RESEARCH ARTICLE
Sprint Conditioning of Junior Soccer Players:
Effects of Training Intensity and Technique
Supervision
Thomas Haugen1,2*, Espen Tønnessen1, Øyvind Øksenholt3, Fredrik Lie Haugen3,
Gøran Paulsen1,3, Eystein Enoksen3, Stephen Seiler2
1 Norwegian Olympic Sports Program (Olympiatoppen), Sognsveien 228, 0840 Oslo, Norway, 2 Faculty of
Health and Sport Sciences, University of Agder, Gimlemoen 25, 4630 Kristiansand, Norway, 3 Norwegian
School of Sport Sciences, Sognsveien 220, 0806 Oslo, Norway
* thomas.haugen@olympiatoppen.no
Abstract
The aims of the present study were to compare the effects of 1) training at 90 and 100%
sprint velocity and 2) supervised versus unsupervised sprint training on soccer-specific
physical performance in junior soccer players. Young, male soccer players (17 ±1 yr,
71 ±10 kg, 180 ±6 cm) were randomly assigned to four different treatment conditions over a
7-week intervention period. A control group (CON, n=9) completed regular soccer training
according to their teams’ original training plans. Three training groups performed a weekly
repeated-sprint training session in addition to their regular soccer training sessions per-
formed at A) 100% intensity without supervision (100UNSUP, n=13), B) 90% of maximal
sprint velocity with supervision (90SUP, n=10) or C) 90% of maximal sprint velocity without
supervision (90UNSUP, n=13). Repetitions x distance for the sprint-training sessions were
15x20 m for 100UNSUP and 30x20 m for 90SUP and 90UNSUP. Single-sprint performance
(best time from 15x20 m sprints), repeated-sprint performance (mean time over 15x20 m
sprints), countermovement jump and Yo-Yo Intermittent Recovery Level 1 (Yo-Yo IR1)
were assessed during pre-training and post-training tests. No significant differences in per-
formance outcomes were observed across groups. 90SUP improved Yo-Yo IR1 by a mod-
erate margin compared to controls, while all other effect magnitudes were trivial or small. In
conclusion, neither weekly sprint training at 90 or 100% velocity, nor supervised sprint train-
ing enhanced soccer-specific physical performance in junior soccer players.
Introduction
The importance of sprinting in professional soccer is well established and the need for speed is
clear [1–4]. According to track-and-field statistics [5], trends over time from large retrospective
data collections in soccer players [3,4] and the experience of practitioners [6], sprint perfor-
mance is resistant to training enhancement. Athletes can spend years training to improve a few
hundredths of a second over short distances [5]. Numerous intervention studies have been
PLOS ONE | DOI:10.1371/journal.pone.0121827
March 23, 2015
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a11111
OPEN ACCESS
Citation: Haugen T, Tønnessen E, Øksenholt Ø,
Haugen FL, Paulsen G, Enoksen E, et al. (2015)
Sprint Conditioning of Junior Soccer Players: Effects
of Training Intensity and Technique Supervision.
PLoS ONE 10(3): e0121827. doi:10.1371/journal.
pone.0121827
Academic Editor: Oyvind Sandbakk, Norwegian
University of Science and Technology, NORWAY
Received: November 10, 2014
Accepted: February 4, 2015
Published: March 23, 2015
Copyright: © 2015 Haugen et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
credited.
Data Availability Statement: All relevant data are
within the paper.
Funding: The authors have no support or funding to
report.
Competing Interests: The authors have declared
that no competing interests exist.
performed over the years in order to enhance soccer-specific sprinting. A recent review reveals
that sprinting under assisted, resisted and normal conditions, maximal and explosive strength
training, plyometric training and high-intensity running have been investigated in different
combinations, but no specific training method has so far emerged as superior [1]. Time effi-
ciency is an important constraining aspect of team-sport conditioning and extensive off-field
interventions will most likely be rejected by team coaches, independent of intervention
efficacy [1].
