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Effect of Training Intensity Distribution on Aerobic Fitness Variables in Elite Soccer Players: A Case Study

Castagna, Carlo1; Impellizzeri, Franco M2; Chaouachi, Anis3; Bordon, Claudio4; Manzi, Vincenzo1

Journal of Strength and Conditioning Research: January 2011 - Volume 25 - Issue 1 - p 66-71
doi: 10.1519/JSC.0b013e3181fef3d3
Orginal Research

Castagna, C, Impellizzeri, FM, Chaouachi, A, Bordon, C, and Manzi, V. Effect of training intensity distribution on aerobic fitness variables in elite soccer players: A case study. J Strength Cond Res 25(1): 66-71, 2011-The aim of this article was to quantify the distribution of training intensities and its effect on aerobic fitness in professional elite soccer players. Fourteen professional soccer players were observed during the prechampionship training period (6 weeks). Treadmill running speed and heart rates (HRs) at 2 and 4 mmol·L−1 blood-lactate concentrations were assessed pre and posttraining. Training intensities were categorized using 3 HR zones: low intensity (<HR 2 mmol·L−1), moderate intensity (between HR 2 and 4 mmol·L−1), and high intensity (>HR 4 mmol·L−1). Analysis of the 504 individual training sessions showed that 73 ± 2.5, 19 ± 2.8, and 8 ± 1.4% of the total training time was spent at low, moderate, and high intensity, respectively (p < 0.001). Speed at 2 and 4 mmol·L−1 significantly improved posttraining (5 and 7%, respectively, p < 0.01). Training spent at high intensity was significantly related to relative speed improvements at 2 mmol·L−1 (r = 0.84, p < 0.001;) and 4 mmol·L−1 (r = 0.65, p = 0.001). Players spent almost two-thirds of their training time at low intensities. However, only the time spent at high intensity (>90% of maximal HR) was related to changes in aerobic fitness. These results support the usefulness of the quantification of aerobic training load using HR. Furthermore, it stresses the effectiveness of the high-intensity training in soccer.

1School of Sport and Exercise Sciences, Team-Sports Department, Faculty of Medicine and Surgery, University of Rome Tor Vergata, Rome, Italy; 2Department of Research and Development, Schülthess Klinik, Zürich, Switzerland; 3Research laboratory: Sports Performance Optimization, National Center of Medicine and Science in Sports (CNMSS), Tunis, Tunisia; and 4Palermo Football Club, Palermo, Italy

Address correspondence to Carlo Castagna,

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During soccer, the aerobic pathway is heavily stressed (30). Indeed in a competitive match, players' mean exercise intensity locates in the range of 80-90% of maximal heart rate (HRmax) corresponding to 70-80% of the maximal oxygen uptake (V̇O2max) (30). Despite the intermittent nature of soccer, it is considered that during a 90-minute game, elite-level players run about 10-12 km at an average intensity close to the anaerobic threshold (80-90% of HRmax) (30).

Descriptive studies showed that aerobic fitness (24) assumed as V̇O2max and anaerobic threshold may discriminate between players of different competitive levels and consequently parallel success considered as participation in higher national professional soccer leagues (30,32). Additionally, training studies showed that improvement in aerobic fitness may positively affect match physical and technical performance in soccer players of different competitive levels (10,14,16,26). For these reasons, soccer training programs should include aerobic conditioning as an important part of the seasonal training plan (13).

Descriptive studies have analyzed the training intensity distribution in elite endurance athletes showing population specific patterns in intensity distribution during the preparation phase (8,9,20,22,28). Differently from endurance sports where training prescription is mainly individual, team-sport athletes usually train in groups (6,14,25), and consequently players' physiological responses to training load (TL) may present remarkable interindividual variations (21,29). Unfortunately, no information is available about the actual TL experienced by elite professional soccer players during the competitive season (15). Additionally, several short-term experimental training interventions for aerobic fitness development resulted in being successful in soccer (4,10,14). However, no information is currently available concerning the effectiveness of nonexperimentally controlled training in professional elite soccer players (30,31).

