In-season Training Load Research Articles

Non-starters vs. starters: Comparison of in-season training load relative to match load in professional soccer players

Non-starters vs. starters: Comparison of in-season training load relative to match load in professional soccer players

In-Season Training Load Variation - Heart Rate Recovery, Perceived Recovery Status, and Performance in Elite Male Water Polo Players: A Pilot Study.

Increased training and competition demands of the in-season period may disturb athlete fatigue and recovery balance. The aim of this study was to describe the training load distribution applied in a competitive period and the training adaptations and fatigue/recovery status of elite water polo players. Effective workload management during tapering (TAP) would restore player recovery and enhance performance. Case series. Level 4. Training load, perceived recovery, maximal speed in 100- and 200-meter swim, heart rate (HR) during submaximal swimming (HRsubmax) and HR recovery (HRR) were assessed in 7 outfield water polo players a week before starting a normal training microcycle (NM), after NM, and after congested (CON) and TAP training blocks in the lead-up to the Final Eight of the European Champions League. Training load was higher in NM compared with CON and TAP by 28.9 ± 2.6% and 42.8 ± 2.1% (P < 0.01, d = 11.54, and d = 13.45, respectively) and higher in CON than TAP by 19.4 ± 4.2% (P < 0.01, d = 3.78). Perceived recovery was lower in CON compared with NM and TAP (P < 0.01, d = 1.26 and d = 3.11, respectively) but not different between NM and TAP (P = 0.13, d = 0.62). Both 100- and 200-meter swim performance was improved in TAP compared with baseline (P < 0.01, d = 1.34 and d = 1.12, respectively). No differences were detected among other training blocks. HRsubmax and most HRR were similar among the training periods. Effective management of training load at TAP can restore recovery and improve swimming performance without affecting HR responses. Despite lower workloads, CON training impairs perceived recovery without affecting performance; however, a short-term training load reduction after a CON fixture restores recovery and improves performance.

Changes in female football players' in-season training load, intensity and physical performance: training progression matters more than accumulated load.

This observational study investigated: (1) potential changes in female football players' in-season training load, intensity and physical performance, and (2) if in-season accumulated training load, intensity, or their progression are associated to changes in physical performance. Thirty-five national level female players (∼21 years, n = 35) from three top-teams of the Finnish national league participated. Players performed tests at the beginning and at the end of the 27-week in-season. Tests were: 30-m sprint, countermovement jump (CMJ) and 1,200-m shuttle run, used to calculate maximal aerobic speed (MAS). Players' external and internal training load and intensity were monitored in all on-field training sessions and official matches (3,941 data samples) using Polar Team Pro system. Training load decreased towards the end of the in-season (p < 0.05), but intensity remained stable. No changes in physical performance test results occurred from before to after in-season tests at a group level. Change of CMJ correlated negatively with accumulated training load, intensity and progression of total distance (TD) and low-intensity running distance (LIRD) (r = -0.398 to -0.599, p < 0.05). Instead, development of MAS correlated positively with progression of TD and LIRD intensities (r = 0.594 and 0.503, p < 0.05). Development of both CMJ and MAS correlated positively with intensity progression of very-high-intensity running distance (VHIRD) and number of accelerations and decelerations (r = 0.454-0.588, p < 0.05). Reduced training load over the in-season is not detrimental for players' physical performance when training intensity progressively increases. Intensity progression of VHIRD, moderate- and high-intensity accelerations and decelerations are indicators of both MAS and CMJ development, respectively.

Within-season Adaptations in Physical, Physiological and Technical-tactical Performance of Experimented Futsal Players

This study analysed the seasonal variations in futsal players’ physical, physiological, and technical–tactical performance. Eight senior futsal players from the same team were monitored at three time points in the season (beginning of the preseason, middle of the first half of the season, and middle of the second half of the season). A progressive and intermittent shuttle-running test (the futsal intermittent endurance test) was applied to collect the following variables: maximum velocity, distance covered, total distance covered, test duration, initial heart rate, peak heart rate, peak blood lactate concentration, and rating of perceived exertion. In addition, different match-performance variables were assessed during a simulated futsal match (goals scored, shots on goal, successful passes, balls lost, balls recovered, and goals conceded). Results indicated that the physiological variables of initial heart rate (p&lt;.001, η2=.862) and peak blood lactate concentration (p=.001, η2=.640) significantly varied over the course of the season. However, no significant differences were found in the physical and technical–tactical variables. This study has implications for sport practitioners; specifically, it emphasizes that preseason and in-season training load periodization enhances the physiological fitness of top-level futsal players, although their physical and technical–tactical performance remained relatively stable.

