatigue and readiness in the in-season period [18].

Previous research has examined jumping ability in basketball, with most studies utilizing the countermovement jump (CMJ) to assess neuromuscular function [18–22]. However, basketball mainly requires rapid stretch-shortening cycle (SSC) actions as well as the activation of H-reflex responses [23] that are not always reflected within the CMJ. To overcome this issue, repeated jumping and hopping tasks can be used, as they permit evaluating the ability to produce high vertical ground reaction forces in short ground contact times. In fact, the reactive strength index (RSI) (i.e., ratio of JH/contact time) has been previously used to measure both performance and fatigue within athletes [8,22].

Along with jumping, running speed is also an important characteristic in basketball [24]. Although the sport is played in a 28 by 15-m court, the ability to reach high top speeds and rates of acceleration can be extremely advantageous within the context of the game [1]. Whether it is via jumping- or running-based actions, athletes that can produce large amounts of force is a short amount of time are more likely to be in optimal positions on the court to garner competitive advantages (e.g., grab a rebound or intercept a pass) [25]. Conversely, if an athlete is producing less force and having longer ground contact times relative to their normative datapoint, this may be a potential sign of fatigue [26,27]. It is for this reason that examining the effects that fluctuations in reactive strength qualities have on the mechanical demands of in-game performance can provide informative decision-making on readiness to compete and recovery needs.

To the best of the authors' knowledge, no previous research has investigated whether a repeated-hop test performed the day before basketball competition can provide meaningful information regarding match-play mechanical demands. Therefore, the main purpose of this study was to investigate if fluctuations in reactive strength qualities could be used as an indicator to discriminate between faster and slower physical in-game performance the following day. This research may help coaches and sports scientists to make more informed decisions on both training and recovery.

#### **2. Materials and Methods**

A prospective comparative study was conducted. Neuromuscular performance was assessed on the training day before competition (i.e., Match-day-1 [MD-1]) via a repeatedhop test. Match-play data was recorded during all 17 matches at the team's home arena. All data was collected between the months of November 2017 and February 2018 by the strength and conditioning staff as routine for the daily assessment of fatigue and player loads.

To evaluate neuromuscular performance (i.e., RSI and JH) on MD-1 for all 17 games, a repeated-hop test [28] was performed. The test was performed both pre-practice and post-practice to account for any of the acute effects imposed by the training session the day before the competition. A standardized warm-up of squats, lunges, and free arm swing CMJ preceded the assessment. Three repeated-hops were performed on a triaxial force platform (9260 AA-Kistler, Kistler Group, Winterhur, Switzerland) with the athletes' hands on their hips. Players were instructed to jump as high and as fast as possible while spending minimal time on the plate without resetting between jumps. All tests were completed 15-min prior to, and after practice. The tests were disregarded if the athlete did not complete the standardized warm-up or did not fall within the 15-min windows. Likewise, data was not considered if the player did not test both pre- and post-practice. All jumps were recorded via a data acquisition system (DAQ System Type 5691 A- Kistler, Kistler Group, Winterhur, Switzerland). Each trial was exported to a TXT file and analyzed with the ForceDecks Software (Vald Performance, Brisbane, Australia) [29]. For each athlete,

the difference between post- and pre-practice values were calculated (i.e., delta [Δ]). A positive or a negative integer would indicate an increase or decrease in neuromuscular performance, respectively. The mean of the 3 jumps RSI (calculated by dividing JH/contact time) in m·s−1, and JH, in cm, were considered for analysis.

Match-play activity profiles were tracked for each of the 17 home games throughout the 2017–2018 season via spatial tracking cameras (Sport VU®, Stats Perform, Chicago, IL, USA). This six-camera system was set up in the home gymnasium during competitions to track distance and speed of each athlete. The activity profile data was collected via Stats Sports VU software and exported to a customized spreadsheet (Microsoft Excel 2016, Microsoft Corporation, Redmond, WA, USA). The primary performance metric examined was peak speed (km·h−1), given that it is an intensity-related variable that can provide a good gauge of neuromuscular readiness. A median split relative to individual's peak speed was used to determine fast versus slow in-game performances. All 7 players competed in every home match.

