Quantification Of Training Load Research Articles

The Influence of Different Training Load Quantification Methods on the Fitness-Fatigue Model.

Numerous methods exist to quantify training load (TL). However, the relationship with performance is not fully understood. Therefore the purpose of this study was to investigate the influence of the existing TL quantification methods on performance modeling and the outcome parameters of the fitness-fatigue model. During a period of 8 weeks, 9 subjects performed 3 interval training sessions per week. Performance was monitored weekly by means of a 3-km time trial on a cycle ergometer. After this training period, subjects stopped training for 3 weeks but still performed a weekly time trial. For all training sessions, Banister training impulse (TRIMP), Lucia TRIMP, Edwards TRIMP, training stress score, and session rating of perceived exertion were calculated. The fitness-fatigue model was fitted for all subjects and for all TL methods. The error in relating TL to performance was similar for all methods (Banister TRIMP: 618 [422], Lucia TRIMP: 625 [436], Edwards TRIMP: 643 [465], training stress score: 639 [448], session rating of perceived exertion: 558 [395], and kilojoules: 596 [505]). However, the TL methods evolved differently over time, which was reflected in the differences between the methods in the calculation of the day before performance on which training has the biggest positive influence (range of 19.6d). The authors concluded that TL methods cannot be used interchangeably because they evolve differently.

Quantification of training and match-play load across a season in professional youth football players

The purpose of this study was to quantify load across an entire season for professional youth football players and assess the effects of stage of season, playing position and training day relative to match day (MD). Data from ratings of perceived exertion and seven global positioning system (GPS) derived measures of external training load were collected from 20 players across a 47-week season. Mixed linear models were used to assess the effects of stage of season, training proximity to match day (e.g. MD-1, MD-2) and position across each dependent variable. Training proximity to match day was found to have the most substantive effect with effect sizes ranging from small ([Formula: see text] to large ([Formula: see text]. Across training load measures, mean values collected on match day were on average 47% higher than all other sessions. Whilst significant regression coefficients were obtained for playing position (p ≤ 0.003) and stage of season (p ≤ 0.049), effect sizes were close to zero ([Formula: see text]in each instance. This study provides insight into the season-long training and match-play demands of a professional youth football team. It highlights the significant impact of match-play on load and supports the use of multiple methods of collecting training load data. Overall, there was limited variation in mean values of dependent variables across playing position, stage of the season and loading during midweek training. These findings highlight the need for future research to investigate whether greater systematic variations in training load can be used to increase physical fitness and maximise physical performance during competition.

Quantification of training and match load in elite youth soccer players: a full-season study.

The present study aimed to quantify training and match load in elite young soccer players over the course of an entire season. Using a longitudinal design, session-rate of perceived exertion (s-RPE) and its metrics (weekly acute workload [wAW], acute to chronic workload ratio [wACWR], training monotony and training strain) were examined in twenty-one elite young soccer players (mean±standard deviation; age: 16.1±0.2 years; height: 176.8±5.6 cm; body mass: 67.3±5.7 kg; BMI: 21.5±1.4 kg/m2; V̇O<inf>2max</inf>: 47.6±3.8 mL.kg-1.min-1) during the whole season containing 4 meso-cycles: preseason (Pre-S), early-season (Ear-S), mid-season (Mid-S), and end-season (End-S). Repeated-measures analysis of variance examined variations in s-RPE load data across the 4 meso-cycles and 1-week of microcycle. Analyzing data revealed the End-S had a significant greater wAW compared to Early-S (P=0.002, g=0.96) and Mid-S (P<0.001, g=1.09). However, no differences between in-season periods were observed in wACWR (P=0.524). The within-week variations revealed significant lower wAW in prematch a day (MD-1) (P<0.001), 1 day after match (MD+1) (P<0.001) and 2 days after match (MD+2) (P<0.001) compared to match day (MD) for overall team analysis. Additionally, analyses by playing position showed that fullbacks have a significant lower AW in MD+2 compared to MD (P<0.029). The periodization of training load indicated variations across the whole season in young elite players. The weekly microcycle perceived load could be identified as follows; there are higher training loads on MD-3 and MD-2 which was similar to intensities experienced by players throughout the match play and, furthermore, lower overall WL on the MD+1 and MD+2 in order to ensure the optimal recovery of the players.

