Citation: Arede, J.; Fernandes, J.F.T.;
Schöllhorn, W.I.; Leite, N. Differential
Repeated Sprinting Training in Youth
Basketball Players: An Analysis of
Effects According to Maturity Status.
Int. J. Environ. Res. Public Health 2022,
19, 12265. https://doi.org/10.3390/
ijerph191912265
Academic Editors: Krzysztof
Ma´ckała and Hubert Makaruk
Received: 12 August 2022
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International  Journal  of
Environmental Research
and Public Health
Article
Differential Repeated Sprinting Training in Youth Basketball
Players: An Analysis of Effects According to Maturity Status
Jorge Arede 1,2,3,4,*
, John F. T. Fernandes 5, Wolfgang I. Schöllhorn 6
and Nuno Leite 4,7
1
Department of Sports Sciences, Exercise and Health, University of Trás-os-Montes and Alto Douro,
5001-801 Vila Real, Portugal
2
School of Education, Polytechnic Institute of Viseu, 3504-501 Viseu, Portugal
3
Department of Sports, Higher Institute of Educational Sciences of the Douro, 4560-708 Penaﬁel, Portugal
4
School of Sports Sciences, Universidad Europea de Madrid, Campus de Villaviciosa de Odón,
28670 Villaviciosa de Odón, Spain
5
School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff CF23 6XD, UK
6
Institute of Sport Science, Training and Movement Science, University of Mainz, 55122 Mainz, Germany
7
Research Center in Sports Sciences, Health Sciences and Human Development, CIDESD,
University of Trás-os-Montes and Alto Douro, 5001-801 Vila Real, Portugal
*
Correspondence: jorge_arede@hotmail.com
Abstract: The differential learning approach, which includes ﬂuctuations that occur without move-
ment repetitions and without corrections has received growing interest in the skill acquisition ﬁeld.
This study aimed to determine the effects of a 9-week training intervention involving differential
repeated sprint training on a series of physical tests in youth basketball players. A total of 29 par-
ticipants with different maturity statuses (pre-peak height velocity (PHV), n = 7; mid-PHV, n = 6;
post-PHV, n = 16) completed 2 sessions per week of differential repeated sprint training for a period
of 9 weeks. Sessions consisted of 2 × 10 repetitions sprints of 20-m whereby participants were
instructed to perform various additional ﬂuctuations for each repetition. Before and after the training
intervention, participants completed jumping tests (countermovement jump (CMJ), single-leg CMJs,
the modiﬁed 505 agility test, and straight sprinting tests (0–10 splits time), and maturity status was
evaluated as well. Within-group analysis showed improvement in CMJ asymmetries and changes
in direction asymmetries and 10-m sprint performance for the pre-, mid-, and post-PHV groups,
respectively (p < 0.05), with large to very large effects. Analysis of covariance demonstrated that
changes in sprint time in post-PHV players were greater than in the pre- and mid-PHV groups
(p < 0.05), with moderate effect. Adding random ﬂuctuations during repeated sprint training appear
to be a suitable and feasible training strategy for maintaining and enhancing physical performance
in youth basketball players, irrespective of maturity status. Furthermore, the present ﬁndings en-
courage practitioners to implement the present approach in youth athletes to improve their physical
performance, but they should be aware that training response can vary according to maturity status.
Keywords: team sports; variation; movement variability; puberty; adolescence; growth; maturation;
bilateral asymmetry
1. Introduction
The requirement for high-intensity running and longer sprint distances has increased
in basketball [1]. Consequently, practitioners have been developing methods of enhancing
sprint and repeated sprint ability (RSA) in team-sports athletes. Since sprinting in basketball
is not exclusively straight-line, it is considered beneﬁcial to prepare athletes to sprint in
different directions and challenge the technical model.
Nevertheless, practitioners should be aware that adolescent youth basketball players
experience puberty, one period of accelerated somatic growth promoted by the syner-
gistic effect of gonadal hormones with growth hormone and insulin-like growth factor
Int. J. Environ. Res. Public Health 2022, 19, 12265. https://doi.org/10.3390/ijerph191912265
https://www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2022, 19, 12265
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1 (IGF-1) [2]. During this period, several physical changes in height, weight, and strength
are observed, resulting in decreased coordination and ﬁne motor control [2]. These changes
could result in increased injury risk, and individualized prevention strategies to reduce
the likelihood of injury should be implemented [2,3]. This approach seems particularly
imperative in “high-risk” or “load-sensitive” athletes, who simultaneously experience the
period of accelerated growth and hold a high degree of sport specialization [4], such as often
occurs with basketball players [5]. This is owing to the few opportunities to experience a
variety of load-adaptive stimuli, resulting in fully developed neuromuscular patterns that
protect against injury [4]. Nonetheless, the body of evidence suggest that underlying mech-
anisms to explain training adaptations are different according maturity status [6]. Whereas
pre-pubertal training adaptations result primarily from nervous system development, pu-
bertal and post-pubertal adaptations are more associated with increases in sex androgen
concentrations (e.g., testosterone, growth hormone, and insulin-like growth factor) [6].
Thus, including variation during training (e.g., using differential learning principles) could
be a suitable strategy for addressing individual needs, mitigating neuromuscular deﬁcits,
and reducing the chance of overloading. However, further studies are needed for better
understanding of the effectiveness of this approach in youth development, whether it is
related to physical performance or health related issues.
In contrast to the traditional training strategy, where ﬂuctuations (i.e., different from
biomechanical models) are viewed as errors that must be minimized, the differential
learning approach [7,8] considers the ﬂuctuations in moving systems as crucial sources
for learning. A major purpose of differential learning is increasing the possibilities of
movement rather than constraining them. Meanwhile, evidence has been provided that
increased movement ﬂuctuations can be quantiﬁed by the amount or structure of noise and
can also be increased or modiﬁed by means of emotions [9] or fatigue [10]. Increasing noise
serves to destabilize the learning system and to launch a genuine self-organizing process.