Data is presented as means and standard deviation. Data normality was tested using the Shapiro-Wilk test (*n* < 30). For every player, in-game performances (*n* = 17) were divided using a median split analysis into two groups (i.e., FAST: above the individual's median value, and SLOW: below the player's median) according to the peak speed achieved by each athlete during competition. Paired *T*-tests were performed to assess post- to prepractices differences. An independent Sample *T*-test was used to assess the differences between FAST and SLOW performances. Cohen's d effect sizes (ES) [30] were calculated to determine the magnitude of the differences and classified as: trivial (<0.2), small (>0.2–0.6), moderate (>0.6–1.2), large (>1.2–2.0), and very large (>2.0–4.0). Statistical significance was set for *p* ≤ 0.05.

#### **3. Results**

Table 1 shows the descriptive data and the comparison between FAST and SLOW performances. Post-practice RSI and JH were significantly higher than pre-training values prior to the FAST but not the SLOW in-game performances. Moreover, when considering the ergogenic response from before to after training (i.e., Δ), a significant difference was found for MD-1 RSI when comparing FAST and SLOW conditions (*p* = 0.01; ES = 0.62). No significant between-group differences were obtained in JH (*p* = 0.07; ES = 0.45).

**Table 1.** Repeated-hop descriptive data from Match-Day -1 and comparison between FAST and SLOW in-game performances.

\*\* Significant increase with respect to pre-practice (*p* ≤ 0.01). **Δ**: delta, change from pre- to postpractice; CI: confidence interval; ES: effect size; RSI: reactive strength index.

#### **4. Discussion**

The aim of the present study was to examine MD-1 pre- to post-practice differences (i.e., Δ) in repeated jump outputs and determine whether potentiation or degradation of neuromuscular performance in training could discriminate between faster and slower in-game physical performance. The main findings indicated that large gains in RSI (from before to after training) were observed the day prior to competitions in which higher peak speed values were reached during match-play. These preliminary results are novel and suggest that testing athletes' repeated jump ability both prior to and after practice MD-1 (to account for any potential acute onset of fatigue or potentiation) can provide meaningful information regarding neuromuscular readiness to compete. This study is also unique in that it evaluated elite level basketball players throughout the entire competitive season.

Of note, vertical jump has been previously found to be highly related to running speed [24] and a predictor of repeated-sprint ability in elite basketball players [25]. However, the present study is the first to identify what seemed to be a positive influence of gains in RSI MD-1 in peak speed of subsequent basketball competition. This finding could be extremely useful to practitioners considering that neuromuscular performance usually fluctuates during a typical in-season week [26]. Knowing that speed is a primary component in basketball [1,3], coaches can, therefore, optimize training strategies with the aim of maximizing reactive strength qualities prior to competition. This may, in turn, translate into superior neuromuscular status of the athletes that can place them at an optimal position for in-game success.

Remarkably, Δ JH MD-1 was not able to discriminate between FAST and SLOW in-game performances. Gathercole et al. [11] reported that neuromuscular function alternations 24 h after a fatiguing protocol were not detected when using JH alone (i.e., in both CMJ and drop jump tasks) and suggested that complementary variables such as Flight Time:Contact Time ratio should be assessed. Likewise, it appears that in the repeated-hop test herein, Δ RSI was more sensible than JH to determine neuromuscular readiness the following day. Based on the previous, it appears that an athlete's ability to express highforce outputs in reduced contact times may better discriminate between FAST and SLOW games when compared to how high he can jump in a repeated-hop task. From a practical perspective, coaches are recommended to utilize the RSI metric obtained from a high rate of frequency test to assess their players on MD-1.

