Training adaptations are the result of the interplay of a number of structured physiological perturbations imposed on athletes during the training process (6,18,19). The individual responses to training are related to athletes' individual fitness level and proportional to the magnitude of the provided training load (TL) (21). As a result, the quantification of the individual response to a given TL is vital to profile training-related adaptive processes (17,22).
Recently, a number of studies have examined the individual training responses using heart rate (HR)–based methods (6,17–19,22). Manzi et al. (17) showed that with a fully individualized approach, it was possible to accurately track fitness improvements during mainly aerobic-training sessions in endurance athletes.
In team sports, players are mainly submitted to group training sessions aiming to develop team physical fitness and technical-tactical skills (18). The potential for differentiated training responses from scheduled team training sessions may significantly challenge the assumed importance of training individualization, considered as favorable criteria to ensure optimal performance development in team sports (18).
Training individualization assumes prominent importance in elite sports, and its interest is magnified in the team-sports domain as a consequence of the supposed remarkable interindividual responses (6,18,20). Recently, Stagno et al. (22) using a semiindividualized approach to describe individual training response, examined the adaptive profile of elite field-hockey players. The results of this study evidenced the existence of a dose-response relationship between internal load and aerobic-fitness variables. Unfortunately, the information provided in the Stagno et al. (22) study did not consider criterion-performance variables, and consequently, the relationship between TL and specific fitness was not provided.
Despite the interest of precise profiling of individual responses to training, no study was carried out using fully individualized approaches in professional team-sport players (19). The possible relationship between fully individualized TL and generic and specific fitness would be of interest for team-sport scientific coaching development.
Participation in professional soccer requires a complex interaction of physical and cognitive attributes to pursue competitive success during the season (20). The ergonomics model of professional soccer is competition oriented with the temporal sequence of matches during the season being the main affecting variable in the model (20).
Moreover, the seasonal volume of match involvements is proportional to competitive level with premiership standard being more demanding than lower-standard championships (23). Because of the reported competitive high fixture rate and the associated economical and nominal match importance, premiership players are submitted to unique training and competitive demands (20,23). Given that an accurate evaluation of the individual response to TL is vital in optimizing the ergonometric model in premiership soccer players. Despite the importance of this issue, no information is available on internal load and adaptive responses in premiership soccer players.
Therefore, the aim of this study was to examine the relationship between internal load and generic and specific variables of aerobic fitness in male premiership soccer players using a fully individualized TL approach. The likelihood of association between individual responses to training and aerobic-fitness variables enhancement was assumed as work hypothesis.
Experimental Approach to the Problem
In this study, a descriptive ex post facto design was used. Specifically, a team of elite-standard soccer players participating in the Italian Premier Division championship (series A) was followed during the 2010–2011 preseason (i.e., 8 weeks). The players were monitored for individual training responses using the Manzi et al. (19) individualized training impulse (TRIMPi) during each preseason training session (n = 900). As variables representing aerobic fitness were assumed maximal aerobic-power (V[Combining Dot Above]O2max), speed at 4 mmol·L−1 blood-lactate concentration (S4) and the V[Combining Dot Above]O2 at ventilatory threshold (V[Combining Dot Above]O2VT).
The V[Combining Dot Above]O2max was reported to be a sensible measure of aerobic fitness in soccer players during the early stages of the competitive season (14). Furthermore, descriptive studies (i.e., correlation and known groups cross-sectional studies) showed significant relationship between individual V[Combining Dot Above]O2max values and match activities variables and team V[Combining Dot Above]O2max and competitive levels (23).
Speed at selected lactate thresholds was reported for ecological validity in professional soccer (23). Furthermore, submaximal aerobic-fitness variables showed to be sensible to seasonal generic and specific training interventions in male soccer (6,14).
Recently Castagna et al. (6) reported that speed at 2 and 4 mmol·L−1 were sensible to variations in TL in male premiership soccer players. Specifically, the improvements in the considered variables representing submaximal aerobic fitness were related to time spent at high-intensity during training (6).