The term ‘direct supervision’ refers to training situations in which a supervisor or training
expert is present at all times [7,8]. The supervisor oversees training activities as they occur and
provides direction, instruction, feedback and assistance. The importance of guidance and feed-
back during practice is well known in motor skill learning and performance enhancements
may happen immediately in such settings [9]. Mazzetti et al. [7] and Coutts et al. [8] concluded
that the presence of a training expert was beneficial for maximal strength development over
time. To the authors’ knowledge, the effect of supervised sprint-training sessions in soccer
players has not been investigated. According to motor skill learning theories, errors increase
with the speed of the movement [9]. Technical training of typically rapid or ballistic move-
ments should be interfered with by using specific drills, large amount of repetitions and an in-
tensity where the athletes are able to control the movements (proper execution not interfered
by fatigue). If the movement is slowed down slightly, the same generalized motor program can
be used as in the normal-speed version [9]. In contrast, the vast majority of studies involving
sprint-training interventions for soccer players make no recommendations other than that
sprint velocity should be maximal throughout [1]. Available evidence in endurance and
strength training demonstrates that high, but sub-maximal intensity loading effectively stimu-
lates adaptation through the interaction between high intensity and larger accumulated work
that can be achieved before the onset of fatigue, compared to maximal efforts [10,11]. This
makes it tempting to speculate similar effects on sprinting. Anecdotal evidence in support of
this is observed in the sprint-training philosophy developed by the athletic sprint pioneer
coach Carlo Vittori in the mid-1970s [12]. His successful athletes performed repeated-sprint
training sessions with an intensity as low as 90% of maximal sprint speed during initial pre-sea-
son conditioning in order to improve sprint endurance (later termed repeated-sprint perfor-
mance). Inspection of training diaries reveals that internationally-competing sprinters perform
sprint training with varying intensity through all parts of the season (unpublished material,
Norwegian Olympic Federation). However, the lowest effective sprinting intensity for stimulat-
ing adaptation is so far not established in the research literature. Recently, Haugen et al. [13]
observed that repeated 20-m sprints at 90% intensity did not enhance sprint performance dur-
ing a soccer season. It was suggested that such training should be performed at other times of
the season to avoid training-related constraints due to the high volume of overall soccer condi-
tioning. The aims of the present study were therefore to compare the effects of 1) training at 90
and 100% sprint velocity and 2) supervised versus unsupervised sprint training at 90% sprint
velocity on soccer-specific physical performance capacities in junior soccer players’ early in
pre-season.
Materials and Methods
Ethics statement
This study was conducted in accordance with the declaration of Helsinki. All participants pro-
vided written, voluntary informed consent before participation. Written parental consent was
also provided for participants < 18 yr old. The human subjects review committee of the Faculty
for Health and Sport, University of Agder, approved the study.
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Experimental approach to the problem
In this randomized controlled trial, participants were randomly assigned to four different treat-
ment conditions. A control group (CON) completed regular soccer training according to their
teams’ original early pre-season training plans. Three training groups performed a weekly re-
peated-sprint training session in addition to their regular soccer training sessions, which was
performed at A) 100% intensity without supervision (100UNSUP), B) 90% of maximal sprint
speed with supervision (90SUP) or C) 90% of maximal sprint speed without supervision
(90UNSUP). Based on sample size limitations and motor learning principles identified in the
introduction, the present study was not performed with a factorial design (i.e. an additional
“100SUP” group). The duration of the intervention period was 7 weeks. To evaluate the treat-
ment conditions (independent variables), the following soccer-specific performance tests (pri-
mary dependent variables) were assessed prior to and after the intervention period: 15x20 m
repeated-sprint, countermovement jump (CMJ) and Yo-Yo Intermittent Recovery 1 (Yo-Yo
IR1). To investigate possible mechanistic influences regarding adaptations to sprint training,
the following secondary dependent variables were assessed during the 15x20 m repeated-sprint
pre- and post-training tests: Heart rate, blood lactate concentration, step length and step rate.
Finally, sprint times for all training sessions were assessed for intensity control (90SUP and
90UNSUP) and to examine weekly changes in repeated-sprint performance (100UNSUP).
Participants
Fifty-two male junior soccer players, aged 16–19 years, volunteered to participate. The athletes
were playing in the highest junior division level for four different clubs (n = 6,13,16 and 17) in
Norway. Each participant had a minimum two years of soccer-specific conditioning experi-
ence. During the intervention period, the participants were requested to refrain from perform-
ing any other off-field physical training regimes in terms of speed, strength and/or endurance.
All participants were free of injuries prior to preliminary testing. None of the athletes had pre-
vious experience with specialized repeated-sprint training.