Quantification of in-season training load in Division I male collegiate soccer players

Quantification of in-season training load in Division I male collegiate soccer players

Quantification of training and match-load distribution across a season in elite English Premier League soccer players

ABSTRACTObjective: To examine training and match loads undertaken by soccer players competing in the English Premier League.Methods: Using a retrospective design, external (GPS) and internal training loads (sessions ratings of perceived exertion [sRPE-TL]) were examined in 26 players across the competition phase of the 2012–2013 English Premier League season. Within-subject linear mixed-models estimated the mean effects (95% confidence interval [CI]) for load data across 6-week mesocycles and 1-week microcycles.Results: Daily sRPE-TL (95% CI range, 15 to 111 AU) and total distance (95% CI range, 179 to 949 AU) were higher during the early stages (mesocycle 1 and 2) of the competition period. Overall, high-speed activity was similar between mesocycles. Across the training week, load was greater on match day and lower pre match-day (G-1) vs. all other days, respectively (p < 0.001). sRPE-TL (~70–90 AU per day) and total distance (~700–800 m per day) progressively declined over the 3 days before a match (p < 0.001). High-speed distance was greater 3 days (G-3) before a game vs. G-1 (95% CI, 140 to 336 m) while very high-speed distance was greater on G-3 and G-2 than G-1 (95% CI range, 8 to 62 m; p < 0.001).Conclusion: Periodisation of in-season training load is mainly evident across the weekly microcycle reflecting the recovery and preparation for matches.

Monitoring Training and Match Physical Load in Junior Soccer Players: Starters versus Substitutes.

The aim of this study was to investigate differences in the physical (locomotor activities) and physiological (Banister’s training impulse) in-season training load between starters and substitutes in a well-trained junior soccer team. Physical performance variables from the Polar Team Pro system were collected and analyzed from a sample of junior soccer players (N = 18; age = 15.7 ± 0.5 years; stature, 177.9 ± 4.6 cm; body mass, 67.1 ± 5.5 kg). The study analyzed a total of 10 matches and 38 training sessions during the 2018 season with linear mixed models. The players from the starting line-ups demonstrated significantly higher average weekly physical load compared to the non-starters with respect to all variables: distance (total, running, high-speed running, and sprint) [F (1, 573) ≥ 66, p < 0.001, eta = 0.10], number of accelerations and sprints [F (1, 573) ≥ 66, p < 0.001, eta = 0.10], as well as Banister’s training impulse (TRIMP) [F (1, 569) = 10, p < 0.001, eta = 0.02]. Evidence from this study indicates that a large amount of weekly accumulated high-speed running and sprint distances is related to match playing time. Therefore, weekly fitness-related adaptations in running at high speeds seem to favor the starters in a soccer team.

In-season training load quantification of one-, two- and three-game week schedules in a top European professional soccer team