Comparative Study Between Two Methods Of Training Load Quantification Through Small-Sided Games In Soccer

Comparative Study Between Two Methods Of Training Load Quantification Through Small-Sided Games In Soccer

A New Approach for Training-load Quantification in Elite-level Soccer: Contextual Factors.

The aims of this study were to analyse the physical responses of professional soccer players during training considering the contextual factors of match location, season period, and quality of the opposition; and to establish prediction models of physical responses during training sessions. Training data was obtained from 30 professional soccer players from Spanish La Liga using global positioning technology (N=1365 performances). A decreased workload was showed during training weeks prior to home matches, showing large effects in power events, equivalent distance, total distance, walk distance and low-speed running distance. Also, the quality of the opposition also affected the training workload (p<0.05). All regression-models showed moderate effects, with an adjusted R2 of 0.37 for metabolic-work, 0.34 for total distance covered, 0.25 for high-speed running distance (18-21 km·h-1), 0.29 for very high-speed running distance (21-24 km·h-1), 0.22 for sprint running distance (>24 km·h-1) and 0.34 for equivalent distance. The main finding of this study was the great association of match location, season period and quality of opposition on the workload performed by players in the training week before the match; and the development of workload prediction-models considering these contextual factors, thus proposing a new and innovative approach to quantify the workload in soccer.

Physical fitness and conditioning in badminton school matches: a comparison between modalities and sexes

ABSTRACT The aim of the present study was to examine physical fitness and conditioning external workload depending on different badminton modalities (badminton (BAD) and mini badminton (BADMini)) and sex. Twenty-eight scholar-age children (16 boys and 12 girls) participated in a two days congested-fixture tournament (84 matches), and external training load was quantified using six antennae ultra-wideband technology. The results showed that different badminton modalities (BAD and BADMini) induce different external workloads. In addition, sex-related differences were found in both modalities. In conclusion, the differences found between both BAD modalities (BAD and BADMini) make suitable the use of space restriction to adapt BAD to scholar badminton players, allowing a walk among elite players and young players. Moreover, sex-related differences found in both modalities demonstrate that the coaches should make individualised training programmes. The quantification of external training load reported would be helpful to provide badminton academy coaches to prepare specific near competition programmes such as tournaments.

Training load monitoring in football: application of field systems in professional male players (PhD Academy Award)

As a practitioner involved in player’s monitoring, one of my duties was to establish monitoring practices to inform the coaching and sports medicine departments about the training process. In this...

Training load quantification of high intensity exercises: Discrepancies between originaland alternative methods.

The purpose of this study was to quantify training loads (TL) of high intensity sessions through original methods (TRIMP; session-RPE; Work-Endurance-Recovery) and their updated alternatives (TRIMPcumulative; RPEalone; New-WER). Ten endurance athletes were requested to perform five sessions until exhaustion. Session 1 composed by a 800m maximal performance and four intermittent sessions performed at the 800m velocity, three sessions with 400m of interval length and work:recovery ratios of 2:1, 1:1 and 1:2 and one with 200m intervals and 1:1. Total TL were quantified from the sessions' beginning to the cool-down period and an intermediate TL (TL800) was calculated when 800m running was accumulated within the sessions. At the end of the sessions high and similar RPE were reported (effect size, η2 = 0.12), while, at the intermediate 800m distance, the higher interval distances and work:recovery ratios the higher the RPE (η2 = 0.88). Our results show marked differences in sessions' total TL between original (e.g., lowest TL for the 800m and highest for the 200m-1:1 sessions) and alternative methods (RPEalone and New-WER; similar TL for each session). Differences appear in TL800 notably between TRIMP and other methods which are negatively correlated. All TL report light to moderate correlations between original methods and their alternatives, original methods are strongly correlated together, as observed for alternative methods. Differences in TL quantification between original and alternative methods underline that they are not interchangeable. Because of high exercise volume influence, original methods markedly enhance TL of sessions with higher exercise volumes although these presented the easiest interval distances and work-recovery ratios. Alternative methods based on exhaustion level (New-WER) and exertion (RPEalone) provided a new and promising point of view of TL quantification where exhaustion determines the highest TL whatever the exercise. This remains to be tested with more extended populations submitted to wider ranges of exercises.