In its most extreme form, differential learning includes movement variations without
repetition and without correction [11]. Movement corrections in differential learning are
avoided to enable the athlete to ﬁnd their own optimal solution (which would not be the
case if the athletes were being guided by information about “errors”). Also according
to differential learning theory, increased ﬂuctuations result in better skill acquisition and
better learning rates than traditional models [12,13]. Thereby, according to the stochastic
resonance principle within the differential learning theory, the noise is to be optimized
rather than maximized [11].
In this regard, the beneﬁts of the training programs based on differential learning
in both technical and physical skills have been reported in team sports [14]. Related to
differential sprint training, the studies by Schöllhorn et al. [12] and Arede et al. [15] are of
special interest. In the ﬁrst study, the effect of an intensive sprint training 5 times a week
for 6 months, based on repetitions and corrections, was compared with a differential sprint
training twice a week for the same duration in 2 youth male groups [12]. After 6 months,
both groups improved their maximum running speed, but the differential group improved
signiﬁcantly more. Additionally, a pilot study of basketball-speciﬁc sprint training in
differential form in female adolescents [15] provided evidence of beneﬁcial applications
in physical performance. The extent to which differential sprint training depends on the
maturity level of the athletes has not yet been investigated. Based on the previous ﬁndings,
including differential learning approach ﬂuctuations in repeated sprints in a training
program is assumed to have the potential for eliciting physical performance improvements.
Therefore, the aim of this study was to examine the effect of a 9-week training interven-
tion involving repeated differential sprint training on a series of physical tests (i.e., jumping,
sprinting, and change-of-direction) but also in bilateral asymmetries, according to player
maturity status. A better understanding of the effects of differential repeated sprint train-
ing on various aspects of physical performance may help practitioners to better design
training tasks to improve these aspects, considering individual needs based on growth
Int. J. Environ. Res. Public Health 2022, 19, 12265
3 of 15
and maturation. Given the lack of previous comparable reports, we expect that repeated
differential sprint training effects are independent of maturity status.
2. Materials and Methods
2.1. Participants
A group of 38 male basketball players from the under-14 to under-18 age groups were
recruited from the Portuguese Basketball Academy to participate in this study. All partic-
ipants completed a total of ~270 min of basketball training (3 basketball sessions/week,
90 min/session) and 1 to 2 competitive matches per week. All participants were healthy,
free of any injury within the last three months, and without previous history of injury
or surgery that might have affected their physical performance. Only participants who
participated in at least 90% of the workouts were considered for data analysis, which
resulted in the exclusion of 1 player from post-testing analysis (Figure 1). Thirty-one play-
ers completed the training program, but only twenty-nine players were ﬁnally assessed
(Figure 1). Post hoc observed power calculations (G*Power, version 3.1.9.8; University of
Düsseldorf; Düsseldorf, Germany) for analysis of covariance (ANCOVA), including three
groups and one covariate (α = 0.05, d = 0.25), revealed power (β) of 0.09. Written and
informed consent was obtained from all participants’ parents, and player approval was
obtained before the beginning of this investigation. The present study was approved by
the Institutional Research Ethics Committee and conformed to the recommendations of the
Declaration of Helsinki.
 
 
according to player maturity status. A better understanding of the effects of differential 
repeated sprint training on various aspects of physical performance may help 
practitioners to better design training tasks to improve these aspects, considering 
individual needs based on growth and maturation. Given the lack of previous comparable 
reports, we expect that repeated differential sprint training effects are independent of 
maturity status. 
2. Materials and Methods 
2.1. Participants 
A group of 38 male basketball players from the under-14 to under-18 age groups were 
recruited from the Portuguese Basketball Academy to participate in this study. All 
participants completed a total of ~270 min of basketball training (3 basketball 
sessions/week, 90 min/session) and 1 to 2 competitive matches per week. All participants 
were healthy, free of any injury within the last three months, and without previous history 
of injury or surgery that might have affected their physical performance. Only participants 
who participated in at least 90% of the workouts were considered for data analysis, which 
resulted in the exclusion of 1 player from post-testing analysis (Figure 1). Thirty-one 
players completed the training program, but only twenty-nine players were finally 
assessed (Figure 1). Post hoc observed power calculations (G*Power, version 3.1.9.8; 
University of Düsseldorf; Düsseldorf, Germany) for analysis of covariance (ANCOVA), 
including three groups and one covariate (α = 0.05, d = 0.25), revealed power (β) of 0.09. 
Written and informed consent was obtained from all participants’ parents, and player 
approval was obtained before the beginning of this investigation. The present study was 
approved by the Institutional Research Ethics Committee and conformed to the 
recommendations of the Declaration of Helsinki. 
 
Figure 1. Flowchart of participant recruitment and follow-up. 
Figure 1. Flowchart of participant recruitment and follow-up.
2.2. Procedures
This experimental study incorporated a parallel-group, repeated-measures design,
whereby participants were divided into three groups with repeated sprinting training based
on differential learning principles [8] (Pre-PHV, n = 7; Mid-PHV, n = 8; Post-PHV, n = 20).
The groups were clustered according to the percentage of predicted adult height (% PAH).
Int. J. Environ. Res. Public Health 2022, 19, 12265
4 of 15
The training period lasted 9 weeks and was carried out within the regular in-season training
sessions. The tests were performed one and two weeks before the commencement of the
training period and one week after the intervention. Physical performance tests were
conducted under the same experimental conditions (training session time and indoor
basketball court). Testing sessions were completed on the same time interval (between
6:30 p.m. and 9:30 p.m.). A 10-min standardized warm-up was performed (5 min jogging,
dynamic stretching, 10 bilateral squats, core exercises, 10 unilateral squats, and 3 vertical
unilateral jumps) before all testing. Tests were conducted in the following order, respecting
the principles of the National Strength and Conditioning Association for testing order [16]:
anthropometrical measurements, jumping tests (countermovement jump (CMJ), single-leg
countermovement jumps (SLCMJs), the modiﬁed 505 agility test, and straight sprinting
tests (0–10 splits time).