Top European soccer teams that play in UEFA competitions often participate in one, two- or three-games per week. Therefore, it is necessary to ensure optimal match-day performance and full recovery. The aim of this study was to quantify internal and external training load (TL) within five microcycles: M1 and M2 – one-game weeks; M3 and M4 – two-game weeks; M5 – three-game week). Thirteen elite soccer players participated in this study. A global positioning system (GPS) was used to measure the total distance covered and distances of different exercise training zones (1–5), the session ratings of perceived exertion (s-RPE) scores and the amount of creatine kinase (CK) created during daily training sessions for the 2015–2016 in-season period. The data were analysed with respect to the number of days prior to a given match. The main results indicate that there was a significant difference in training intensity for zone 1 between M2 and M4 (4010.2 ± 103.5 and 4507.6 ± 133.0 m, respectively); a significant difference in training intensity for zone 3 between M1 and M5 (686.1 ± 42.8 and 801.2 ± 61.2 m, respectively); a significant difference in the duration of the training sessions and matches between M2 and M5 (69.2 ± 2.1 and 79.6 ± 2.3) and M3 and M5 (69.7 ± 1.0 and 79.6 ± 2.3); and finally, there was a significant difference in CK between M3 and M2 (325.5 ± 155.0 and 194.4 ± 48.9). Moreover, there was a significant decrease in TL in the last day prior to a match, for all microcycles and all variables. There was no significant difference with respect to s-RPE. This study provides the first report of daily external and internal TLs and weekly accumulated load (training sessions and match demands) during one, two, and three-game week schedules in a group of elite soccer players. Expected significant differences are found in daily and accumulated loads for within- and between-game schedules. A similar pattern is exhibited for one- and two-game week microcycles regarding the day before the match, which exhibits a decrease in all variables. Despite the different number of games played per week, TL remain similar between microcycles for zone 2 and 5, plus s-RPE.

Effects of Off-Season Training on In-Season Training Load and Time Spent in Heart Rate Zones

Maximizing training in and out of season is essential for player development in college soccer. Maintaining and improving aerobic performance has been shown to be successful using high-intensity interval training (HIIT) and vigorous endurance exercise (END). Utilizing HIIT can be as much as half the time commitment, which among Division III who have limited contact time, becomes crucial for success of programs. PURPOSE: To compare the effects of two off season endurance-training protocols on Training Load (TL), as well as time spent in Heart Rate Zone (HRZ) during in season training. METHODS: During off seasons, players (N=19) were randomly assigned to either HIIT or END. The HIIT group performed five maximal 30-sec sprints with 4.5 minutes of recovery, twice per week, and the END group completed a 40-min run at 80% heart-rate reserve twice weekly. VO2max was estimated pre vs post of the 5 week training intervention. Once athletes were in season, data was collected using Polar Team2 system for 6 sessions. TL and time in each of the 5 HRZs were recorded from 50% to 100% HRmax, in 10% increments. RESULTS: During off season, both groups significantly improved their VO2max estimated by the Beep test; however, there was no significance between groups. When examining TL and HRZ during in season training, there were also no significant differences (p>0.05) among groups. Nevertheless, average TL for athletes in the HIIT group (190.27+41.92) was higher than athletes in the END group (180.29+60.70). Additionally, when examining HRZ, athletes in the HIIT group spent a larger percentage of time (39.70%) in 80% HRZ or higher as compared to the END group (35.72%). CONCLUSIONS: Soccer players may improve aerobic performance irrespective of training method thus saving significant time during self-directed off season training among Division III athletes . In-season analysis indicated neither training type impacted TL; however, the HIIT group spent on average an hour more in the 80-100% HRZ.

Relationships Between Model Estimates and Actual Match-Performance Indices in Professional Australian Footballers During an In-Season Macrocycle.

To assess and compare the validity of internal and external Australian football (AF) training-load measures for predicting match exercise intensity (MEI/min) and player-rank score (PRScore) using a variable dose-response model. A cohort of 25 professional AF players (23 ± 3y, 188.3 ± 7.2cm, 87.7 ± 8.4kg) completed a 24-wk in-season macrocycle. In-season internal training and match load were quantified using session rating of perceived exertion (sRPE) and external load from satellite and accelerometer data. Using a training-impulse (TRIMP) calculation, external load (au) was represented as distance (TRIMPDist), distance ≥4.16m/s (TRIMPHSDist), and PlayerLoad (TRIMPPL). In-season training load, MEI/min, and PRScore were applied to a variable dose-response model, which provided estimates of MEI/min and PRScore. Predicted MEI/min and PRScore were correlated with actual measures from each match. The magnitude of the difference between MEI/min and PRScore estimates for each model input and the difference between the precision of internal and external load measures to predict MEI/min and PRScore were calculated using the effect size ± 90% confidence interval (CI). Estimates of MEI/min demonstrated very large associations with actual MEI/min (r, 90% CI) (eg, TRIMPDist .76 ± .13, and sRPESkills .73 ± .14). Estimates of PRScore demonstrated associations of large magnitude with actual PRScore using the same inputs. Precision of actual MEI/min was lowest using sRPE compared with (ES ± 90% CI) TRIMPDist, -.67 ± .34, and TRIMPPL, -.91 ± .39. There were trivial and unclear differences in the precision of PRScore estimates between TRIMP and sRPE inputs. Dose-response models from multiple training-load inputs can predict within-individual variation of MEI/min and PRScore. Internal and external training-input methods exhibited comparable predictive power.