Moving Beyond Weekly "Distance": Optimizing Quantification of Training Load in Runners.

Quantifying total running distance is valuable, as it comprises some aspects of the mechanical/neuromuscular, cardiovascular, and perceptual/psychological loads that contribute to training stress and is partially predictive of distance-running success. However, running distance is only one aspect contributing to training stress. The purpose of this commentary is to highlight (1) problems with only using running distance to quantify running training and training stress, (2) the importance of alternative approaches to quantify and monitor training stress, (3) moderating factors (effect-measure modifiers) of training loads, and (4) the challenges of monitoring training stress to assess injury risks. Training stress is influenced by external (ie, application of mechanical load) and internal (ie, physiological/psychological effort) training load factors. In running, some commonly used external load factors include volume and pace, while physiological internal load factors include session rating of perceived exertion, heart rate, or blood lactate level. Running distance alone might vastly obscure the cumulative training stress on different training days and, ultimately, misrepresent overall training stress. With emerging and novel wearable technology that quantifies external load metrics beyond volume or pace, the future of training monitoring should have an ever-increasing emphasis on biomechanical external load metrics, coupled with internal (ie, physiological/psychological) load metrics. It may be difficult to change the running culture's obsession with weekly distance, but advanced and emerging methods to quantify running training discussed in this commentary will, with research confirmation, improve training monitoring and injury risk stratification. J Orthop Sports Phys Ther 2020;50(10):564-569. Epub 1 Aug 2020. doi:10.2519/jospt.2020.9533.

CHARACTERIZING PERFORMANCE IN ELITE TRACK AND FIELD SPRINTERS IN RELATION TO THE ACUTE:CHRONIC WORKLOAD RATIO

PURPOSE: The acute:chronic workload ratio is a method of training load quantification that quantifies internal and external responses to training. Chronic training load is a rolling average of the most recent 28 days of training, and the acute workload is the most recent 7 days. The purpose of this study was to explore the relationship between the acute:chronic workload ratio and peak performance in elite track and field sprinters over the course of the 2018 outdoor season. METHODS: The acute:chronic workload ratio was determined retrospectively by calculating the sum of the 7 days before a competition session ratings of perceived exertion of training load (acute load) and dividing it by the average weekly session rating of perceived exertion of training load over the 28-days prior to competition (chronic workload). Partial correlations were used to characterize the relationship between race time (covaried for confounding variables of temperature, humidity, and wind) and the acute:chronic workload ratio. Secondarily, the adjusted race times were used to create Z-scores for each sprinters’ race time. Bins were then created for the acute:chronic workload ratio ranges, and the Z-scores were pooled into the acute:chronic workload ratio bins with which they corresponded. RESULTS: Moderate, positive correlations between the acute:chronic workload ratio and race times for the 100m (r= 0.542) and 200m (r= 0.711) races were observed. 85% of 100m sprinters and 60% of 200m sprinters had their lowest times within the 0.8-1.3 z- score bin: a range cited in previous research as being associated with a lowest risk of injury. CONCLUSIONS: Maintaining an acute:chronic workload ratio between 0.8 and 1.3 may be optimal for elite track and field sprinters to reach their peak performance in the 100m and 200m races. An individualized approach to training load using the acute:chronic workload ratio should help coaches and performance staff with individualized training-load prescription for the sprinters to reach peak performance.