The limitations of the present study should be addressed. Firstly, the small sample size limits the generalization of the current findings to other athletic populations. Nevertheless, since 17 games were analyzed here, the preliminary results obtained open a new perspective and should be investigated more in-depth. Secondly, it is important to keep in mind that peak speed is only one of many in-game physical parameters (e.g., accelerations, decelerations, or jumps); hence, further research should consider a more complete set of metrics to provide a clearer picture regarding match-play performance. Finally, variables other than RSI alone may influence subsequent in-game physical performance (e.g., MD-1 training load, recovery protocols, priming strategies). Thus, the reader should interpret the present results cautiously.

In summary, MD-1 sessions that resulted in greater post-practice increases in RSI were observed prior to faster in-game performances when examining peak speed in elite collegiate basketball players. However, larger JH gains were not able to discriminate between faster and slower performances. These finding could impact stimuli provided to athletes prior to competition. Exposures to menu items that promote maximal high force outputs applied in reduced contact times may be most appropriate close to competition.

#### **5. Conclusions**

Athletes with greater gains (i.e., Δ) in RSI from pre- to post-practice were found to achieve greater peak speeds in match-play the following day. Conversely, no differences were found between FAST or SLOW performances when JH was the variable analyzed. It is for this reason that professionals should closely examine acute adaptations to MD-1 as it may influence player selection or training strategies that place their athletes in the best position to succeed on the court. Having a critical thought process in regard to the sequencing of menu items is vital in the appreciation of the heterochronicity and different time courses of adaptive processes for varying stimuli. Specifically, actions that foster reactive strength and short ground contacts should be placed as close to the competition as possible within a training week. Further research on these topics is needed to gain a more

robust insight into how to best create an environment for optimal neuromuscular outputs around match-play. The proper application of stimulus relative to match-play could have a direct impact on the optimization of neuromuscular status for in-game performance.

**Author Contributions:** For this present study A.J.P. was responsible for data collection and writing. T.T.F. was responsible for data curation, formal analysis, and editing. J.C.-G. and P.E.A. were responsible for methodologies, editing, and supervision. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** The University Institutional Review Board (IRB #17-04-632) approved this study in accordance with the Helsinki Declaration and researchers were provided de-identified data to analyze. As student-athletes for the university's basketball program, each player provided individual consent for study participation as part of their team requirements.

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The data presented in this study are available within the article.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

### *Article* **Data Mining to Select Relevant Variables Influencing External and Internal Workload of Elite Blind 5-a-Side Soccer**

**José M. Gamonales 1,\*, Kiko León 1, Daniel Rojas-Valverde 1,2,\*, Braulio Sánchez-Ureña 3 and Jesús Muñoz-Jiménez 1,\***

**Abstract:** (1) Background: Data mining has turned essential when exploring a large amount of information in performance analysis in sports. This study aimed to select the most relevant variables influencing the external and internal load in top-elite 5-a-side soccer (Sa5) using a data mining model considering some contextual indicators as match result, body mass index (BMI), scoring rate and age. (2) Methods: A total of 50 top-elite visually impaired soccer players (age 30.86 ± 11.2 years, weight 77.64 ± 9.78 kg, height 178.48 ± 7.9 cm) were monitored using magnetic, angular and rate gyroscope (MARG) sensors during an international Sa5 congested fixture tournament.; (3) Results: Fifteen external and internal load variables were extracted from a total of 49 time-related and peak variables derived from the MARG sensors using a principal component analysis as the most used data mining technique. The principal component analysis (PCA) model explained 80% of total variance using seven principal components. In contrast, the first principal component of the match was defined by jumps, take off by 24.8% of the total variance. Blind players usually performed a higher number of accelerations per min when losing a match. Scoring players execute higher DistanceExplosive and Distance21–24 km/h. And the younger players presented higher HRAVG and AccMax. (4) Conclusions: The influence of some contextual variables on external and internal load during top elite Sa5 official matches should be addressed by coaches, athletes, and medical staff. The PCA seems to be a useful statistical technique to select those relevant variables representing the team's external and internal load. Besides, as a data reduction method, PCA allows administrating individualized training loads considering those relevant variables defining team load behavior.