2.3. Training Program
The athletes included in the different training groups participated in two weekly
training sessions during in-court training sessions (Supplementary Table S1). All the
intervention drills were performed at the beginning of the training session, after the warm-
up period. The differential repeated sprint training comprised 2 sets of 10 sprints for 20 m
with 30 s of passive recovery between sprints and 3 min of passive recovery between sets.
Before each repetition, all participants were verbally instructed by the main researcher to
perform a different ﬂuctuation (Supplementary Table S2) or a combination of ﬂuctuations.
No instructed movement ﬂuctuation was repeated more than once in each training session.
These ﬂuctuations were selected based on previous studies involving the differential
learning approach exercises for motor skills [11,15,17]. While differential learning theory,
based on ﬁndings from biomechanical studies on motor learning and neuroanatomical
development [18–20], suggests a coarse orientation on ﬂuctuations that depend on the
learning status [8], in our study, all participants, independent of their maturity status,
executed the same structure of ﬂuctuations. According to differential learning theory,
beginners should focus more on varying variables that are associated with the geometry
of a movement, and with advancing learning status, the focus shifts to variables that are
related to velocity, acceleration, and rhythm [21]. Whether the maturity status corresponds
to learning status in the investigated range of ages needs future extensive research and is
beyond the scope of this study.
2.4. Measurements
Somatic maturation. Height was recorded using a commercially portable stadiometer
(Tanita BF-522W, Japan, nearest 0.1 cm). Body mass was estimated using a scale (Tanita
BF-522W, Japan, nearest 0.1 kg). All measurements were taken following the guidelines
outlined by the International Society for the Advancement of Kinanthropometry (ISAK)
by the same researcher, who holds an ISAK Level 1 accreditation. Players’ height, weight,
chronological age, and mid-parent height were used to predict the adult height of each
player [22]. The heights of the biological parents of each player were self-reported and
adjusted for over-estimation using the previously established equations [23]. The current
height of each player was then expressed as a percentage of their predicted adult height
(% PAH), which can then be used as an index of somatic maturation [24]. Players were
grouped into three maturity bands based on the percentage of predicted adult height
attained at the time of the tournament [25]: <86% (Pre-PHV), 86–95% (Mid-PHV) and >95%
(Post-PHV) of predicted adult stature (Table 1). Only for descriptive reasons, maturity
timing was estimated for each player based on z-scores: average or on-time (z-score
between +0.5 and −0.5), early (z-score > +0.5), and late (z-score < −0.5).
Int. J. Environ. Res. Public Health 2022, 19, 12265
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Table 1. Descriptive data of the subjects (Mean ± SD).
Variables
Pre-PHV (n = 7)
Mid-PHV (n = 6)
Post-PHV (n = 16)
Biological age (years)
12.01 ± 0.36
13.32 ± 0.58
16.97 ± 1.15
Height (cm)
149.14 ± 7.31
160.67 ± 7.99
179.31 ± 8.68
Body mass (kg)
39.86 ± 10.78
53.83 ± 10.80
74.13 ± 15.09
PAH (%)
83.71 ± 1.11
88.67 ± 2.50
98.69 ± 1.70
Timing
−0.01 ± 0.50
1.75 ± 0.63
0.90 ± 0.39
Maturity Timing
(Z-score)
Early = 1
On-time = 4
Late = 2
Early = 6
On-time = 0
Late = 0
Early = 14
On-time = 2
Late = 0
Training experience
(years)
4.86 ± 0.38
3.50 ± 1.38
5.94 ± 2.79
Legend: PHV = Peak of height velocity; PAH = Percentage of Adult Height. Note: A z-score < −0.5 is late, > +0.5
is early, and between +0.5 and −0.5 is average or on-time.
Bilateral and Unilateral Countermovement Jumps (CMJ). CMJs were assessed according to
the Bosco Protocol [26]. Participants performed three successful single leg CMJs (SLCMJs)
with each leg in the vertical and horizontal directions. Participants began by standing
on one leg, then descended into a countermovement before extending the stance leg to
jump as far or as high as possible in the vertical and horizontal directions. The landing
was performed on both feet simultaneously. A successful trial included hands remaining
on the hips throughout the movement and balance being maintained for at least 3 s after
landing. If the trial was considered unsuccessful, a new trial was performed. In the
horizontal direction, the participants started with the selected leg positioned just behind a
starting line. The jump height was recorded using an infrared optical system (OptoJump
Next—Microgate, Bolzano, Italy).
The modiﬁed 505 agility test (COD). Each participant was instructed to run to a mark
situated 5 m from the starting line, perform a 180◦ COD using the right or left leg to push
off, and return to the starting line, covering a total of 10 m [27]. The participants were asked
to pass the line indicated on the ground with their entire foot at each turn. The modiﬁed
505 agility test total time was recorded with 90 cm height photoelectric cells separated by
1.5 m (Witty, Microgate, Bolzano, Italy). Each participant performed 2 sprints with COD for
each side with 2 min of rest between them. Players began each trial in standing staggered
position with their front feet 0.5 m behind the ﬁrst timing gate. The lower limb asymmetry
index (ASI) was determined using the following formula [28]: ASI = 100/Max Value (right
and left)*Min Value (right and left)* − 1 + 100. The COD deﬁcit (CODD) for the double
180◦ COD test for each leg was calculated via the following formula: mean double modiﬁed
505 agility test time—mean 10 m time [27].
Sprint test. The running speed was evaluated as 10 m (0–10 m) split time. Running
times were recorded with single pairs of 90 cm high photoelectric cells separated by 1.5 m.
Each participant performed 2 trials with 2 min of rest between each trial. Players began
each trial in an upright standing position with their feet 0.5 m behind the ﬁrst timing gate.