Quantification of in-season training load relative to match load in professional Dutch Eredivisie football players

ABSTRACTObjectives: The aims of this study were (1) to quantify and compare the load of a professional football team's training days and matches and (2) to compare training of nonstarters the day after the match with regular training of starters and nonstarters.Methods: On-field training load during in-season training days (categorized as days before match day, i.e., MD minus) and 3 friendly matches were recorded using alocal positioning measurement system.Results: Mixed linear models showed lower load when training approached match day. Relative to match values (100%), training values for running (52 -20%; MD-4 -MD-1) and high-speed running (38 -15%) were lower than for total distance (67 -35%), and all considerably lower than match values. On average, medium and high accelerations and decelerations during training were more similar to match values (90 -39%). Load during nonstarters training was lower than during regular training for almost all variables on MD-4 and several high-intensity variables on MD-3 and MD-2.Conclusions: The results highlight that acceleration and deceleration measures complement more commonly used external load variables based on distance and speed. Furthermore, nonstarters are potentially under-loaded compared to starters, especially in terms of (high-speed) running.

Training load--injury paradox: is greater preseason participation associated with lower in-season injury risk in elite rugby league players?

AimTo determine whether players who completed a greater number of planned preseason training sessions were more or less likely to be injured during the competitive season.MethodsA cohort of 30 elite...

The Influence of In-Season Training Loads on Injury Risk in Professional Rugby Union.

To explore the association between in-season training-load (TL) measures and injury risk in professional rugby union players. This was a 1-season prospective cohort study of 173 professional rugby union players from 4 English Premiership teams. TL (duration × session-RPE) and time-loss injuries were recorded for all players for all pitch- and gym-based sessions. Generalized estimating equations were used to model the association between in-season TL measures and injury in the subsequent week. Injury risk increased linearly with 1-wk loads and week-to-week changes in loads, with a 2-SD increase in these variables (1245 AU and 1069 AU, respectively) associated with odds ratios of 1.68 (95% CI 1.05-2.68) and 1.58 (95% CI 0.98-2.54). When compared with the reference group (<3684 AU), a significant nonlinear effect was evident for 4-wk cumulative loads, with a likely beneficial reduction in injury risk associated with intermediate loads of 5932-8651 AU (OR 0.55, 95% CI 0.22-1.38) (this range equates to around 4 wk of average in-season TL) and a likely harmful effect evident for higher loads of >8651 AU (OR 1.39, 95% CI 0.98-1.98). Players had an increased risk of injury if they had high 1-wk cumulative loads (1245 AU) or large week-to-week changes in TL (1069 AU). In addition, a U-shaped relationship was observed for 4-wk cumulative loads, with an apparent increase in risk associated with higher loads (>8651 AU). These measures should therefore be monitored to inform injury-risk-reduction strategies.

Energy intake and expenditure assessed ‘in-season’ in an elite European rugby union squad

Rugby union (RU) is a complex high-intensity intermittent collision sport with emphasis placed on players possessing high lean body mass and low body fat. After an 8 to 12-week pre-season focused on physiological adaptations, emphasis shifts towards competitive performance. However, there are no objective data on the physiological demands or energy intake (EI) and energy expenditure (EE) for elite players during this period. Accordingly, in-season training load using global positioning system and session rating of perceived exertion (sRPE), alongside six-day assessments of EE and EI were measured in 44 elite RU players. Mean weekly distance covered was 7827 ± 954 m and 9572 ± 1233 m with a total mean weekly sRPE of 1776 ± 355 and 1523 ± 434 AU for forwards and backs, respectively. Mean weekly EI was 16.6 ± 1.5 and 14.2 ± 1.2 megajoules (MJ) and EE was 15.9 ± 0.5 and 14 ± 0.5 MJ. Mean carbohydrate (CHO) intake was 3.5 ± 0.8 and 3.4 ± 0.7 g.kg−1 body mass, protein intake was 2.7 ± 0.3 and 2.7 ± 0.5 g.kg−1 body mass, and fat intake was 1.4 ± 0.2 and 1.4 ± 0.3 g.kg−1 body mass. All players who completed the food diary self-selected a ‘low’ CHO ‘high’ protein diet during the early part of the week, with CHO intake increasing in the days leading up to a match, resulting in the mean EI matching EE. Based on EE and training load data, the EI and composition seems appropriate, although further research is required to evaluate if this diet is optimal for match day performance