The relevance of quantifying the TL in soccer using HR methods can be evaluated by examining the relation between training intensity (e.g., time spent at HR in selected intensity zones) and training outcomes (e.g., submaximal aerobic fitness variables such as speeds at selected blood-lactate concentrations) (9). Otherwise, the appropriateness of controlling and modulating TL in soccer using HR can be questionable. Unfortunately, no information about this topic is currently available in the soccer-related international literature (30).

The aim of this study was to examine the training intensity distribution as quantified using the HR in professional outfield soccer players during the early phase of the competitive season. Furthermore, to establish the efficacy of the quantification of TL using HR in soccer players, we examined the relation between the time spent in different intensity zones and aerobic fitness as measured using standard laboratory tests.

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Experimental Approach to the Problem

The observational study covered the first stage of the training periodization of the upcoming competitive season because in this period mainly conditioning training sessions are implemented to professional first division soccer teams. The TL was assessed monitoring exercise HRs experienced by the outfield players during the preparation phase (6 weeks) of the competitive season (8,28). Because of the observational nature of the study, no training intervention or advice were provided by the authors of this research.

Training intensity was quantified using 3 HR intensity zones based on the result of submaximal treadmill testing (28). This testing procedure was used because a number of soccer studies reported greater sensitivity of submaximal aerobic fitness variables in tracking seasonal changes in endurance than in V̇O2max (7,14,23,30). Furthermore, enhancements in submaximal aerobic fitness variables were reported to positively affect match physical performance in soccer players (10,14).

As physiological anchors were considered the HR attained at selected blood-lactate concentrations (i.e., 2 and 4 mmol·L−1) (28). Training HR was categorized as low intensity (<HR at 2 mmol·L−1), medium intensity (between HR at 2 and 4 mmol·L−1), and high intensity (>HR at 4 mmol·L−1). The HRs were recorded throughout the preparation phase, and a total of 36 training sessions were monitored (i.e., 6 sessions per week). Quantification of training intensity was established analyzing the distribution pattern of players' time spent in each of 3 physiologically based HR zones (9,28).

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In this study, we examined the training profile of an Italian premier league (serie A) soccer team (Palermo Calcio, n = 14). Fourteen professional soccer players (age 25 ± 4 years, height 178 ± 7 cm, body mass 74 ± 8 kg, serie A experience 2-6 years) volunteered to participate in this study. This study was conducted in conformance with the Human and Animal Experimentation Policy Statements of the American College of Sports Medicine. Written informed consent was received from all players after verbal and written explanation of the experimental design and potential risks of the study. Information was presented at the time of consent in a way that was easily understood by the subjects and provided in a language in which the subjects are fluent. As a result, a fair explanation of the procedures to be followed and their purposes, identification of any procedures that were experimental, and description of any and all risks attendant to the procedures was provided to each player who voluntarily accepted to participate after prior familiarization with the testing procedures. Informed consent was obtained from each of the participants only after familiarization with the procedures used in this study (i.e., submaximal practice of the field tests). To improve this study, internal validity players were blinded to the work hypothesis informing the aims of this observational study. All players agreed to provide their maximum will effort to perform at their best during all the field tests and training sessions considered in this study. Before familiarization, each player was written and verbally made aware that they were free to withdraw from the study without any penalty for an upcoming reason(s). The study protocol was approved by the local Institutional Review Board before the commencement of this study.

During the 4 weeks preceding the study, players abstained from heavy and supervised training (postchampionship break). Furthermore, to avoid potential confounding effects of prior exercise fatigue on the outcome variables, coaches were asked to ensure that their players refrained from heavy training the day preceding assessments. A record of the nutrient content was taken to provide the sufficient carbohydrate intake during the week before assessments. Throughout the study, all testing and training sessions took place at the same time of the day (between 16.00 and 18.00 hours) to avoid circadian influences. The studied players were all starters, and the examined team ranked fifth at the end of this study competitive championship (18 teams). During the last part of the preceding competitive season, all players reported compliance to a similar training routine that consisted of 80-90 and 10-20% of aerobic-anaerobic and strength-sprint-agility training, respectively.