2.5. Statistical Analyses
Descriptive data are presented as mean (M) ± standard deviation (SD). The reliability
of test measures was computed using an average-measures two-way random intraclass
correlation coefﬁcient (ICC) with absolute agreement, inclusive of 95% conﬁdence inter-
vals (CI), and the coefﬁcient of variation (CV). The ICC was interpreted as poor (<0.5),
moderate (0.5–0.74), good (0.75–0.9), or excellent (>0.9) [29]. Coefﬁcients of variation were
considered acceptable if <10% [30]. The normality of the data distribution and spheric-
ity were conﬁrmed using the Shapiro–Wilk statistic and Levene’s test for the equality of
variances, respectively. The analysis of variance (ANOVA) with bootstrapping was used
to compare the groups at baseline, and Tukey’s post hoc test was used in conjunction
Int. J. Environ. Res. Public Health 2022, 19, 12265
6 of 15
to examine the differences between groups. Effect sizes were evaluated using an omega
squared (ω2), with <0.06, 0.06–0.14, and >0.14 indicating a small, medium, or large effect,
respectively. A paired-samples t-test with bootstrapping was used to analyse within-group
changes [31]. Percentage changes were calculated as ([post-training value—pretraining
value]/pre-training value) × 100. Differences between pre- and post-test were calculated
according to criteria described elsewhere [32]. Effect sizes (ES) of the within-group changes
were evaluated using Hedges’ g correcting small sample biases [33]. The effect sizes were
considered <0.2 trivial, >0.2–0.5 small, >0.5–0.8 medium, >0.8–1.3 large, and >1.3 very
large [34]. An ANCOVA with Bonferroni-adjusted post hoc tests was performed to examine
the differences between groups (Pre-PHV, Mid-PHV, and Post-PHV) in post-training values
where the pre-training score was used as a covariate, the post-test scores as the dependent
variable and the maturity status as the independent variable [35]. ES was evaluated with
partial eta squared (η2p), and the threshold values were no effect (η2p < 0.04), minimum ef-
fect (0.04 < η2p < 0.25), moderate effect (0.25 < η2p < 0.64), and strong effect (η2p > 0.64) [36].
This measure has been widely cited as a measure of ES and predominantly provided by
statistical software [37]. All statistical analyses were performed using the SPSS software
(version 28 for Windows; SPSS Inc., Chicago, IL, USA).
3. Results
3.1. Tests Reliability
All ICCs were excellent (ICC range = 0.97–0.99), and most (5 of the 6) of the CVs were
acceptable (CV range = 1.34–10.11%) (Table 2).
Table 2. Reliability data for test variables. Data are presented as value with lower- and -upper
conﬁdence limits.
Test Variables
ICC
(95% CL)
CV (%)
(95% CL)
CMJ (cm)
0.98 (0.97; 0.99)
5.66 (3.81; 7.52)
0–10 m (s)
0.99 (0.98; 0.99)
1.34 (0.88; 1.80)
CMJR (cm)
0.98 (0.97; 0.99)
8.19 (6.47; 9.92)
CMJL (cm)
0.98 (0.97; 0.99)
10.11 (7.82; 12.39)
M505R (s)
0.97 (0.92; 0.98)
2.58 (2.01; 3.14)
M505L (s)
0.98 (0.95; 0.99)
1.96 (1.36; 2.56)
Abbreviations: ICC = Intraclass correlation coefﬁcient; CV = Coefﬁcient of variation; CL = Conﬁdence limits;
CMJ = Countermovement jump height; 0–10 m = 0–10 m sprint time; M505 = Modiﬁed 505 agility test; R = Right;
L = Left.
3.2. Tests Outcomes
At baseline, the training groups were signiﬁcantly different in CMJ, 0–10 m sprint
time, CMJR, CMJL, M505R, and M505L (p ≤ 0.05; large effect; see Table 3). Tukey’s post
hoc analysis revealed signiﬁcant differences between the Pre-PHV and Post-PHV training
groups on these physical performance tests. Within-group changes for both training groups
are described in Table 3. The Pre-PHV training group showed a signiﬁcant decrease in
CMJASY (p ≤ 0.05, large effect), and the Mid-PHV training group showed a signiﬁcant
decrease in CODASY (p ≤ 0.05, very large effect). Finally, the Post-PHV training group
showed signiﬁcant improvement in 0–10 m sprint time (p ≤ 0.01, large effect). According to
the ANCOVA results, signiﬁcant differences were observed in 0–10 m sprint time (p ≤ 0.05;
moderate effect), with higher results for the Post-PHV than the Pre-PHV.
Int. J. Environ. Res. Public Health 2022, 19, 12265
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Table 3. Inferences of the training programs intervention on subject’s performance measures.