Power Assessment in Road Cycling: A Narrative Review

Nowadays, the evaluation of physiological characteristics and training load quantification in road cycling is frequently performed through power meter data analyses, but the scientific evidence behind this tool is scarce and often contradictory. The aim of this paper is to review the literature related to power profiling, functional threshold testing, and performance assessment based on power meter data. A literature search was conducted following preferred reporting items for review statement (PRISMA) on the topic of {“cyclist” OR “cycling” AND “functional threshold” OR “power meter”}. The reviewed evidence provided important insights regarding power meter-based training: (a) functional threshold testing is closely related to laboratory markers of steady state; (b) the 20-min protocol represents the most researched option for functional threshold testing, although shorter durations may be used if verified on an individual basis; (c) power profiling obtained through the recovery of recorded power outputs allows the categorization and assessment of the cyclist’s fitness level; and (d) power meters represent an alternative to laboratory tests for the assessment of the relationship between power output and cadence. This review elucidates the increasing amount of studies related to power profiling, functional threshold testing, and performance assessment based on power meter data, highlighting the opportunity for the expanding knowledge that power meters have brought in the road cycling field.

Seasonal Training Load Quantification and Comparison in College Male Soccer Players.

Ryan, GA, Snarr, RL, Eisenman, ML, and Rossi, SJ. Seasonal training load quantification and comparison in college male soccer players. J Strength Cond Res 36(4): 1038-1045, 2022-Monitoring and quantification of training load (TL) throughout a competitive soccer season is important to ensure players are able to perform throughout the season. The intent of this study was to examine the positional demands and patterns of select measures of TL during a 14-week season in collegiate male soccer players. Heart rate (HR), running performance (SZ), and perceived recovery data were collected daily using a bioharness for each subject (n = 21). Data were grouped into 2- to 3-week training blocks (Pre1, Pre2, In1, In2, In3, and In4). Continuous variables were analyzed using a multivariate analysis of variance, with post hoc Least Squared Difference pairwise comparisons. Significant positional differences were observed across the season. During Pre1, center midfielders (CM) spent more time in %HRlow compared to center backs (CB) (p < 0.01), wide midfielders (p < 0.01), and center forwards (p = 0.04). Center midfielders spent greater time in SZlower than CB (p < 0.01) and wide backs (WB) (p = 0.01). Wide backs spent greater time in SZupper compared to other positions (all p < 0.01). During Pre2, WB spent more time in %HRhigh and SZupper compared to other positions (all p < 0.01). Positional differences were more varied throughout in-season comparisons, but generally, WB and CB demonstrated higher intensities in variables compared to other positions. Tracking variations in positional TLs across the season is important for coaching and training staffs to determine player readiness and plan future training sessions, while helping to mitigate overuse injuries during a long competitive season.

The impact of different training load quantification and modelling methodologies on performance predictions in elite swimmers

The use of rolling averages to analyse training data has been debated recently. We evaluated two training load quantification methods (five-zone, seven-zone) fitted to performances over two race distances (50 and 100 m) using four separate longitudinal models (Banister, Busso. rolling averages and exponentially weighted rolling averages) for three swimmers ranked in the top 8 in the world. A total of 1610 daily load measures and 108 performances were collected. Banister (standard error of the estimate (SEE) 0.64 and 0.62 s; five-zone and seven-zone quantification methods), Busso (SEE 0.73 and 0.70 s) and exponentially weighted rolling averages (SEE 0.57 and 0.63 s) models fitted more accurately (p < 0.001) than the rolling averages approach (SEE 1.32 and 1.36 s). The seven-zone quantification method did not produce more accurate performance predictions than the five-zone method, despite being a more detailed form of training load quantification. Four neural network models were fitted and had a lower error (SEE 0.38, 0.41, 0.35 and 0.60 s) than all longitudinal models, but did not track as predictably over time. Exponentially weighted impulse–response models and exponentially weighted rolling averages appear more effective at predicting performance using training load data in elite swimmers than a rolling averages approach.

Positional Differences in Peak- and Accumulated- Training Load Relative to Match Load in Elite Football.