To eliminate the influence of varying overall soccer conditioning, the participants were ini-
tially distributed by club and then allocated to one of the four intervention conditions by a co-
author not directly involved in testing or the training intervention. The 14 participants ran-
domly assigned to each of the three training groups were required to complete at least six out
of seven training sessions during the intervention period in addition to all performance tests in
order to be included in further analyses. The 10 allocated CON participants were required to
perform at least 80% of planned sessions and complete all pre- and post-training tests. We
chose a slightly uneven distribution of subjects based on 1) the expectation of increased drop-
out risk generally observed in any intervention and 2) the expectation of lower variability of
outcome in CON exposed to testing only and an unchanged training routine.
One participant each from CON, 100UNSUP and 90SUP dropped out due to illness during
training or testing. Two participants from 90SUP and one from 90UNSUP dropped out due to
injuries sustained outside the sprint-training intervention. A final player from 90SUP group
dropped out due to Achilles tendon strain, possibly associated with the sprint intervention.
Thus, 45 of 52 participants completed the study with the following sample sizes (club distribu-
tion in brackets): CON = 9 (0,3,3,3), 100UNSUP = 13 (0,4,5,4), 90UNSUP = 13 (1,3,5,4) and
90SUP = 10 (2,3,3,2). Physical and training characteristics of these participants are presented
in Table 1.
Regular soccer training sessions typically commenced with warm-up activities like
short-passing and coordination exercises with the ball, followed by more intensive
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change-of-direction exercises with and without ball. The main part of the soccer practice con-
sisted of small-sided and more full-sized team compositions, ranging from 3 vs. 3 to 7 vs. 11.
Testing procedures
The pre- and post-training tests were conducted at the Norwegian Olympic Training Centre
on two separate days, with two days in between. All participants completed the tests in the
same order and at the same time of day. Regarding nutrition, hydration, sleep and physical ac-
tivity, the athletes were instructed to prepare as they would for a regular soccer match, includ-
ing no high-intensity training the last two days before testing. They were also instructed to use
identical footwear and kit for each of the tests. Test day one consisted of CMJ and 15x20 m re-
peated- sprint testing. On test day two, the athletes completed the Yo-Yo IR1 test. Prior to test-
ing on test-day 1, participants completed a 25 min standardized treadmill warm-up consisting
of a 10-min general warm-up at 60–75% of age-predicted maximum heart rate, 3 sets of 4 exer-
cise drills (high knees, back kick, sideway and backwards running) and finally 2–3 repetitions
of 40-m runs with a progressive increase in speed. Prior to testing on test-day 2, participants
warmed up with a 10-min easy jog at 60–75% of age-predicted heart rate followed by the initial
60–90 s of the Yo-Yo IR1 test.
CMJ test. Immediately after warm up, each athlete was weighed on a force platform for
system calibration before performing three trials of CMJ (vertical jump) separated by 1 min re-
covery. The best result for each player was retained for analysis. To isolate leg extensor muscles
and minimize technical elements, all jumps were performed with hands placed on the hips.
The tests were performed on an AMTI force platform (OR6–5–1, Watertown, USA). Calcula-
tion of jump height is formerly described in Haugen et al. [3].
Sprint test. A 15x20 m repeated-sprint test with starts each 60 s was performed directly
after the CMJ test. Distance and recovery were chosen in line with mean frequency and typical
distance of all-out sprints reported from match analyses [14]. Procedures and equipment are
formerly described in Haugen et al. [13]. Best 20-m time was used in order to determine maxi-
mal single-sprint capacity, while mean time for the 15 sprints was used to determine repeated-
sprint performance. Heart rate was measured continuously during the test (Polar RS400, Kem-
pele, Finland). A blood sample was acquired via finger stick to quantify the blood lactate
concentration (BLa-) immediately after the last sprint (LactatePro LT-1710, Arkay KDK,
Kyoto, Japan).
All sprint tests were captured by a video camera (Sony HDR-HC9E)) mounted on a tripod
in line with the finish line and 3 m from the sprinter’s running lane. Video recordings were
analysed in ProSuite, version 5.5 (Dartfish, Switzerland) to determine step count and derive av-
erage step length (SL). For precision, the digital ruler in the analyser window was used to
Table 1. Physical and training characteristics at inclusion.