Variables
Pretest,
Mean ± SD
Postest,
Mean ± SD
∆ %
p
Hedge’s g
Between-
Groups
Pretest
Differences (p)
ω2
ANCOVA
(p)
η2p
CMJ (cm)
Pre-PHV
22.06 ± 6.55
23.44 ± 5.41
6.28
0.171
0.007 *
0.26
(−0.04; 0.47)
0.466
Mid-PHV
25.23 ± 6.80
26.37 ± 6.63
4.49
0.444
Post-PHV
34.73 ± 9.95
35.51 ± 8.61
2.23
0.372
0–10 m (s)
Pre-PHV
2.18 ± 0.29
2.17 ± 0.28
−0.46
0.731
0.014 *
0.22
(−0.06; 0.43)
0.020 *
0.27
Mid-PHV
2.07 ± 0.16
2.03 ± 0.17
−2.25
0.138
Post-PHV
1.88 ± 0.21
1.81 ± 0.17
−3.53
0.000
1.05
(0.42; 1.65)
CMJR (cm)
Pre-PHV
11.74 ± 3.90
12.44 ± 3.99
5.96
0.222
0.014 *
0.22
(−0.06; 0.44)
0.072
Mid-PHV
12.28 ± 2.79
14.22 ± 3.21
15.74
0.205
Post-PHV
19.66 ± 8.01
20.86 ± 6.35
6.14
0.052
CMJL (cm)
Pre-PHV
13.67 ± 3.61
13.61 ± 4.17
−0.42
0.945
0.027 *
0.18
(−0.07; 0.40)
0.332
Mid-PHV
12.72 ± 2.27
14.82 ± 2.93
16.51
0.131
Post-PHV
19.67 ± 7.45
20.85 ± 7.64
6.01
0.098
CMJASY (%)
Pre-PHV
26.96 ± 6.61
19.67 ± 7.56
−27.04
0.046
0.88
(−0.03; 1.75)
0.195
0.095
Mid-PHV
27.57 ± 12.77
26.57 ± 8.28
−3.62
0.819
Post-PHV
20.33 ± 9.96
18.61 ± 11.34
−8.47
0.611
M505R (s)
Pre-PHV
3.15 ± 0.35
3.06 ± 0.38
−2.90
0.112
0.026 *
0.18
(−0.07; 0.40)
0.430
Mid-PHV
3.07 ± 0.17
3.01 ± 0.18
−1.90
0.321
Post-PHV
2.78 ± 0.32
2.72 ± 0.22
−2.22
0.164
M505L (s)
Pre-PHV
3.13 ± 0.36
3.10 ± 0.38
−0.91
0.365
0.023
0.19
(−0.00; 0.41)
0.177
Mid-PHV
3.15 ± 0.13
3.00 ± 0.22
−4.56
0.063
Post-PHV
2.80 ± 0.33
2.73 ± 0.25
−2.41
0.091
CODASY
(%)
Pre-PHV
4.85 ± 4.05
5.54 ± 2.19
14.42
0.648
0.594
0.326
Mid-PHV
6.34 ± 1.62
4.02 ± 1.41
−36.56
0.015
1.94
(0.50; 3.32)
Post-PHV
5.33 ± 2.18
5.68 ± 2.96
6.43
0.705
CODDR (s)
Pre-PHV
1.03 ± 0.14
0.94 ± 0.13
−8.97
0.172
0.192
0.664
Mid-PHV
1.04 ± 0.17
0.99 ± 0.12
−4.94
0.326
Post-PHV
0.93 ± 0.14
0.94 ± 0.10
1.00
0.804
CODDL (s)
Pre-PHV
0.99 ± 0.13
0.96 ± 0.10
−2.88
0.541
0.115
0.864
Mid-PHV
1.09 ± 0.12
0.97 ± 0.14
−10.70
0.075
Post-PHV
0.95 ± 0.14
0.93 ± 0.11
−1.19
0.782
Abbreviations: CMJ = Countermovement jump height; 0–10 m = 0–10 m sprint time; M505 = Modiﬁed 505 agility
test; COD = Change of direction test; CODD = COD deﬁcit; R = Right; L = Left; ASI = Bilateral asymmetry;
* Pre-PHV vs. Post-PHV (p < 0.05).
Figure 2 displays the individual changes in performance from pre- to post-test for
each training group. Most Pre-PHV subjects were better at CMJ (57%) and CMJR (71%)
on the post-test compared with the pre-test. In the same training group, all subjects
improved CMJL. Furthermore, within Pre-PHV, distinct training responses were observed
for 0–10 sprint time. The majority of Mid-PHV subjects were better in M505L (50 %), when
comparing to the pre-test values. However, in the same training group many subjects kept
the same performance in CMJL (33%) and 0–10 sprint time (33%), in post-test. Nevertheless,
in CMJ distinct training response were observed in Mid-PHV subjects. In the post-PHV
group, many subjects improved 0–10 sprint time (63%); however, distinct training response
was observed for different tests, with exception of CMJR.
Int. J. Environ. Res. Public Health 2022, 19, 12265
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Int. J. Environ. Res. Public Health 2022, 19, x  
8 of 16 
 
 
 
Figure 2. Percentage of athletes per training response. Legend: (A) Pre-PHV; (B) Mid-PHV; (C) Post-
PHV. 
4. Discussion 
The aim of this study was to examine possible group specific effects of differential 
repeated sprinting training dependent on maturity status. Although all groups had the 
same training content of differential sprint training exercises, every group had a different 
training response in distinct variables. We found that the presented training program 
resulted in significant decreases in bilateral asymmetries during the physical performance 
tests in the Pre- and Mid-PHV subjects. Moreover, the Post-PHV training group improved 
their 0–10 m sprint time significantly more than the Pre-PHV subjects. Furthermore, Mid-
PHV had more homogenous training responses (better and/or same), whereas more 
diverse training responses were observed in Pre-PHV and Post-PHV. Whether these 
results depend on the different levels at the beginning or on the maturity status needs 
further research.  
Given the lack of comparative studies on the training response by maturity status, 
this study should be viewed as the starting point for further studies on this topic as a 
further intermediate step on the way to individuality of learning [38]. The results indicate 
that 9 weeks of differential repeated sprinting training of adolescent male basketball 
players had a beneficial impact in 0–10 m sprint time in different maturity statuses, 
especially in Post-PHV subjects, as the effect was significantly higher than Pre-PHV. The 
extent to which the lower increase in performance in the Pre-PHV group is indicative of 
either too much variation or wrong variations for the performance level and thus suggests 
that a more traditional approach or individually adapted variations to sprint training are 
recommended, which at this level still has sufficient variation for optimal learning even 
with repetition. Whether there is a principle level dependency, needs to be clarified in 
future studies [11,39]. However, performance advances should not forget the long-term 
development of athletes, where other parameters like higher symmetry in CMJs could be 
a preventive and precondition for further performance gains. The beneficial impact in 0–
10 m sprint time is in line with previously results obtained in a pilot study on female 
basketball players [15]. Nonetheless, results from other studies differ in magnitude. For 
Figure 2.