Quantification of training and match load is an important method to personalize the training stimulus’ prescription to players according to their match demands. The present study used time-motion analysis and triaxial-accelerometer to quantify and compare: a) The most demanding passages of play in training sessions and matches (5-min peaks); b) and the accumulated load of typical microcycles and official matches, by playing position. Players performance data in 15 official home matches and 11 in-season microcycles were collected for analysis. Players were divided into four different playing positions: Centre-backs, wing-backs, centre midfielders, and centre forwards. The results show that match demands were overperformed for acceleration counts (acccounts) (131%–166%) and deceleration counts (deccounts) (108%–134%), by all positions. However, relative to match values, training values for sprint distance (sprintdist) and high-intensity run distance (HIRdist) were considerably lower (36%–61% and 57%–71%) than for accelerations and decelerations. The most pronounced difference on the 5-min peaks was observed in sprints (sprintpeak), with wing-backs achieving during the microcycle only 64% of the sprintpeak in matches, while centre backs, centre midfielders, and centre forwards levelled and overperformed the match values (107%, 100%, and 107%, respectively). Differences observed across playing positions in matches and microcycles underline the lack of position specificity of common training drills/sessions adopted by coaches in elite football.

The prevention of overtraining with the monitoring training loads: case of football

The aim of this paper is to use a training load quantification tool (RPE) to evaluate if the training load programmed by the coach is appropriate to the characteristics of these footballers. The study was conducted at the football section of the Sale Sports Association, Morocco, on a sample of 8 football players who practice in the club of the Association, aged between 18 and 21 years, the study was established during a mesocycle in a period from 18/03/2019 to 20/04/2019. For the quantification of the training load (TL) we chose the (RPE) tool, where each footballer must give his own perception of the effort felt in each training session, taking into consideration also the duration of the session. This will allow us to calculate the intensity of the session estimated, on a scale from 0 to 10. Based on the results of the quantification of training load for the 8 footballers, we note that in the majority of the cases, the acute load (AL) is higher than the chronic load (CL) at the end of each week. On the other hand, for the monotony index (MI) that provides information on the negative adaptations of training and overtraining, we note that it present a high value among the majority of footballers (1.8UA&lt;2.1UA). For the average of the ratio of the training load: acute/chronic, we note that for the first three footballers the training loads are higher compared to the others. The monitoring training load help to better conceptualize the adaptations of the athlete to the training, and also allows the prediction of the performance.

Training monitoring in professional Australian football: theoretical basis and recommendations for coaches and scientists

ABSTRACTAustralian football (AF) is a high-intensity field-based sport with regular collisions and intense physical demands such as jumping, tackling and jostling, resulting in neuromuscular fatigue and soreness, combined with external stressors (i.e., sponsorship, education, family). These can influence an athlete’s fatigue and recovery status, requiring an individualised approach to monitoring to optimise training readiness. Optimal readiness would reflect a condition where an athlete has no impairment of physical performance, no mental fatigue or excessive psychological distress. A theoretical framework exists for athlete monitoring that includes the quantification of training load and understanding individual ability to tolerate the training demands imposed by coaches. However, while this approach is thought to ultimately determine the readiness of a player for training and competition, it has not been tested empirically. The purpose of this review is to describe the theoretical basis that underpins athlete monitoring systems, and to provide an overview of their contribution to decision-making processes in planning and delivery of training in professional AF players. This review can assist coaches and scientists to gain a better understanding of commonly used monitoring measures and how the information derived from these sources is applied in a professional AF environment.

In-season internal and external training load quantification of an elite European soccer team.