**Keywords:** soccer; performance analysis; heart rate; technology; inertial measurement units

#### **1. Introduction**

Soccer 5-a-side (Sa5) is an adapted Paralympic sport for people with blindness [1]. The game has different modifications compared to soccer for persons without a disability. The game is played in a 40 × 20 m field with barriers on the sides and a ball that sounds when moving [2]. To be orienteered, players receive auditory references during the game by three sighted components; their coach, their goalkeeper, and the "caller", who stands behind the opponent's goal [3].

The Sa5 game requires some crucial adaptations of the sport technic and tactic because it is played in a total absence of visual references, which differentiates it from other soccer modalities. These unique characteristics are presented in scientific literature, with diverse approaches [4], highlighting performance analysis in sports, focusing on the main technical aspects [5,6], and defining performance indicators that explain the success in this sporting context [7–11].

**Citation:** Gamonales, J.M.; León, K.; Rojas-Valverde, D.; Sánchez-Ureña, B.; Muñoz-Jiménez, J. Data Mining to Select Relevant Variables Influencing External and Internal Workload of Elite Blind 5-a-Side Soccer. *Int. J. Environ. Res. Public Health* **2021**, *18*, 3155. https://doi.org/10.3390/ ijerph18063155

Academic Editor: Paul Tchounwou

Received: 11 February 2021 Accepted: 16 March 2021 Published: 18 March 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

In recent years, research on performance analysis in sports for people with disabilities has used new technological devices to quantify athletes' external load. This load is usually linked with other internal load indicators (e.g., heart rate) to have a global perspective of the physical and physiological game demands [12–14]. The use of the so-called electronic performance and tracking systems (EPTS) has increased due to its portability and availability of many variables. These devices integrate multiple sensors (e.g., accelerometers, gyroscopes, magnetometers, global position systems and tracking technology) [15], allowing to record data related to the workload profile. These variables bring information about the magnitude and frequency of accelerometric-based (e.g., impacts, jumps, steps, landings, changes of direction) and speed-based indicators (e.g., distance, mean speed). Due to the sensor's capacity, up to 250 variables are registered at a sampling frequency of 100 to 1000 Hz. This is why this information is defined as big data [16,17]. To identify, cluster, and select the most relevant variables in a specific team and task, it is necessary to implement a data mining technique [18]. The reduction in the data sets size allows to objectively identify the variables to assess the interaction between the external and internal load with other contextual factors that may influence performance.

One of these data mining methods is known as Principal Component Analysis (PCA). This is the most used technique to reduce data into a small series of variables (5–15 variables), explaining up to 70% of the data set variance. Although some studies have applied this statistical method to select and cluster anthropometric, biomechanical, physical, and physiological variables of team top elite sports, this procedure has never been used in the performance analysis of adapted sports for people with disabilities [19].

Considering that some contextual and situational factors may influence game's physical and physiological performance, as other studies have revealed, it is hypothesized that due to the particular characteristics of the Sa5 game, the magnitude of some external and internal load variables could be influenced by contextual variables as match result, age, goal scorer and anthropometric variables. We hypothesized that both internal and external load variables may be affected by match result, age, goal scorer and some anthropometric variables, based on previous results of similar studies. Consequently, this study aimed to explore the potential differences in the Sa5 internal and external load variables selected by PCA considering three variables: a. match result, b. body mass index (BMI), c. scoring rate and d. age.