The Yo-Yo intermittent recovery test level 1 (Yo-Yo IR1) showed construct (i.e., high-intensity activity) convergent validity in soccer (2). Given that the Yo-Yo IR1 was assumed as match-performance criterion for this study (i.e., specific aerobic performance). This was done with the aim to evaluate the preparedness of the players to cope with game demands during the observed period.
The testing procedures took place during the first week of training after the end of the summer break and during the week preceding the first Serie A Championship match (i.e., during the ninth training week). The magnitude of internal load was assessed using the TRIMPi method to guide training intensity and recovery. This was done with the aim to avoid undue states of nonfunctional overreaching. The testing procedures took place on 3 separate occasions (i.e., 48 hours apart) across the testing week with a randomized assessment order to avoid effect of test sequence on test outcomes. During training and testing session, hydration was promoted allowing ad libitum fluids assumption. Testing procedures were carried out at the same hours of the day (i.e., 3–6 PM) to account for circadian effect on physical performance. The players were maintained on a high carbohydrate diet during the days preceding the testing and during training and competition days.
Eighteen (age 28.4 ± 3.2 years, height 182 ± 5.3 cm, body mass 79.9 ± 5.5 kg) professional Italian Serie A Soccer players (6 defenders, 6 midfielders, and 6 forwards) volunteered to this study. The players had at least 7 years of competitive experience in premiership. All the players were active members of the same Serie A team during the 2010–2011 season. Ten players were starters of their own country national A team.
The players trained 7 times a week throughout the preseason with a cup or championship match played in the weekend and a friendly match played on Thursday. Training sessions were mainly devoted to technical-tactical skill development with fitness training sessions performed as single training sessions during preseason. The training time during the observed period was 15 and 13% devoted to ball drills and generic aerobic training, respectively. The 21 and 8% of the training time was spent training for technical-tactical skill development and matches, respectively. Mainly anaerobic training (strength and sprint training) accounted for 14% of all the training time. The remaining time (29%) was spent with warm-up routines.
Written informed consent was obtained from the players before the commencement of the study and after local Institutional Research Board research design approval.
The players on separate occasions (48 hours apart) were submitted to 2 treadmill tests for blood-lactate concentration profiling and maximal HR (HRmax), and V[Combining Dot Above]O2max assessment. The individual Lactate profiles were assessed according to the procedures suggested by Manzi et al. (19). Blood-lactate concentration was assessed from earlobe capillary blood samples (5 μl) collected using a portable amperometric microvolume lactate analyzer (LactatePro, Arkray, Japan). Before each test, the analyzer was calibrated following the manufacturer's recommendations.
The V[Combining Dot Above]O2max and VT were assessed using a progressive-maximal treadmill test with a starting speed of 10 km·h−1 and speed increments of 1 km·h−1·min−1 until exhaustion. The V[Combining Dot Above]O2VT was assessed according to Beaver et al. (4). Achievement of V[Combining Dot Above]O2max was considered as the attainment of at least 2 of the following criteria: (a) a plateau in V[Combining Dot Above]O2 despite increasing speeds, (b) a respiratory exchange ratio above 1.10, (c) an HR ± 10 b·min−1 of age predicted HRmax (208 − 0.7 age). Expired gases were analyzed using a breath-by-breath automated gas-analysis system (VMAX29, Sensormedics, Yorba Linda, CA, USA).
The highest HR measured in either maximal incremental test was used as HRmax. Criteria for HRmax achievement were attainment of subjective and visual exhaustion, blood-lactate concentrations higher than 8 mmol·L−1 and HR plateau attainment despite speed increments.
The Yo-Yo IR1 performance was assessed according to the procedures reported by Castagna et al. (5).