Group
n
Age (yr)
BM (kg)
Height (cm)
Weekly training sessions
Games per week (n)
Tot. vol. (hwk-1)
CON
9
17 ±1
72 ±11
181 ±6
4.4 ±2.3
0.4 ±0.4
6.8 ±3.3
100UNSUP
13
17 ±1
66 ±9*
178 ±6
4.4 ±2.3
0.3 ±0.7
6.6 ±3.8
90UNSUP
13
17 ±1
72 ±6
183 ±5
4.5 ±2.4
0.4 ±1.0
7.0 ±3.5
90SUP
10
17 ±1
72 ±8
178 ±7
4.4 ±1.6
0.4 ±0.9
6.8 ±2.9
Values are mean ± SD. BM = Body mass, Tot. vol. = Total training volume. Training values are based on self-reported weekly averages during the
intervention period. There were no signiﬁcant differences among the groups for any of the variables, except for body mass (*100UNSUP < 90UNSUP,
p = 0.04).
doi:10.1371/journal.pone.0121827.t001
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interpolate the last step across the finish line. For example; if the 13th and 14th ground contact
occurred 0.8 m in front of and 1.2 m beyond the finish line, respectively, the recorded number
of steps was registered as 13.4. Mean SL was calculated by dividing the number of steps by the
distance (in this case: 20 m13.4–1 = 1.49 m). Mean step rate (SR) was calculated from mean ve-
locity and mean SL. Prior to the present study, this measurement method was validated by roll-
ing out thin paper at the finish line area in order to measure the distance between the visible
spike shoe marks from competitive sprinters. The absolute difference across twenty sprint
comparisons never exceeded 0.1 steps. Thus, the maximal margin of error for step counts over
20 m is 0.7–0.8% for athletes using 13–15 steps.
Yo-Yo IR1 test.
The Yo-Yo IR1 test was performed indoors on artificial turf. Two test
leaders supervised the tests. The athletes were divided in small groups that completed the test
consecutively, such that each supervisor was responsible for  5 athletes during the test. Set-up
and procedures were in line with the guidelines by Krustrup et al. [15], who have reported a
test-retest CV < 5%. The test score is reported in total distance covered until exhaustion.
Intervention program
The training intervention took place from the end of October to mid December, corresponding
to early pre-season in the Norwegian soccer annual cycle. The sprint-training sessions were
performed at the same time and day for each training group throughout the intervention peri-
od and no regular soccer training sessions were performed on the same day as the sprint train-
ing took place. Athletes in 100UNSUP performed 15x20 m maximal sprints with starts each
60 s once a week. Groups 90SUP and 90UNSUP performed one weekly training session con-
sisting of a larger dose of 30x20 m sprints at 90% of maximal sprint velocity (based on the best
20-m sprint time obtained during the pre-training test) with starts each 60 s.
Two sprint-training experts, with extensive national-level coaching experience, supervised
the 90SUP group during the intervention. Three key sprint-technical elements and correspond-
ing verbal instructions were emphasized during the training sessions:
• Optimal upper-body angle relative to the ground during the initial steps in order to create
higher horizontal propulsive forces through more effective utilization of hip and knee exten-
sors [16,17]. The athletes were instructed to assume a start position with forward lean in the
upper body and a lowered centre of gravity and to gradually become more upright through-
out the acceleration.
• Minimize horizontal braking forces [16]: Athletes with apparently too high braking forces
were encouraged to assume a more favourable configuration at the point of ground contact
with the foot plant closer to the perpendicular line from the centre of mass. This can be
achieved by hitting the ground with a bent knee (relevant during acceleration) or with the
centre of mass at a large vertical distance above the ground (relevant during maximal
sprinting).
• Produce a stiff rebound during ground contact in order to minimize degeneration of hori-
zontal propulsive forces [18–20]: Identified “heal runners” were encouraged to pre- activate
dorsiflexion muscles prior to foot plant and stiffen the ankle joint during ground contact, al-
lowing them to utilize the elasticity in the plantar flexors for greater force development.
These instructions were emphasized during the warm up drills.
After video analysis of the first training session, the two sprint-training experts prepared an
individual capacity profile for all participants in the 90SUP group. Each athlete was presented
with one technical task at a time, in accordance with general feedback principles [9]. Players
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with obvious technical limitations were provided with more verbal instructions than technical-
ly well-performing athletes.
In the absence of previously published studies, a 1:2 repetition ratio between 100% and 90%
sprinting was chosen. Several measurements were assessed in order to compare the two repeat-
ed-sprint training sessions used. Firstly, session rated perceived exertion (RPE) was recorded
for all athletes after the repeated sprints performed in pre-training testing and the first training
session. Written and verbal instructions regarding its use were provided in advance [21]. More-
over, heart rate was measured continuously during the first training session for all athletes who
ran at 90% sprint intensity, in addition to BLa- immediately after their last sprint. These were
compared to corresponding data assessed during pre-training tests. Mean SL and SR for the
first sprint-training session were calculated by identical procedures as for the pre- and post-
training tests. Finally, all training group athletes performed 3x20 m maximal sprints with starts
each 60 s 48 hours after the first training session for a performance recovery check. The mean
time for these three sprints was compared with corresponding sprints from the pre-
training test.