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Players performed a 2-phase progressive treadmill test (Technogym Run Race 1400 HC, Gambettola, Italy) for the assessment of individual blood-lactate concentration profiles and maximal HR, respectively, on 2 occasions (at the start and after 6 weeks of training). The progressive treadmill test consisted of 4-5 submaximal exercise bouts at initial running speed of 9 km·h−1 followed by a maximal incremental test to volitional fatigue. The treadmill running velocity was increased during the submaximal test by 1 km·h−1 every 5 minutes. Once capillary blood-lactate concentrations were elevated above 4 mmol·L−1, the treadmill speed was increased by 0.5 km·h−1 every 30 seconds until exhaustion (14,18). Capillary blood samples (25 μL) were taken from the earlobe immediately after each submaximal bouts and 3 minutes after exhaustion and analyzed to assess exercise blood-lactate concentrations using an electroenzymatic technique (YSI 1500 Sport, Yellow Springs Instruments, Yellow Springs, OH, USA).

Before each test, the analyzer was calibrated following the instructions of the manufacturer using standard lactate solutions of 0, 5, 15, and 30 mmol·L−1. Heart rates were recorded every 5 seconds with a short-range telemetry system (Polar Team System, Polar Electro Oy, Kempele, Finland) during all assessments. The highest HR measured during the maximal incremental test was used as maximum reference value (HRmax) (3). Individual blood-lactate concentration vs. running speed profiles were obtained in each subject, and as exercise paradigm speeds at 2 and 4 mmol·L−1 were used (12,19). Blood-lactate concentrations were plotted against running speeds and HR elevation, and individual blood-lactate concentration profiles (speed at 2 and 4 mmol·L−1 and HR at 2.0 and 4 mmol·L−1) were identified via exponential interpolation (2).

Submaximal aerobic fitness assessment was performed at the beginning and at the end of the 6 weeks' training phase corresponding to the prechampionship preparation phase. Postpreparation phase tests were performed at least 2 days apart of the last training session to avoid cumulative fatigue between tests and training. The training schedule followed by players represented the typical training program performed by elite soccer players aiming to develop fitness and technical and tactical aspects of the game before the competitive season. No external support was provided to team coaches and fitness trainers after the starting fitness assessment. During the observational study, players performed aerobic training sessions using ball drills (1,25). Strength training sessions were provided in the form of circuit training using 80-90% 1RM loads to stress upper and lower limb strength and power development. Sprint and agility training was performed in the form of 10- to 30-m sprints (i.e., 2 times per week and always before the beginning of the aerobic sessions. The ratio between time devoted to anaerobic and aerobic based training (i.e., strength training and sprint training) was approximately 1:10. Only aerobic fitness and tactical skill development training sessions were monitored in this study. In all, 504 individual training sessions were monitored and used for calculations (average duration 90 ± 10 minutes). During all the training sessions, the HR was recorded in each subject, and to avoid missing data, HRs were downloaded immediately at the end of each training session on a computer and analyzed using specific software (Polar ProTrainer 5) and an electronic spreadsheet (Microsoft Excel, USA). To check for possible HR monitor malfunction (i.e., inability to record HR during exercise), the sport scientists supervising (n = 3) the data collection procedures checked Polar Team-System recording with HR displayers (Polar 610, Polar Electro Oy) during all the training sessions. Additionally, supervisors were available all the time to fix HR chest bands or to immediately substitute them. The HR monitor bands batteries were recharged every day, and only fully operating systems were used on each occasion. Consistency of HR records was checked using 2 systems (see above) at the same time during training and in rest conditions. No missing data occurred during this study because of compliance to the manufacturer's guidelines, proper device care, and passionate collaboration of all players involved.

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Statistical Analyses

The results are expressed as mean ± SDs and 95% confidence intervals (95% CIs). Normality assumption was verified using the Shapiro-Wilk W test, and Pearson's correlation coefficients were used to examine correlations between variables. Magnitude of effects was qualitatively assessed according to Hopkins (11) as follows: trivial r < 0.1, small 0.1 < r < 0.3, moderate 0.3 < r < 0.5, large 0.5 < r < 0.7, very large 0.7 < r < 0.9, nearly perfect r > 0.9, and perfect r = 1. Correlation effect sizes (ESs) were assessed with coefficient of determination (r2).

The ES was calculated to assess the meaningfulness of differences (5). The ESs of above 0.8, between 0.8 and 0.5, between 0.5 and 0.2, and <0.2 were considered as large, moderate, small, and trivial, respectively.