Percentage of athletes per training response.
Legend: (A) Pre-PHV; (B) Mid-PHV;
(C) Post-PHV.
4. Discussion
The aim of this study was to examine possible group speciﬁc effects of differential
repeated sprinting training dependent on maturity status. Although all groups had the
same training content of differential sprint training exercises, every group had a different
training response in distinct variables. We found that the presented training program
resulted in signiﬁcant decreases in bilateral asymmetries during the physical performance
tests in the Pre- and Mid-PHV subjects. Moreover, the Post-PHV training group improved
their 0–10 m sprint time signiﬁcantly more than the Pre-PHV subjects. Furthermore, Mid-
PHV had more homogenous training responses (better and/or same), whereas more diverse
training responses were observed in Pre-PHV and Post-PHV. Whether these results depend
on the different levels at the beginning or on the maturity status needs further research.
Given the lack of comparative studies on the training response by maturity status, this
study should be viewed as the starting point for further studies on this topic as a further
intermediate step on the way to individuality of learning [38]. The results indicate that
9 weeks of differential repeated sprinting training of adolescent male basketball players
had a beneﬁcial impact in 0–10 m sprint time in different maturity statuses, especially
in Post-PHV subjects, as the effect was signiﬁcantly higher than Pre-PHV. The extent to
which the lower increase in performance in the Pre-PHV group is indicative of either
too much variation or wrong variations for the performance level and thus suggests that
a more traditional approach or individually adapted variations to sprint training are
recommended, which at this level still has sufﬁcient variation for optimal learning even
with repetition. Whether there is a principle level dependency, needs to be clariﬁed in
future studies [11,39]. However, performance advances should not forget the long-term
development of athletes, where other parameters like higher symmetry in CMJs could be
a preventive and precondition for further performance gains. The beneﬁcial impact in
0–10 m sprint time is in line with previously results obtained in a pilot study on female
basketball players [15]. Nonetheless, results from other studies differ in magnitude. For
example, 6 weeks of plyometric training resulted less effective improvement in 0–10 m
Int. J. Environ. Res. Public Health 2022, 19, 12265
9 of 15
sprint time in youth basketball players [40], whereas other short- to medium-term training
protocols (combined strength and conditioning, small-sided games training, high-intensity
interval training, and plyometric, strength and change-of-direction training) were more
effective at improving the 0–10 m sprint time in pubertal youth basketball players, based
in their maturity offset [41–43]. In contrast, the current protocol gives indication to be
superior to 6-week eccentric overload training that was direction-speciﬁc [44], and 10-week
strength training program with random recovery times [45] to achieve gains in 0–10 m
sprint time. These ﬁndings are in line with Rumpf and colleagues [46] who suggested that
other methods (e.g., plyometrics and strength) can be more effective to improve speed
during puberty, whereas the combination of methods in athletes with accumulated training
and well-developed training skills combination of training methods, forms and purposes in
a single drill can be particularly effective [47]. Thereby, discrepancies between studies, and
between maturity status can have substantial inﬂuence on neuromotor development aspects
which underlie possible training adaptations to the differential repeated sprint training.
However, with respect to the actual more generally discussed replication crisis [48,49] and
the critical discussion of the applied statistics therein the results are rather to be considered
as helpful proposals and cannot be generalized [50]. Including our own investigation, they
at best provide suggestions that it is worthwhile to conduct further research in this area.
During differential repeated sprinting training, many alternating variants of sprinting
occur in a single session. In this regard, in comparison with normal sprinting patterns,
differential sprints provide a multitude of kinematic and kinetic changes [12,51–56]. Here,
the general idea of differential learning theory is to also use restrictions in one area to
increase ﬂuctuations in another area in the short term and then increase the number of
opportunities in general in the long term by combining the again released constrained
area with the increased ﬂuctuations in the other areas. Thereby it is important to notice
that the restrictions are explicitly not used for guiding the system towards an externally
given problem solution but to initiate a self-organizing process. For example, sprinting
with the arms held across the chest or running with the arms held behind the back resulted
in increased peak lateral ground reaction forces and higher peak hip internal rotation, and
knee ﬂexion [54]. Moreover, forward trunk lean sprinting resulted in greater lengths of all
the three hamstring muscles at foot strike and toe-off [53]. Evidence was also provided
that the restriction of scapula movement inﬂuenced the stance-leg motion and whole-
body position during the ﬁrst step, but also the sprint speed [55]. Restricted arm action
(i.e., crossed arms) resulted in compensatory upper body motions that could provide the
rotational forces needed to offset the lower body angular momentum generated by the
swinging legs [52]. Adding “erroneous” and non-representative -movements by increasing
the existing ﬂuctuation during repeated sprint training generate short term co-contractions
(i.e., simultaneous contraction of agonist and antagonist muscles around a joint), which
provide more joint stability and higher accelerating forces [57,58]. However, combining
higher levels of noise, speed, and co-contractions may reduce the momentary speed of
movement but provide stronger and movement adequate stimuli for muscle groups that
are requested in situations of high competitive stress [56,59]. Greater physical performance
requires a balance between maximizing the movement intensity, controlling movement
through co-contractions, faster relaxation, and reducing muscle slack [56,59]. In this regard,
the transient shift from protective, long-latency reﬂexes to pre-active, short-latency reﬂex
recruitment throughout maturation, particularly the reduction of inhibitory mechanisms to
protect the Musculo-tendon unit [60] can result in more efﬁcient stretch shortening cycle
(SSC) actions [58], explaining better training response in 0–10 m sprint time of Post-PHV
subjects comparing to the Pre-PHV.