The TRIMPi was calculated for each player for every training session according to the procedures suggested by Manzi et al. (19). Resting HR (HRrest) was measured with subjects in a resting state (i.e., quiet room, supine position after 24 hours of no exercise). The HRrest was assumed as the lowest 5-second value within 5-minute monitoring period. Individual blood-lactate concentrations vs. running speeds were obtained in each subject with speeds at 4 mmol·L−1 used as exercise paradigm (6,19). Blood-lactate concentrations were plotted against running speeds and fractional HR elevation (ΔHR, i.e., HR reserve), and individual blood-lactate concentration profiles (speed and ΔHR at 4 mmol·L−1) were identified via exponential interpolation (3).
Training volume and intensity were prescribed to the players by team strength and conditioning and technical-tactical coaches. The prescribed training schedule represents the typical training program performed by professional premiership players to prepare for the upcoming competitive season (6).
During all the training sessions and tests, the HR was recorded every 5 seconds with a short-range telemetry system (Polar Team System, Polar Electro Oy, Kempele, Finland). The HR data were downloaded on a portable PC and analyzed using dedicated software (Polar ProTrainer 5, Polar Electro Oy, Kempele, Finland) and an electronic spread-sheet (Excel, Microsoft Corporation, USA).
The results are expressed as mean ± SD and 95% confidence intervals (95% CI). Assumption of normality was verified using the Shapiro-Wilk W test. Variables association was assessed using Pearson's product-moment correlation coefficients and linear regression analysis. Qualitative magnitude of associations was reported according to Hopkins (12). Pre-to-post changes were examined with paired t-tests. The Cohen's d was used to assess effect size (ES) (7). Significance was set at p ≤ 0.05.
The average weekly TL for the observed period was of 644 ± 224 AU (arbitrary units).
The S4 (from 13.7 ± 2.0 to 14.7 ± 1.5 km·h−1; p = 0.0008; 95% CI from 0.48 to 1.52 km·h−1; ES = 1.09), V[Combining Dot Above]O2max (from 58.7 ± 4.4 to 61.2 ± 4.1 ml·kg−1·min−1; p = 0.009; 95% CI from 0.75 to 4.3 ml·kg−1·min−1; ES = 0.9), and V[Combining Dot Above]O2VT (from 49.0 ± 4.5 to 52.7 ± 4.2 ml·kg−1·min−1; p = 0.0003; 95% CI from 2.1 to 5.2 ml·kg−1·min−1; ES = 1.4) significantly improved pretraining to posttraining. The Yo-Yo IR1 performance significantly improved after the training period (from 1,998 ± 279 to 2,366 ± 409 m, 95% CI from 237 to 498 m; ES = 2.1).
The TRIMPi was significantly associated with change in V[Combining Dot Above]O2max (r = 0.77, p = 0.002, 95% CI from 0.38 to 0.93, very-large), S4 (r = 0.64, p = 0.004, 95% CI from 0.25 to 0.85, large, Figure 1), and V[Combining Dot Above]O2VT (r = 0.78, p = 0.002, 95% CI from 0.40 to 0.93, very-large). A large association (r = 0.69, p = 0.009, 95% CI from 0.22 to 0.90, large) was found between TRIMPi and change in Yo-Yo IR1 performance.
This is the first study that examined the association of TRIMPi with variables of aerobic-fitness and specific intermittent-endurance performance in male premiership Soccer players. The reported results showed large to very-large association between average preseason weekly TRIMPi and percentage of changes in the considered physiological variables. These findings provide evidence for the longitudinal validity of the TRIMPi method and of an intervention-magnitude effect on aerobic fitness in premiership soccer players during the precompetitive season (13).
The TRIMPi method is an integrated measure of TL, which permits us to account for intensity and volume effects on the biological and physiological systems of the athletes (19). As a consequence of this, the TRIMPi constitutes a viable way to monitor the internal load of athletes in endurance sport and a potentially interesting variable for tracking group training in team sports (19).