Electronic timing was continuously used to control running speed and adjust intensity ac-
cording to each player’s “target time”. Target time for the 90SUP and 90UNSUP participants
were derived from the best single-sprint time achieved during preliminary testing by multiply-
ing mean velocity over the 20-m distance by 0.9. No feedback other than sprint time informa-
tion (for intensity control purposes) was provided by a timekeeper for the 90UNSUP and
100UNSUP groups after each run. Fig. 1 shows intensity distribution for the two 90% groups
(90SUP and 90UNSUP pooled together) during all training sessions. More than 90% of all
sprints were completed with intensities between 87 and 93% of maximal sprint velocity. All
sprints for 100UNSUP during the training sessions were completed with an intensity > 97%
(mean ± SD: 98.2 ± 0.8%) when related to the best single-sprint within each training session.
Thus, treatment conditions in 90SUP and 90UNSUP were strictly separated and did not over-
lap with 100UNSUP. For simplicity, we continue to use the terms “100UNSUP” or “maximal
intensity”.
Statistical analysis
All statistical analyses were carried out using SPSS 17.0 for Windows (SPSS Inc., Chicago, IL,
USA). Level of significance was set to p<0.05. The General Linear Model with Repeated Mea-
sures followed by Bonferroni adjustment for multiple comparisons was used to examine re-
peated-sprint performance development (mean sprint time) for 100UNSUP across tests and
training sessions. The same model was used for 90SUP and 90UNSUP (both groups pooled
together) to compare effort-related variables in maximal and sub-maximal sprinting. Analy-
sis of covariance (ANCOVA) adjusting for the pre-training test value and randomization
stratification factor (club) was used to examine within-group and between-group mean
changes. The differences were judged by using estimated marginal means (EMM).
Bonferroni corrections were used to adjust p-values for multiple testing. Effect magnitudes
were calculated and interpreted categorically according to the guidelines by Hopkins et al.
[22]. The first 6 sprints from the pre-training test (for all included participants) were used to
calculate typical variation for sprint time, SL and SR. Effect size of the within-group changes
for mean sprint time were based on mean change and typical variation. The results are ex-
pressed as mean ±SD and 95% confidence intervals (95% CIs) were calculated for
all measures.
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Results
Table 2 shows effort-related variables for the two repeated-sprint training sessions used in the
present intervention. No differences in RPE were observed between the sessions. Mean sprint
time for the 3x20-m sprints performed 48 hours after the first training session was not signifi-
cantly different when compared to the corresponding pre-training sprint test. Sprinting at 90%
velocity was accompanied with reduced HR peak (17%; very large effect; p<0.001), BLa- (55%;
large effect; p<0.001) and SR (11%; very large effect; p<0.001) compared to maximal sprinting.
Fig 1. Intensity distribution for the sprint training groups during all training sessions. Best sprint from
pre-training testing was set as reference (100%) for 90SUP and 90UNSUP, while best sprint within each
training session was set as reference (100%) for 100UNSUP.
doi:10.1371/journal.pone.0121827.g001
Table 2. Effort-related variables in maximal (100%) and sub-maximal (90%) sprinting.
Sprint session
15x20m (100% intensity)
30x20m (90% intensity)
Δ sprint time 48 h (s)
0.00 ±0.02
0.01 ±0.02
Session RPE
3.8 ±1.2
4.0 ± 1.1
HR peak (beats min-1)
170 ±10
141 ±10*
BLa- (mmolL-1)
4.4 ±1.8
2.0 ±0.7*
SL (m)
1.55 ±0.08
1.56 ±0.09
SR (stepss-1)
4.36 ±0.18
3.87 ±0.22*
Δ sprint time 48 h = sprint time 48 hours after the ﬁrst training session minus corresponding pre-training
sprint test time (mean of ﬁrst 3 sprints for each time point), RPE = rated perceived exertion, HR peak = peak
heart rate, BLa- = blood lactate concentration, SL = step length, SR = step rate
* = signiﬁcantly different from 100% sprinting (p<0.001).