Closely connected to the increase in the multitude of muscle activation patterns due to
changed joint lever conditions and, consequently, due to the changed proprioception are
changes in the brain activation. Neurophysiological adaptations resulting from differential
learning include electroencephalographic frequencies in the alpha- and theta-bands which
beneﬁts short-term memory and learning [61]. Moreover, there is evidence that differential
Int. J. Environ. Res. Public Health 2022, 19, 12265
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learning results in increased theta activity in contralateral parieto–occipital regions [61]
but also stimulates the somatosensory and motor system and engages more regions of the
cortex [62]. Notwithstanding these meaningful ﬁndings, brain activity after differential
learning has been only analyzed in young adults, and the effects of differential learning,
including the brain activity, may be different during neurodevelopment in childhood
and puberty, resulting in inter-individual differences in terms of physical performance.
Indeed, during young adulthood occurs a peaking of white matter volume [63], an area
which controls the signals that neurons share, coordinating how well brain regions work
together [64]; whereas, the peak of grey matter (i.e., area with large number of neurons)
volume occurs before typical age of puberty onset [63]. Moreover, the process of myelination
(i.e., acquisition of the highly specialized myelin membrane around axons) occurs from the
back of the cerebral cortex to front, and from subcortical regions to higher centers of the
central nervous system (e.g., cerebellum and cortex) [65]. This suggests that the learning of
complex skills may lead to distinct neurological adaptations with respect to the maturity
status. In fact, learning complex skills results in noticeable changes in the white matter;
however, learning after adolescence is associated with increased white matter development
in regions that are still undergoing myelination, such as the forebrain [64]. This region
integrates different brain areas, such as the prefrontal cortex, the premotor cortex, and the
primary motor cortex associated with voluntary movement [65]. Altogether, Post-PHV
may have beneﬁted from both brain maturity patterns and neurophysiological adaptations
of training in speciﬁc brain areas, resulting in improved performance during voluntary
actions, such as short sprinting.
After the differential repeated sprint training program, irrespective of maturity status,
participants displayed higher values of unilateral vertical jumping (except for CMJL in
pre-PHV) compared to the pre-test values. Similar beneﬁts for unilateral vertical jump-
ing were observed in a pilot study [15]; whereas different effects occurred after a group
of youth basketball players completed different training programs [44,45,66]. Albeit en-
hanced neuromuscular qualities can be achieved using movement variability [67], overload
and assist musculature of hip and knee regions involved in the SSC may be beneﬁcial
(e.g., higher peak activity of knee stabilizers muscles or considering concentric peak verti-
cal power/body weight) [68,69], to have higher unilateral jumping height in youth athletes.
Furthermore, differential repeated sprint training program was particularly beneﬁcial
for Mid-PHV athletes regarding vertical unilateral jumping. These results are particularly
promising because using the present training strategy, practitioners can simultaneously
achieve positive adaptations resulting from natural improvements in maximal muscular
power during puberty [60], but also adjust load patterns considering particularities of
accelerated growth period. Thereby, during puberty muscle strength increases, but there is
no increase in proportion to limb inertial properties; and, excessive physical loading may
cause skeletal injury, particularly through overuse mechanism. Therefore, jumping training
during puberty should be carefully prescribed because the increased risk of joint overload,
and coordination training (movement adaptability) should be particularly emphasized [2].
In this regard, practitioners can provide a relatively safe, enjoyable, and effective training
program more based on individual needs, frequently alternating many variants of sprinting
in a single session using differential learning, resulting in improved multifaceted adaptabil-
ity, and consequently improved vertical unilateral jumping. Moreover, subjects may beneﬁt
from an immediate transfer to speciﬁc sport such as previously observed after differential
learning based jumping training in handball [21].
In addition, it is widely established that change-of-direction speed is an essential
skill among youth athletes engaging in team sports [70]. The current training program
was beneﬁcial (but without statistical signiﬁcance) during the agility test including 180◦
change of direction. This change of direction involves a more aggressive cutting angle
(≥75◦) which includes higher braking requirements [71]. In this regard, fastest performance
in 180◦ change of direction includes higher propulsive and braking forces (particularly
horizontal) on the ﬁnal foot contact [72], and has been associated with higher eccentric
Int. J. Environ. Res. Public Health 2022, 19, 12265
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and isometric strength [70]. Moreover, the 180◦ change of direction involves high peak
muscle activity of the knee stabilizers (vastus medialis and lateralis) which play a key
role in frontal play control [69]. Thus, chronic exposure to frequently alternating variants
of sprinting in a single session can generate structural and functional adaptations which
positively inﬂuences biomechanical determinants of 180◦ change of direction, resulting in
improved performance in a controlled setting. Furthermore, youth athletes may have bene-
ﬁted from continued neural development and hormonal changes throughout childhood
and adolescence, resulting in improved change of direction performance [73]. Nevertheless,
a previous study involving 16 years old male basketball players which included multidi-
rectional eccentric overload training resulted in similar gains in the same 180◦ change of
direction test [44]. Thus, older players may beneﬁt from multidimensional adaptations
(i.e., biomechanical, morphological, and neuromuscular levels) resulting from eccentric
training [74], which could provide an advantage in high-intensity actions, such as cutting.
Moreover, athletes may have beneﬁted from performing resistance exercises (i.e., unilateral
lateral eccentric overload training) including frontal and transverse plane-dominated tasks,
similar to a 180◦ COD test. Notwithstanding, the present ﬁndings are promising because the
training strategy is low in cost due to no equipment requirements and the results are bene-
ﬁcial in 180◦ change of direction, including the potential of increased neurophysiological
adaptations [61].
Increases in bilateral asymmetries are observed during early stages of adolescence or
in the period of accelerated growth, particularly when rapid gains in limb length occur [75].
In this regard, young athletes can be more predisposed to various injuries in high-intensity
activities (e.g., cutting and landings), because of additional stress placed on the weaker leg
due to bilateral asymmetry [75]. In the present study, most of subjects had CMJASY above
10% cut-off criterion for bilateral asymmetries becoming more likely to have an injury.