Influence of Pitching Rotation Day on Resting Heart Rate Variability Among Professional Baseball Starting Pitchers

Longitudinal examination of the autonomic nervous system (ANS) through measures of heart rate variability (HRV) has recently been proposed as a possible methodology to monitor acute and chronic responses to training and recovery. Due to the regimented rotation day schedule of baseball starting pitchers, this methodology holds potential for guiding in-season training load among this population. However, measures of HRV among baseball starting pitchers have yet to be reported across an entire season. PURPOSE: The purpose of this study was to examine the influence of a 5-day pitching rotation schedule on resting measures of HRV across an entire baseball season among professional baseball starting pitchers. METHODS: Eight Single-A level professional baseball starting pitchers volunteered to participate in this study (21.91 ± 1.34 yrs; 185.42 ± 3.59 cm; 85.23 ± 7.49 kg). Resting measures of HRV were collected daily throughout the season upon arrival to the clubhouse and before any physical training. All HRV data were collected using remote physiological monitors with the participant quietly lying supine for 10 minutes. Square root of the mean sum of the squared differences (RMSSD) were calculated during the middle five minutes of the R-R series data. A mixed-model repeated measures ANOVA was used to examine the influence of pitching rotation day on resting RMSSD across the season, as well as differences in resting RMSSD among pitchers. An alpha of p < 0.05 determined statistical significance. RESULTS: The interaction effect between Rotation Day × Pitcher on resting RMSSD was not significant (F28,706 = 1.267, p = 0.163). However, significant main effects of both Rotation Day and Pitcher on resting RMSSD were identified (F4,706 = 2.519, p = 0.040; F7,706 = 106.940, p < 0.001, respectively). Follow-up pairwise tests revealed that resting RMSSD on Day 2 was significantly lower than all other rotation days. CONCLUSIONS: Resting HRV one day after completing a normally scheduled start (i.e., Day 2) is significantly lower than all other rotation days. However, this altered ANS function returned to Day 1 values before the next scheduled start. Furthermore, the significant differences in resting RMSSD values among the pitchers suggests that future research may need to examine longitudinal HRV changes on an individual basis.

Influence of Physical Fitness, Age, Experience, and Weekly Training Load on Match Performance in Elite Australian Football

Season long competition schedules in football create unique challenges for coaches in balancing the requirements of recovery, developing and maintaining physical fitness, and adjusting the training load before each match. The aim of this study was to investigate the influence of player characteristics (physical fitness, age, and playing experience) and weekly in-season training load on elite match performance across an Australian football season. Twenty-five players (age: 24.1 ± 3.0 years; height: 188.3 ± 7.3 cm; weight: 90.4 ± 8.3 kg) from one elite team participated in this study. Before the season, player's age, experience, height, and weight along with measures of aerobic (6-minute run) and anaerobic (6 × 40 m repeated sprints) physical fitness were recorded. Individual player training load during the season was measured using global positioning system technology for the main training session of the week. Player match performance was calculated weekly from 33 individual playing statistics. Multilevel modeling was used to investigate the relationship between weekly training load and match performance and to explore the influence of player characteristics on this relationship. Playing experience (p < 0.01) and aerobic fitness (p < 0.05) displayed positive relationships with performance, whereas player age (p < 0.01) showed a negative relationship. Most players coped well with weekly variations in training load; however, the relationship was moderated by the results of the preseason repeated sprint test (p < 0.05). The adverse effect on playing performance in selected players after a more intense training session suggests that recovery from the session may be delayed in players who exhibit a better anaerobic fitness profile.