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No significant within-group differences for the analyzed performance parameters were ob-
served, except that 90SUP improved Yo-Yo IR1 performance from pre- to post-training (258
m; 17,3%; p<0.01). No significant between-group differences were observed (p<0.05). 90SUP
improved Yo-Yo IR1 performance by a moderate margin compared to all other groups, while
all other between-group differences were small or trivial (Table 3 and Fig. 2).
Achievement of best sprint performance was randomly distributed across the 15 sprints in
all groups during both pre- and post-training tests. Typical variation for sprint time, SL and SR
was 0.025 s (CV 1.0%), 0.028 m (CV 1.8%) and 0.08 stridess-1 (CV 1.9%), respectively. In
CON, a variation in mean sprint time of ±0.04 s was observed between the pre- and post-train-
ing tests. Corresponding variation for SL and SF was 0.06 m and 0.19 stridess-1, respectively.
In 100UNSUP, significant differences from pre- to post-training tests were observed for
BLa- (1.5 mmolL-1; 35.7%; p<0.001), SL (-0.04 m; 2.6%; p = 0.020) and SF (0.13 stepss-1;
3.0%; p = 0.019). BLa- increased significantly in 100UNSUP compared to CON from pre- to
post-training (p = 0.008) (Table 4). No other within- or between-group differences were
Table 3. Between-group changes (mean and 95% CIs) versus controls in physical performance from pre- to post-training.
Intervention group
Best sprint time (s)
Mean sprint time (s)
CMJ (cm)
Yo-Yo IR1 (m)
100UNSUP
-0.03 (-0.07 to 0.00)
-0.03 (-0.06 to 0.01)
1.0 (-0.6 to 2.6)
-34 (-272 to 205)
90UNSUP
-0.03 (-0.07 to 0.01)
-0.02 (-0.06 to 0.02)
0.4 (-1.3 to 2.1)
-1 (-120 to 117)
90SUP
-0.02 (-0.06 to 0.02)
-0.03 (-0.07 to 0.01)
1.8 (0.0 to 3.6)
131 (-108 to 369)
The differences vs. control group are assessed by estimated marginal mean. Minus (-) indicates lower values post-training compared with the control
group (assessed by estimated marginal means). CMJ = countermovement jump, Yo-Yo IR1 = Yo-Yo intermittent recovery level 1. No signiﬁcant between-
group differences were observed.
doi:10.1371/journal.pone.0121827.t003
Fig 2. Individual changes in 15x20 m mean sprint time from pre- to post-training tests.
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observed. The change in BLa- within 100UNSUP was moderate while the other effect magni-
tudes between- or within-groups were trivial or small.
Fig. 3 shows the development of repeated-sprint performance (mean sprint time) for
100UNSUP during the intervention period, including pre- and post-training tests. Weekly
changes in group mean values up to 0.05 s were observed.
Discussion
In the present study, weekly repeated-sprint training sessions performed at maximal or with
90% intensity were not sufficient to improve soccer-specific physical performance in junior
soccer players, when compared to a matched control group assumed to maintain a constant
training pattern. Moreover, no differences in performance outcomes were observed between
supervised and unsupervised sprint-training groups training at 90% maximal sprinting veloci-
ty. Apparently, the relative work loads elicited by the current intervention strategies were not
sufficient to create appropriate adaptations during the early pre-season soccer period.
To the authors’ knowledge, this is the first study to compare the effects of sprint training at
90 vs. 100% sprint intensity or supervised vs. unsupervised sprint training. Our findings con-
firm the assumption that sprint performance is resistant to training enhancement, even among
junior soccer players during the early pre-season period where total training load is reduced.
Since treatment allocation was adjusted for club participation, the current results were not
influenced by varying overall soccer conditioning across groups (Table 1). Age distribution was
consistent across groups (Table 1) and body mass did not change significantly in any of the
groups (Table 4). The moderate group sample sizes may mask possible significant outcomes.
However, based on the trivial to moderate effect magnitudes, our findings do not support a rec-
ommendation to perform the present training regimes under otherwise identical conditions.
Fig 3. 95% confidence intervals of mean sprint time for 100UNSUP during the intervention.
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Despite the absence of significant differences in the experimental training interventions, the
present study may outline directions for future related studies.