#### **2. Materials and Methods**

#### *2.1. Study Design*

A cross-sectional and observational protocol approached the problem of the study. The external and internal load variables were assessed during a Sa5 International Tournament. This congested tournament was held on a single weekend, and the teams were representatives of European national teams. A total of four matches were played per each team under similar circumstances and in the same venue. The Sa5 International Tournament was held in the city of Seville (Spain) in May 2019 (temperature = 21.2 ± 3.7 ◦C, relative humidity = 65.2 ± 5.3%), in which the teams of Spain, Italy, the Czech Republic, and an Andalusian team participated.

#### *2.2. Participants*

Data were collected from 50 blinded male players (age 30.86 ± 11.2 years, weight 77.64 ± 9.78 kg, height 178.48 ± 7.9 cm). The players were members of top elite national European teams. There were no reports of neuromuscular injuries that could compromise physical or physiological performance. The players who participated >85% of the matches' effective time were included in the analysis.

Before data collection, all participants signed an informed consent document, which contained all the investigation details. The protocol followed the Helsinki Declaration guidelines for biomedical research. The study was reviewed and approved by the Institutional Review Board (University of Extremadura, Reg. Code 67/2017). Besides, the teams' staff and tournament managers gave their consent for participation in this research.

#### *2.3. Instruments and Procedures*

Before the matches, each player was equipped with a heart rate monitor (GARMINTM, Lenexa, KS, USA) to record internal load variables. Magnetic, angular rate, and gravity (MARG) sensors (WIMUTM, RealTrack Systems, Almería, Spain) were fixed using an adapted anatomically harness at the height of T2–T4 vertebrae between scapulae. The devices were calibrated considering previously published guidelines [20]. The MARG sensors integrate data of four three-axis microelectromechanical system accelerometers, gyroscope, and magnetometer to assess external load-related variables. After registration, the data was processed using special software (SPROTM, RealTrack Systems, Almería, Spain) immediately after each match. Moreover, the MARG sensor incorporate GPS and UWB systems to register all speed and distance based variables. The sampling was made using a 5 Hz sampling frequency for the GPS system and 100 Hz for accelerometric-based variables [21]. All players were used to wear the MARG sensors during soccer matches.

#### *2.4. Variables*

While the MARG sensors provide up to 200 variables, considering there could be differences in the time played in each match, only peak and time-related variables were initially selected (n = 44). This criterion is used to homogenize the average demands of each match [22–24]. These variables were introduced in a correlation matrix to select the uncorrelated representative variables; those with an r > 0.7 were discarded [25]. Before an Exploratory Factor Analysis called Principal Component Analysis (PCA), this procedure was performed, and previous similar studies' statistical protocol was followed [19,22]. Variables with variance = 0 were excluded from the analysis.

The 15 selected variables after the correlation matrix were scaled and centered (Z-scores). Suitability of PCA was confirmed by Kaiser-Meyer-Olkin (KMO = 0.71), and Barleth's Sphericity test was significant (*p* < 0.01) [26,27]. Eigenvalues >1 were considered for the extraction of principal components (PC) [27]. A VariMax-orthogonal rotation method was performed to identify high correlations of components and guarantee that each principal component offered different information. A threshold of 0.6 in each PC loading was retained for interpretation, extracting the highest factor loading when a cross-loading was found between PCs. PCA procedure followed standard quality criteria, meeting 21 out of 21 of the quality items [19]. Moreover, the report of the PCA model results followed previous guidelines for team sport performance analysis [28].

The contextual variables considered during this tournament were match result (losers vs. winners), BMI (lower vs. higher based on the BMI mean), scoring rate (those scorers at least once during a match vs. non-scorers), and age (younger vs. older players based on the age mean).

#### *2.5. Statistical Analysis*

Data were expressed in mean and standard deviation with respective upper and lower limits for descriptive purposes. Independent *t*-tests were performed to explore differences by match result (loser vs. winner), BMI (lower vs. higher), scoring rate (scorer vs. non-scorer) and age (younger vs. older). The magnitude of *t*-test differences was interpreted using Cohen's d (d) as follows: 0–0.2 trivial; 0.2–0.5 low; 0.5–0.8 moderate and >0.8 high [29]. Statistical differences were considered if *p* < 0.05. Data exploratory analysis was performed using the Statistical Package for the Social Sciences (SPSS, IBM, SPSS Statistics, v.22.0 Chicago, IL, USA).