Indeed, the participants of our study had larger CMJASY and CODASY than previously
observed in youth tennis players, irrespective of maturity status based in maturity off-
set [76]. Notwithstanding, the applied training strategy was effective to decrease CMJASY
and CODASY, in Pre- and Mid-PHV, respectively. In this regard, differential repeated sprint
training which generates neurophysiological adaptations seems to be similarly beneﬁcial
to other methods to reduce discrepancies between lower limbs (e.g., bilateral and unilateral
strength and plyometric training, and balance and core training) [77], in young subjects
where neural mechanisms are mainly responsible for training adaptations [47]. On the
contrary to previously observed after 10-week strength training program with random
recovery times involving post-pubertal male basketball players [45], the decrease in CMJASY
was substantially lower in the present study. This comparison between studies suggests
that resistance training may be more effective to induce positive changes in CMJASY.
In addition, contrary to what was observed in the pilot study, probably one reason
of a lower starting performance level [15], the present protocol did not result in increased
CMJ performance. In previous studies including young male basketball players, CMJ
values showed higher improvements after completing different short- to medium-term
training programs (most of them including jumps) compared to that of the present study,
irrespective of maturity status [41–43,78–81]. It appears that a greater dynamic correspon-
dence of CMJ with different exercises (vertical jumps, axial based resistance exercises,
etc.) may be responsible for achieving the CMJ improvement. Also, in older basketball
players (≥16 years old), short- to medium resistance training programs (6–10 week) in
unilateral and bilateral fashion resulted more [45,82], albeit lower magnitude was observed
in direction-speciﬁc eccentric overload training [44]. It suggests different between-studies
underlying mechanisms explaining the adaptations in jumping performance, particularly
in pre- and pubertal stages, where higher improvements were observed. Thereby, the
adaptative response to frequently alternating variants of sprinting in a single session using
differential learning which result in improved ability to use the positive effect of SSC to the
vertical jumping performance, could be related to neural improvements in these stages [47].
Notwithstanding, in prepubertal and pubertal stages, the magnitude of improvement in
Int. J. Environ. Res. Public Health 2022, 19, 12265
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a key physiological mechanism underlying efﬁcient movement, such as utilization of the
SSC, seems to be greater according the level of neuromuscular load experienced in this
plane, how occurs in plyometric training [60].
5. Conclusions
Often interpreted at a ﬁrst superﬁcial glance as arbitrary variations, on a slightly closer
look the variations proposed under the differential learning approach turn out to be tar-
geted interventions for a holistic neuromuscular and speciﬁc training that must be adjusted
to every discipline and level of performance [8]. Through constantly changing postures
within the context of the discipline (crossed arms in front of the body, arms above the head,
etc.) there is not only a stronger tuning of targeted muscle groups through correspondingly
changed levers, but also a more versatile or noisy tuning of the neuronal system (e.g., motor
and somatosensory cortices), which thus becomes more robust against future disturbances.
Thereby, the body and especially head rotations around various axis are of special im-
portance since they train the versatile interactions of the vestibular apparatus with the
activating and perceiving apparatus [20,56]. Our ﬁndings indicate that adding “erroneous”
ﬂuctuation and non-representative movements during repeated sprint training can result
in a signiﬁcant reduction of bilateral asymmetries during physical performance tests, in
pre- and mid-PHV basketball players. Furthermore, Post-PHV athletes improved their
10-m sprint to a greater extent than Pre- and Mid-PHV. Generally, the Mid-PHV had more
positive and homogenous training response (better and/or same), whereas more varied
response was observed in their Pre- and Post-PHV counterparts. Indeed, the inclusion of
these ﬂuctuations within repeated sprint training may positively inﬂuence the basketball
players’ movement patterns towards more effective and stabilized skills. The positive
adaptations are potentially owing to concomitant neurophysiological adaptations induced
by the differential repeated sprint training. Nonetheless, how much of the learning progress
is inﬂuenced by the continuously changing biomechanical conditions and how much by
the cognitive effect of not having errors corrected in connection with the accompanied
disadvantageous brain activations needs to be clariﬁed in future. Nevertheless, the present
ﬁndings may encourage practitioners to implement similar protocols in youth athletes to
improve physical performance, although always being aware that training response can be
variable according to maturity status. Furthermore, the higher variability of stimuli during
the training also suggests looking for additional effects on prevention of injuries, which
have higher incidence during periods of accelerated growth. Finally, further studies should
examine the real differences between the application of differential repeated sprint training
to the natural development without any training protocol (i.e., control group), advancing
towards more individuality in training.
Supplementary Materials: The following supporting information can be downloaded at: https:
//www.mdpi.com/article/10.3390/ijerph191912265/s1, Table S1: Training program variations. Table
S2: Examples of the ﬂuctuations performed during differential repeated sprint training interventions.
Author Contributions: Data curation, J.A.; Formal analysis, J.A.; Funding acquisition, N.L.; Inves-
tigation, J.A. and N.L.; Methodology, J.A. and N.L.; Project administration, J.A.; Validation, J.A.;
Visualization, J.A.; Writing—original draft, J.A., J.F.T.F., W.I.S. and N.L.; Writing—review & edit-
ing, J.A., J.F.T.F., W.I.S. and N.L. All authors have read and agreed to the published version of
the manuscript.
Funding: This work was supported by the Foundation for Science and Technology (FCT, Portugal),
under the project UIDB 04045/2020.
Institutional Review Board Statement: The present study was approved by the Institutional Re-
search Ethics Committee and conformed to the recommendations of the Declaration of Helsinki.
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: The data that support the ﬁndings of this study are available from the
corresponding author, J.A., upon reasonable request.
Int. J. Environ. Res. Public Health 2022, 19, 12265
13 of 15
Conﬂicts of Interest: The authors declare no conﬂict of interest.
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Differential Repeated Sprinting Training in Youth Basketball Players: An Analysis of Effects According to Maturity Status.
Arede, Jorge,Fernandes, John F T,Schöllhorn, Wolfgang I,Leite, Nuno