Effort matched sprint training
The two training sessions used were equally rated in terms of session RPE (Table 2). Further-
more, recovery status after two days was not different for the maximal and sub-maximal train-
ing groups. Based on these observations, we find it reasonable to conclude that the two
repeated-sprint training sessions were effort matched. Blood lactate values obtained after re-
peated sprints at 90% intensity were below what has been considered “lactate threshold intensi-
ty” (2.5–4.0 mmolL-1) in endurance training [23]. In contrast, repeated sprinting at maximal
intensity was accompanied with BLa- at or above the typical lactate threshold range described
for endurance athletes. Even though BLa- values obtained from sprint and endurance training
are not directly comparable, the present data suggest metabolic pathway partitioning differ-
ences between 90% and maximal sprinting. Small but meaningful differences in muscle recruit-
ment cannot be excluded as contributory to the observed increase in lactate accumulation at
maximal sprinting.
Effects of training at maximal and sub-maximal intensity
The present results revealed only trivial and non-significant changes in soccer-related sprinting
from pre- to post-training for 100UNSUP (Table 3, Fig. 2). Previously, Tønnessen et al. [24]
observed unaltered sprint velocity over 0–20 m sprint and improved velocity over 20–40 m as a
result of weekly repeated 40-m sprints at maximal or near maximal intensity. This suggests
that players are more disposed to adaptations over somewhat longer but less soccer-specific
sprint distances. Soccer players perform a high number of brief accelerations during training
and games [14]. Thus, one could argue that most players have likely maximized their 0–20 m
sprint (acceleration) potential during regular soccer conditioning. While sprint performance
remained unchanged in 100UNSUP (Table 3), SL and SR changed significantly from pre- to
post-training (Table 4). These changes were greater than the observed typical variation. Our
findings are somewhat in contrast to previously published studies stating that individual
achievement of sprint velocity corresponds to an optimal self-selected step length/step rate
ratio [25] and that a different ratio will produce a lower velocity, so-called negative interaction
[26]. In the present study, maximal sprint training induced a significant shift in the step
length/frequency relationship “selected” by the athletes, with step frequency increasing 3%
from 4.33 to 4.46 steps.s-1 and step length declining correspondingly. These changes cannot be
ascribed to supervision as this group did not receive sprint technique feedback or instruction.
Moreover, 100UNSUP demonstrated an increase in BLa- after 15x20 m maximal sprinting in
the post-training test, suggesting possible changes in anaerobic energy release, buffering
Table 4. Between group changes (mean and 95% CIs) versus controls for underlying performance variables between pre- and post-training.
Intervention group
Body mass (kg)
HRpeak (beatsmin-1)
BLa- (mmolL-1)
SL (m)
SR (stepss-1)
100UNSUP
0.3 (-0.8 to 1.5)
5 (-1 to 12)
1.9 (0.7 to 3.2)*
0.00 (-0.07 to 0.06)
0.06 (-0.13 to 0.25)
90UNSUP
-0.3 (-1.4 to 0.8)
2 (-5 to 8)
1.1 (-0.1 to 2.3)
0.04 (-0.02 to 0.10)
-0.09 (-0.28 to 0.10)
90SUP
-0.3 (-1.5 to 0.9)
4 (-3 to 11)
1.5 (0.2 to 2.9)
0.03 (-0.03 to 0.10)
-0.04 (-0.24 to 0.17)
The differences vs. control group are assessed by estimated marginal mean. Minus (-) indicates lower values post-training compared with the control
group (assessed by estimated marginal means). HR = heart rate, BLa- = blood lactate concentration, SL = step length, SR = step rate
* = signiﬁcantly different (Bonferroni adjusted) from CON (p = 0.01).
doi:10.1371/journal.pone.0121827.t004
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characteristics or muscle recruitment pattern. However, these possible physiological changes
were not accompanied with enhanced performance.
Based on both current and previous findings [13], it cannot be concluded that weekly train-
ing at 90% velocity is a sufficient sprinting intensity for stimulating adaptation over short
sprint distances. Blood lactate and peak heart rate values observed in the present junior soccer
players indicate relatively low metabolic stress (Table 2). It is possible that sub-maximal sprint
training is more appropriate for typical competitive athletics sprinting distances (100–200 m)
compared to 0–20 m accelerations. 20-m sprints are comprised of high to maximal acceleration
from a resting state and continuing through the timed distance. In this condition, energy de-
mands during the acceleration phase greatly exceed those at peak velocity [17]. The change in
kinetic energy (½mv2) is proportional to the square of the change in velocity, such that the
90% sprint condition is associated with a nearly 20% reduction in kinetic energy change (and
presumably, muscular energetic demand) compared to maximal sprinting velocity. Due to this
non-linearity, a 5% reduction in short sprint velocity during repeated-sprint training over
short distances would correspond to 90% workloads in strength training and endurance train-
ing and might give a more optimal balance of stress, injury risk reduction and adaptive signal
retention. This possibility remains to be explored.