#### **3. Results**

Table 1 shows absolute descriptive data of the 15 selected variables of the whole match. A total of seven PCs were extracted after performing PCA. The whole model explains 80.5% of the total variance. PC cumulative variance of each PC is shown in Table 1.

**Table 1.** External workload and locomotion variables extracted from principal components analysis in soccer 5-a-side playing.

The results suggested differences by match result in only one external load variable. There were differences by match results in Acc per minute, and the losers make higher accelerations during the matches compared to the winners (see Table 2). This change was qualified as low based on effect size.

**Table 2.** External workload and locomotion variables in soccer 5-a-side playing by match result.

**Table 2.** *Cont.*

\* Significant differences with low effect size.

Additionally, there were no differences in external or internal workload demands considering BMI (see Table 3). No differences were found between those players categorized in low or high BMI. Besides, effect sizes showed trivial changes by group.

There were found differences in distance variables extracted from the PCA model. Those players who scored at least once during the matches showed higher DistanceExplosive and Distance21–24 km/h than non-scorers (see Table 4). These variables showed low changes between groups based on the effect size.

**Table 4.** External workload and locomotion variables in soccer 5-a-side playing by goal scorer.

\* Significant differences with low effect size.

There were found differences by age in HRAVG and AccMax as internal and external load variables, respectively. Younger players performed higher HRAVG and AccMax compared to the older ones. Effects sizes of these changes were classified as low (see Table 5).

**Table 5.** External workload and locomotion variables in soccer 5-a-side playing by age.

**Table 5.** *Cont.*

\* Significant differences with low effect size.

#### **4. Discussion**

The purpose of this study was to explore the potential differences in the Sa5 internal and external load variables selected by PCA considering three variables as match result, body mass index (BMI), scoring rate and player's age. The results suggested that players usually performed a higher number of accelerations per min when losing a match. There were no differences in external workload variables by player's BMI. Those Sa5 players that scored during a match execute higher DistanceExplosive and Distance21–24 km/h. And younger players presented higher HRAVG and AccMax.

In actual soccer-playing, high-intensity actions (e.g., sprints, high-speed running, jumps, etc.) are considered the most relevant external load performance indicators in team sports. Moreover, these variables seem to be crucial during congested fixture conditions, and it is essential to understand how these external and internal load variables could be affected by some contextual factors [22]. Addressing these potential load differences could be fundamental when planning and monitoring both training and official matches.

In this research, 80.5% of the total variance was explained by the PCA model using seven PCs. The 15 variables extracted from the model were heart rate, accelerations, decelerations, high-intensity speed, impacts, jumps, and take-offs. The present PCA results are in line with analyses previously performed in team sports3/17/2021 10:34:00 PM were external and internal load variables derived from MARGS and inertial measurement units in team sports were selected through PCAs [19]. After the variables extraction, the results suggested some impact on external and internal loads by match outcome, scoring rate, and age.

It has been found that match outcome is significantly related to performance in some external and internal load variables in soccer. In this study, it was found that losers teams performed more accelerations per minute than the winners. In this sense, it has been also reported that total distance increases when losing even when distance performed between 0–6 km/h decreased [30]. These results suggest that high-intensity actions as accelerations could increase to improve the final score as the losing team is trying to look after new goal opportunities [30]. Although, there is a lack of agreement in soccer research since the link between the higher external and internal is not clearly understood; considering that other match contextual factors as opponent level, team strategies, or match status could also influence load and it is difficult to isolate the individual effect of these contextual variables [30–32]. The external and internal load demands could also increase and decrease during the match whether the team is winning, drawing, or losing [30].