In this study, the TRIMPi showed to be associated with the aerobic-fitness variables that were reported to be relevant to soccer performance (23). Indeed, the interindividual variability in TRIMPi was very large associated with variability in V[Combining Dot Above]O2max changes. Similarly, improvements in submaximal components of aerobic fitness showed large to very-large associations with mean weekly TRIMPi. These results suggest that TRIMPi was a valid measure of the reported individual changes in aerobic fitness in premiership soccer players. Given this,TRIMPi may be successfully used for training prescription in elite-standard players during preseason.
The regression equation describing the relationship between TRIMPi and V[Combining Dot Above]O2max achieved changes (TRIMPi = 498.13 + 3,326.78 × %V[Combining Dot Above]O2max) showed that to maintain the acquired physiological level (i.e., %V[Combining Dot Above]O2max = 0), players would need to accumulate at least 498 AU during the weekly training of the competitive season. Maintenance weekly TL for S4 (TRIMPi = 453.67 + 2,118.74 × %S4 ) and V[Combining Dot Above]O2 VT (TRIMPi = 415.18 + 2,974.66 × %V[Combining Dot Above]O2 VT) were (i.e., y = 0) 454 and 415 AU, respectively. This information is of interest to guide training during the season once the strength and conditioning coach considers that the required improvement in aerobic fitness has been attained. Additionally, this critical TRIMPi values may be considered during the postcompetitive season transition phase to guide the fitness maintenance on individual basis using objective tools (1). Because of practical interest of this issue, experimental interventions with preplanned TRIMPi are warranted.
In this descriptive training study as a reference of players' match physical capability, the Yo-Yo IR1 performance was used (2). The nonexperimental training approach used in this study showed to induce significant improvements in Yo-Yo IR1 that enforce the increased match fitness achieved during the preseason training by premiership players. The resulting 18.4% mean change of the Yo-Yo IR1 performance was in line with that of a previous research report carried out in soccer (2). Specifically, the results of this study were lower than that reported by Krustrup et al. (16) in elite-standard referees (31 vs. 18.4%) but similar (17–22 vs. 18.4%) to the improvements in young elite-standard soccer players found by Hill-Haas et al. (11). Again Ferrari-Bravo et al. (9) found improvements of 22 and 17% in Yo-Yo IR1 performance in young soccer players performing exercise-mode specific sprint training and high-intensity interval running during the preseason (i.e., 7 weeks), respectively. This information provided supporting evidence for the sensibility of the Yo-Yo IR1 in tracking changes in specific endurance in premiership players. The resulting magnitude of the changes showed that with proper load implementation the Yo-Yo IR1 performance may be substantially improved (ES = 2.1) even in well-trained professional players (baseline Yo-Yo IR1 1,998 ± 279 m). In this regard, average weekly TRIMPi values >509 AU (TRIMPi = 509.18 + 1,205.86 × %Yo-Yo IR1) should be considered for promoting improvements in specific endurance in premiership Soccer players during preseason.
Analysis of the critical weekly TRIMPi maintenance values showed that to improve maximal aerobic fitness and specific endurance, the weekly TL should exceed the 500 AU. Doing this, the benefit would be experienced in the whole range of aerobic fitness and performance.
During the observed training period, the players spent 7% of their total training time at HR >90% of HRmax. This was similar (7 vs. 8%) to the training distribution reported by Castagna et al. (6) in Italian professional premiership soccer players during the preseason (6 training weeks). Interestingly, this profile was similar to that reported by Esteve-Lanao et al. (8) and Manzi et al. (19) in endurance athletes. This finding lends support to the limited amount of time necessary to induce practical improvement in aerobic fitness in elite and medium standard soccer players during the first stage of the yearly training routine. Specifically, Impellizzeri et al. (14) showed that a significant improvement in aerobic fitness associated with match-performance enhancements were obtained with just 6–7% of the training time spent in structured aerobic-fitness aimed drills. In light of these findings, it could be argued that at least 7% of the training time should be performed at high intensity (i.e., 90–95% o HRmax) to induce practical improvement in aerobic fitness in soccer. This irrespective of the competitive level considered (6,14,23). However, the absolute amount of time may result different as premiership players usually train longer during the weekly routine compared with lower level amateur or young soccer players (20).