Student's paired t test was used to determine any significant difference in physiological variables before and after training. Differences between training intensity zones were detected using 1-way (between-group design) analysis of variance with Bonferroni post hoc test. As null hypothesis (H0) was assumed no difference between the 3 considered training HR zones (H0: low-intensity = medium-intensity = high-intensity HR time). Homogeneity of variance was tested with the Bartlett test. Significance was set at 5% (p ≤ 0.05). The intraclass correlation coefficient for the fitness measurements ranged between 0.89 and 0.92 in a preliminary quality control performed before the commencement of the study with a population similar to this study (i.e., semiprofessional soccer players, n = 16).

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Analysis of the 504 individual training sessions showed that soccer players exercised for 73 ± 2.5 (1,528 ± 92 minutes), 19 ± 2.8 (406 ± 64 minutes), and 8 ± 1.4% (165 ± 27 minutes) of the total training time at low, medium, and high intensity, respectively (p < 0.001). Heart rates at 2 and 4 mmol·L−1 were 81.5 ± 2.6 and 90.2 ± 2.1% of HRmax, respectively. The speeds corresponding to the 2 mmol·L−1 lactate threshold were 10.9 ± 0.6 and 11.4 ± 0.5 km·h−1 at pre and posttraining, respectively (p < 0.001; ES = 0.21). Pre and posttraining speeds at 4 mmol·L−1 were 13.0 ± 0.8 and 13.9 ± 0.4 km·h−1, respectively (p < 0.01; ES = 0.00). The training time spent at high intensity showed significantly large and very large relationships (Figures 1 and 2), with the relative improvement in speed at 2 mmol·L−1 (r = 0.84, 95%CI 0.55-0.95; p < 0.001) and 4 mmol·L−1 (r = 0.65, 95% CI 0.20-0.80; p = 0.001), respectively.

Figure 1

Figure 1

Figure 2

Figure 2

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The first aim of this study was to quantify the distribution of training intensity in a team of elite professional soccer players in real setting. To achieve this, HR responses to daily training sessions (9,28) were monitored during the most intense period of conditioning training of the season (prechampionship preparation phase) (15). The main finding of this observational study was that elite professional soccer players adopt a remarkable differentiation of training intensity in the preparation phase of the competitive season. Specifically, professional soccer players spent 73, 19, and 8% of their total training time at low, medium, and high intensities, respectively.

Similarly to the present study, 2 recent investigations have examined the training intensity profile of elite crosscountry skiers and subelite endurance runners during the early phases of the preparation period of the competitive season (9,28). In these studies, the intensity zones were defined according the first and second ventilatory thresholds (VTs): low intensity (<VT1), moderate intensity (>VT1 and < VT2), and high intensity (>VT2). The resulting profiles of this descriptive studies showed the existence of a polarized distribution of training intensities in well-trained endurance athletes (9,28). Specifically in the study of Seiler and Kjerland (28), junior elite crosscountry skiers spent about 91% of their training time running at low intensity (i.e., VT1, HR ≤ 2 mmol·L−1). The remaining 6.4 and 2.6% of the training time was spent at moderate and high intensities, respectively. Analyzing the training responses of subelite endurance runners (5- to 10-km racers) Esteve-Lanao et al. (9) showed that over a prolonged preparation period (i.e., a 6-month macrocycle), 71% of the total training time was spent at low intensity, 21% at moderate intensity, and 8% at high intensity. The training intensity distribution reported by Esteve-Lanao et al. (9) resulted in being quite dissimilar from the figures reported in crosscountry skiers, showing that different training strategies may take place in endurance sports. However, the reported difference in intensity distribution profiles may be partly because of the different observational period used in those studies (i.e., 6 months vs. 32 days) and the dissimilar training aim of the periods of the season examined.