While in soccer, BMI seems to be a crucial parameter that determines muscle power, fatigue index, and strength [33,34]; in Sa5, BMI does not influence external or internal load demands. BMI is a relevant indicator of performance that allows differentiation between players level and defines in-field actions as speed [35]. In Sa5, the developed

speed during matches is lower than in regular similar soccer modalities [36]; it could be why BMI is not that determinant in the blinded player's load. Speed could not be as critical as the change of direction, acceleration, or other external load variables as stated in recent studies [37,38]. Despite this evidence, more studies should be developed to explore the above more in-depth.

While the practice of any sport predisposes individuals to suffer injuries, particularly in Sa5 soccer, there are up to 80% of injuries of traumatic etiology [39]. Despite there are some rules that protect blinded players from an injury (e.g., the "go" rule), the inherent danger of hitting other players remains latent. As with other anthropometric variables, BMI should be monitored and controlled to enhance performance and prepare the body to resist those impacts.

In this study, those who scored at least once presented higher DistanceExplosive and Distance21–24 km/h. This may suggest the requirement to train the ability to perform highintensity actions in these players. Considering that the actions usually started in the pre-offensive zone of the field had more probabilities of finish in goal in Sa5 [7], the attention should be focus on those players that due to tactical or positional characteristics play in this zone.

This result is also in line with other studies that suggest that most soccer goals are preceded by at least one high-intensity action performed by the assisting or scoring player [40]. Straight sprints, jumps, rotations and change of directions were the most common actions executed prior a goal situation. Moreover, decisive passes are preceded by these kind of high intensity actions enabling the attackers to locate in an optimal position to score [40].

In the present study, younger players presented higher HRAVG and AccMax when compare to the older ones. In this respect, older players are usually present some physiopsychological factors as higher experience, higher self-confidence, better game reading and self-efficacy, allowing to dose their effort throughout the match [41] requiring less physical demands. Conversely, there are contrast evidence if the younger players present better physical performance in professional soccer compare to their older peers [42]. Besides it is clearly known that the rate of maturation impacts the physical performance characteristics of the players. Still, it usually depends on the relative age effect and no in broader age ranges as in professionals [42]. In this sense, national team coaches should consider these differences when identifying and selecting representative players.

#### **5. Limitations**

While the results of this study have provided information regarding how contextual factors as age, scoring abilities and match result could affect external and internal load demands, these research outcomes must be seen in the light of some limitations. One of the limitations in this study concerns the sample studied, the locomotion demands presented in this research must be applied to top-elite blinded soccer players and could serve as a reference to other inferior divisions. Due to the authors did not influence the natural dynamic of the competitions or the tournament schedule, the sample between the compared groups were distributed unequally. Besides, despite the matches were performed under the same conditions for all players (e.g., same venue, same turf, same referees) some other situational factors that could affect the game demands were not controlled (e.g., temperature). Finally, due to the lack of evidence in Sa5, some other soccer modalities were studied as reference.

#### **6. Conclusions**

This study represents the first effort to report external and internal load demands of Sa5 elite soccer, selecting, using an objective statistical criterion, those representative variables with great influence in physical performance. It was found that players usually performed higher number of accelerations per min when losing a match possible due to the need to increase their efforts to score. Those Sa5 players that scored during a match execute higher DistanceExplosive and Distance21–24 km/h. Considering the goals are usually anteceded by high-intensity actions (e.g., jumps, sprints), those Sa5 players that scored during a match execute higher DistanceExplosive and Distance21–24 km/h. Due to some technical and tactical Sa5 conditions that differentiate the more experienced players from the younger ones, the younger players presented higher HRAVG and AccMax.

#### **7. Practical Applications**

Coaches, athletes and medical staff should address the influence of some contextual variables on external and internal load during top elite Sa5 official matches. The comprehension of the potential differences by match outcome, players age and scoring rate could redirect the designing of conditioning training programs, match strategies, tactical decisions and recovery protocols, especially during congested fixture tournaments.