Given the practical interest of this issue, further studies examining the effect on physiological adaptation in the aerobic domain of different amounts of time spent in the HR high-intensity zone (i.e., 90–95% of HRmax ) in soccer are warranted (6).
The pre-to-post changes in aerobic fitness observed in this study were in line with previous research findings (14,23). Specifically, the V[Combining Dot Above]O2max improved by 4.3% an improvement that was slightly lower than experimental training interventions induced changes in youth soccer. Indeed, Impellizzeri et al. (14) reported preseason (i.e., 4 weeks) improvement in V[Combining Dot Above]O2max in the range of 6–7% in young Soccer players with a starting V[Combining Dot Above]O2max lower than the players of this study (55.6 ± 3.4 vs. 58.7 ± 4.4 ml·kg−1·min−1). Supporting evidence for an effect of initial fitness on post preseason improvement in V[Combining Dot Above]O2max can be found examining the Bravo et al. (9) study that found improvement in the range of 7% in player possessing V[Combining Dot Above]O2max values oscillating between 52and 54 ml·kg−1·min−1. Interestingly, the players of the cited studies achieved V[Combining Dot Above]O2max values that matched this study premiership players' baseline values. Although these pictures may support the initial fitness effect the Helgerud et al. (10) study reported in-season improvements, as a consequence of high-intensity interval running that were remarkably higher than those reported in this study (i.e., 11 vs. 4.3%). This with junior players possessing V[Combining Dot Above]O2max values that matched at baseline the mean values for this study players (58.1 ± 4. vs. 58.7 ± 4.4 ml·kg−1·min−1, respectively). However, the magnitude of the improvement in V[Combining Dot Above]O2max reported in the Helgerud et al. (10) study was not supported by successive studies using the same training paradigm but conducted in more favorable training (i.e., preseason vs. season) and fitness conditions (i.e., lower V[Combining Dot Above]O2max values at baseline). The reason for less pronounced enhancement of V[Combining Dot Above]O2max in this specific period of the season may be the consequence of initial fitness level of the players ensured by the unsupervised postseason training performed by the premiership players and by the nature of the training sessions considered here (21).
The changes observed in submaximal aerobic fitness (∼7%) matched those reported for male young and premiership Soccer players in the preseason (6,14). The difference in magnitude changes in aerobic-fitness components suggests a greater sensibility of submaximal aerobic-fitness variables in tracking preseason physiological adaptations (15).
This study results showed that in premiership soccer players, improvement in soccer relevant aerobic-fitness and performance variables were associated with individual training responses during the preseason. This demonstrates the responsiveness of TRIMPi in tracking changes in aerobic fitness and estimated match performance. Indeed, TRIMPi variations were able to account for interindividual difference in training adaptations despite the observed moderate changes in aerobic-fitness (4–7%). This adds to the body of evidence that already showed longitudinal validity of TRIMPi in endurance athletes (19).
From the practical point of view, weekly TL in the range of 500 AU may ensure a global development of aerobic-fitness and performance variables. This information has huge impact on training prescription in elite-standard soccer training. Furthermore, the knowledge of threshold values grants practical guidelines to the development of a structured ergonomic model of elite-standard soccer.
The TRIMPi method can be successfully used to check the training process dynamic during the precompetitive season and guide performance maintenance during the competitive season. Given the integrated measure nature of the TRIMPi information about the dose-response relationship to changes in the aerobic domain should be assessed with experimental manipulation of weekly TLs. Therefore, further studies are warranted examining the optimal weekly TRIMPi to be provided in the premiership setup to maximize training responses in aerobic fitness and performance.
The authors have no conflict of interest with the nature of this study. This research received no funding.
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