A Comparison of Methods to Quantify the In-Season Training Load of Professional Soccer Players

To compare various measures of training load (TL) derived from physiological (heart rate [HR]), perceptual (rating of perceived exertion [RPE]), and physical (global positioning system [GPS] and accelerometer) data during in-season field-based training for professional soccer. Fifteen professional male soccer players (age 24.9 ± 5.4 y, body mass 77.6 ± 7.5 kg, height 181.1 ± 6.9 cm) were assessed in-season across 97 individual training sessions. Measures of external TL (total distance [TD], the volume of low-speed activity [LSA; <14.4 km/h], high-speed running [HSR; >14.4 km/h], very high-speed running [VHSR; >19.8 km/h], and player load), HR and session-RPE (sRPE) scores were recorded. Internal TL scores (HR-based and sRPE-based) were calculated, and their relationships with measures of external TL were quantified using Pearson product-moment correlations. Physical measures of TD, LSA volume, and player load provided large, significant (r = .71-.84; P < .01) correlations with the HR-based and sRPE-based methods. Volume of HSR and VHSR provided moderate to large, significant (r = .40-.67; P < .01) correlations with measures of internal TL. While the volume of HSR and VHSR provided significant relationships with internal TL, physical-performance measures of TD, LSA volume, and player load appear to be more acceptable indicators of external TL, due to the greater magnitude of their correlations with measures of internal TL.

Quantification of the typical weekly in-season training load in elite junior soccer players

We examined the typical weekly training load experienced by elite junior soccer players during the in-season competitive period. Altogether, eight under-14 (U14), eight under-16 (U16) and eight under-18 (U18) players were monitored over a 2-week period during the first month of the 2010–11 competitive season. This time period included one competitive match per week. Physiological loading was monitored using heart rate (HR) and ratings of perceived exertion (RPE). Training and match loads were calculated by multiplying the global session RPE and duration (session-RPE). Total weekly training load (training and match) increased with age (U14, 2524 ± 128 arbitrary units [AU]; U16, 2919 ± 136 AU; U18, 3948 ± 222 AU; P < 0.05). Differences in the daily training load across the training week were also evident in the older age group relative to both U14 and U16. The amount of time engaged in low (<50% HRmax) and high (>90% HRmax) intensity activity during training and match-play was significantly lower and higher respectively in the U18 compared to the U14 group (P < 0.05). When comparing activity, the intensity (% HRmax) of field training (U18, 69 ± 2%; U16, 74 ± 1%; U14, 74 ± 2%) was significantly lower compared to match-play (U18, 81 ± 3%; U16, 84, ± 2%; U14, 83 ± 2) across all age groups (P < 0.05). Findings demonstrate that age related differences in the volume and intensity of weekly in-season training load are evident amongst elite professional junior soccer players. These differences may reflect a systematic approach to the long-term physical development of elite junior players.

A modified TRIMP to quantify the in-season training load of team sport players

The aims of the study were to modify the training impulse (TRIMP) method of quantifying training load for use with intermittent team sports, and to examine the relationship between this modified TRIMP (TRIMPMOD) and changes in the physiological profile of team sport players during a competitive season. Eight male field hockey players, participating in the English Premier Division, took part in the study (mean±s: age 26±4 years, body mass 80.8±5.2 kg, stature 1.82±0.04 m). Participants performed three treadmill exercise tests at the start of the competitive season and mid-season: a submaximal test to establish the treadmill speed at a blood lactate concentration of 4 mmol · l−1; a maximal incremental test to determine maximal oxygen uptake ([Vdot]O2max) and peak running speed; and an all-out constant-load test to determine time to exhaustion. Heart rate was recorded during all training sessions and match-play, from which TRIMPMOD was calculated. Mean weekly TRIMPMOD was correlated with the change in [Vdot]O2max and treadmill speed at a blood lactate concentration of 4 mmol · l−1 from the start of to mid-season (P<0.05). The results suggest that TRIMPMOD is a means of quantifying training load in team sports and can be used to prescribe training for the maintenance or improvement of aerobic fitness during the competitive season.