Effects of supervised training
The present study revealed no significant training effects when supervised and unsupervised
sprint training at 90% sprint velocity were compared (Table 3 and Fig. 2). However, the 90SUP
group improved Yo-Yo IR1 performance by a moderate margin compared to the other groups.
Since Haugen et al. [13] reported unchanged VO2 max after seven weeks of repeated-sprint
training at 90% intensity, it is reasonable to assume that locomotion efficiency during high-in-
tensity running has improved in 90SUP. The lack of effects on maximal and repeated-sprint
performance may have been affected by the possibility that sprint training at 90% sprint speed
is below the lowest effective sprinting intensity for stimulating adaptation. Future studies
should therefore explore the effect of supervised training with a gradual increase in intensity
from sub-maximal to maximal sprint velocity. Another argument for such a gradual increase
in velocity also becomes relevant if one assumes that the athletes gradually enhance sprint per-
formance over the training period. We chose not to control and adjust for possible sprint per-
formance enhancement in 90SUP and 90UNSUP throughout the present intervention period
to avoid a mix of different treatment conditions.
Theoretically, the lack of effects with supervised sprint training may be due to poor coaching
quality such that the athletes were not able to translate the instructions into practice. However,
both training experts used in the present study had many years of experience coaching athletics
performers on both national and international levels. Mazzetti et al. [7] and Coutts et al. [8]
showed that the presence of a training expert was beneficial for maximal strength and power
development over time. In contrast to the present study, the training experts in those studies
were allowed to adjust the total training load during the interventions. Based on these observa-
tions, one could argue that the effect of expert supervision during training is optimized when
combined with greater flexibility in the day-to-day training prescription.
Training-related constraints
Common challenges in applied studies of this nature are related to constraints with overall
team conditioning [1,13,27]. Current analyses confirm these constraints, even though the
study was conducted early pre-season where total training load is typically reduced. In CON,
we observed ±0.04 s absolute individual variation in mean sprint time between pre- and post-
Repeated-Sprint Training in Soccer Players
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training tests. More importantly, weekly changes in group mean values up to 0.05 s (nearly 2%)
were observed in 100UNSUP (Fig. 3), despite consistent frequency and volume of games and
training sessions during the intervention period (Table 1). This weekly or seasonal variation is
considerably higher than the observed typical variability. The present findings emphasize the
need for more detailed information about overall conditioning load, accepting that soccer-spe-
cific movements (i.e. brief accelerations, high sprinting velocities or changes of directions) are
impossible to assess accurately in groups of players with current technology [28,29]. In princi-
ple, the present study could have been accomplished in a more controlled experimental envi-
ronment, omitting the concurrent soccer training. However, such an approach severely limits
the external validity. If improvement of sprinting performance is the primary goal for certain
players, future studies should explore the effects of more frequent sprint-training sessions and
longer intervention periods, perhaps in combination with other training forms. Future studies
should also explore whether it is more effective to structure the players’ weekly soccer training
rather than introducing an additional physical conditioning regime. A theoretically perfect
conditioning program for certain capabilities may limit other important qualities and vice
versa. Coaches and conditioning experts have to balance their training methods and exercises
in order to optimize different skills in relation to their contribution to overall soccer perfor-
mance. Based on the varying individual responses to each of the performed treatments (Fig. 2)
and the absence of evidence supporting the choice of specific training methods at the group
level, it is essential to diagnose each individual and develop training interventions that target
their key physiological and technical weaknesses.
Author Contributions
Conceived and designed the experiments: TH ET ØØ FLH EE SS. Performed the experiments:
TH ET ØØ FLH EE GP. Analyzed the data: TH ET ØØ FLH GP SS. Contributed reagents/ma-
terials/analysis tools: TH ET GP EE SS. Wrote the paper: TH ET ØØ FLH GP EE SS.
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Sprint conditioning of junior soccer players: effects of training intensity and technique supervision.
Haugen, Thomas,Tønnessen, Espen,Øksenholt, Øyvind,Haugen, Fredrik Lie,Paulsen, Gøran,Enoksen, Eystein,Seiler, Stephen