The training intensity profile found in this study was similar to that reported in endurance runners training for race distances that ranged from 5 to 10 km in an observational (9) and experimental study (8). In the latter study was examined the impact of intensity distribution on endurance performance in 2 intervention groups that differed for time spent at low and moderate training intensities (8). Results showed that over a 5 months' macrocycle, low-intensity training volume exerted a superior effect on endurance performance compared to training characterized by more time spent at moderate intensity. These findings were similar to that reported by the same research group in a precedent descriptive study (9) showing that low-intensity training is a spontaneously chosen and performance enhancing training strategy in subelite endurance runners. The figure so far depicted for endurance runners contrasts with this study findings that reported an exclusive positive effect of high-intensity training time over aerobic fitness in elite soccer players. This is in line with several studies that showed that with experimental training interventions aerobic fitness was significantly improved, training junior soccer players at intensities in the range of the 90-95% of the individual HRmax (4,10,14). Consequently, it could be suggested that soccer players may benefit more from high-intensity training (17) than endurance athletes for the improvement of aerobic-fitness components (24). Anyway, differences in absolute training (i.e., minutes spent in each intensity zone) time should be considered when addressing this issue.

Interestingly, despite remarkable differences in absolute training time spent at low and moderate intensities, no dissimilarities were apparent in the high-intensity domain across the sport disciplines when expressed as percent of total training time (8,9,28). Indeed the high-intensity TL accounted for just the 8% of the total training time in the different training conditions. Interestingly, this figure overlaps with the finding of this study that reported that only 8% of the total training time was performed at intensities ≥90% of the HRmax. The competitive construct being similar across the different sport disciplines (i.e., national and international level), it could be speculated that probably this is the amount (i.e., 8% of total training time) of high-intensity exercise (i.e., HR ≥ 90% of HRmax) that can be safely tolerated by elite and subelite well-trained athletes when training (8,9,28). Because of the importance of the issue at hand for the optimization of the endurance training process, further studies are warranted.

A secondary aim of this study was to examine the relation between the time spent in the different intensity zones and the improvement in aerobic fitness. We found a significant association (i.e., very large to large, r2 from 0.71 to 0.42) between the high-intensity training and changes in speed at 2 and 4 mmol·L−1 lactate thresholds. In contrast, the time spent at low and moderate intensity was not related to changes in aerobic fitness. These findings are similar to that reported by Impellizzeri et al. (17) who found a significant correlation (r = 0.55, p < 0.05) between time spent in high-intensity zones and changes in oxygen uptake at 4 mmol·L−1 lactate threshold. This study results support the validity of the quantification of exercise intensity using HR and therefore its usefulness in the optimization of soccer training (14). This study also showed the existence of a dose-response relation, with greater improvement in aerobic fitness achieved with a greater amount of high-intensity training. These results confirmed previous studies showing the effectiveness of high-intensity training in soccer players (10,14).

In this study, the progression of aerobic fitness was assessed by monitoring changes of speeds at selected blood-lactate concentrations at the end of the precompetitive season mesocycle. The submaximal test used in this study is similar to that reported in the soccer-related literature that showed greater sensitivity of submaximal aerobic fitness variables in tracking seasonal changes in endurance compared to V̇O2max (7,14,23,30). In light of this and other study results, the applicability of submaximal aerobic testing in a professional soccer environment is warranted. Specifically, the submaximal running test revealed sensitive in tracking short-term fitness changes not requiring all-out or maximal effort. The latter feature may be considered as an added value for using submaximal tests during the preparatory and competitive season in professional soccer (27).

The main limitation of this study is the use of a convenience sample (i.e., a professional soccer team), and consequently, this investigation should be regarded as a case study. Therefore, conclusive inferences about the precompetitive season training intensity profile used by elite professional soccer players should be drawn studying larger randomized cohorts of players.

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Practical Applications

The findings of this study showed that submaximal aerobic fitness was positively affected by the amount of high-intensity exercise accumulated during training. Specifically, the time spent at HR >90% of HRmax affected speed attained at selected blood-lactate concentrations. In light of the results of this study, aerobic fitness should be stressed implementing exercise drills contemplating high-intensity phases (i.e., HR ≥ 90% HRmax) that will at least constitute 8% of the total weekly training plan of elite soccer players.

Given the diversity of training responses that may be expected in soccer because of group specific vs. generic training, the importance of monitoring training intensity is warranted (14). In this regard, this study provided supporting evidence for the use of HR to assess the individual responses to training in soccer players. Consequently, HR monitoring can be considered as an appropriate tool to quantify and modulating the individual TL in soccer players at the professional level.

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This research did not receive any financial support. The authors declare no conflict of interest.

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association football; exercise intensity; lactate threshold; team sports

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