Elite soccer teams that participate in European competitions need to have players in the best physical and psychological status possible to play matches. As a consequence of congestive schedule, controlling the training load (TL) and thus the level of effort and fatigue of players to reach higher performances during the matches is therefore critical. Therefore, the aim of the current study was to provide the first report of seasonal internal and external training load that included Hooper Index (HI) scores in elite soccer players during an in-season period. Nineteen elite soccer players were sampled, using global position system to collect total distance, high-speed distance (HSD) and average speed (AvS). It was also collected session rating of perceived exertion (s-RPE) and HI scores during the daily training sessions throughout the 2015–2016 in-season period. Data were analysed across ten mesocycles (M: 1 to 10) and collected according to the number of days prior to a one-match week. Total daily distance covered was higher at the start (M1 and M3) compared to the final mesocycle (M10) of the season. M1 (5589m) reached a greater distance than M5 (4473m) (ES = 9.33 [12.70, 5.95]) and M10 (4545m) (ES = 9.84 [13.39, 6.29]). M3 (5691m) reached a greater distance than M5 (ES = 9.07 [12.36, 5.78]), M7 (ES = 6.13 [8.48, 3.79]) and M10 (ES = 9.37 [12.76, 5.98]). High-speed running distance was greater in M1 (227m), than M5 (92m) (ES = 27.95 [37.68, 18.22]) and M10 (138m) (ES = 8.46 [11.55, 5.37]). Interestingly, the s-RPE response was higher in M1 (331au) in comparison to the last mesocycle (M10, 239au). HI showed minor variations across mesocycles and in days prior to the match. Every day prior to a match, all internal and external TL variables expressed significant lower values to other days prior to a match (p<0.01). In general, there were no differences between player positions.Conclusions: Our results reveal that despite the existence of some significant differences between mesocycles, there were minor changes across the in-season period for the internal and external TL variables used. Furthermore, it was observed that MD-1 presented a reduction of external TL (regardless of mesocycle) while internal TL variables did not have the same record during in-season match-day-minus.

Effect of Training Load Distribution on Aerobic Fitness Measures in Hurling Players

Malone, S, Hughes, B, and Collins, K. Effect of training load distribution on aerobic fitness measures in hurling players. J Strength Cond Res 33(3): 825-830, 2019-The aim of the current investigation was to quantify the training intensity distribution of hurling players and their association with changes in aerobic fitness measures within hurling players. Thirty hurling players (n = 30; age 26.5 ± 3.2 years; height 178.9 ± 3.2 cm; body mass 81.5 ± 4.5 kg) were observed during the pre-championship training period (12 weeks). Aerobic fitness measures (V[Combining Dot Above]O2max), peak treadmill velocity (km·h), heart rates (HRs) at 2 and 4 mmol·L blood lactate concentrations, and Yo-Yo intermittent recovery test performance (Yo-YoIR1) were assessed before and after the training period. Training intensities were categorized using 3 individualized HR zones based on the following criteria: low intensity (≤HR 2 mmol·L), moderate intensity (between HR 2 and 4 mmol·L), and high intensity (≥HR 4 mmol·L). Analysis of 1,025 individual training sessions showed that players spent 58.1 ± 2.5%, 24.3 ± 2.9%, and 17.6 ± 1.3% of time in the low-, moderate-, and high-intensity zones, respectively. The training time spent at high intensity (Zone 3) showed moderate-to-large associations with improvements in S2 (r = 0.80; p = 0.04) and S4 (r = 0.58; p = 0.03). Similar trends were observed for time spent in high intensity and improvements in V[Combining Dot Above]O2max (r = 0.77; p = 0.001) and Yo-YoIR1 performance (r = 0.65; p = 0.05). Hurling players have been shown to spend the majority of training time in low (≤ HR 2 mmol·L) to moderate intensity (between HR 2 and 4 mmol·L) training. 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. The study also supports the efficacy of spending elements of training time within the high-intensity zone to increase hurling player's aerobic fitness characteristics.

Measuring Training Load in Dance: The Construct Validity of Session-RPE.

The session rating of perceived exertion (session-RPE) is a practical and non-invasive method that allows a quantification of internal training load (ITL) in individual and team sports. As yet, no study has investigated its construct validity in dance. This study examines the convergent validity between the session-RPE method and an objective heart rate (HR)-based method of quantifying the similar ITL in vocational dance students during professional dance training. Ten dance students (4 male, 20±1.16 yrs; 6 female, 20±0.52 yrs) participated in this study. During a normal week of training, session-RPE and HR data were recorded in 96 individual sessions. HR data were analysed using Edwards-TL method. Correlation analysis was used to evaluate the convergent validity between the session-RPE and Edwards-TL methods for assessing ITL in a variety of training modes (contemporary, ballet, and rehearsal). The overall correlation between individual session-RPE and Edwards-TL was r=0.72, p<0.0001, suggesting there was a statistically significantly strong positive relationship between session-RPE and Edwards-TL. This trend was observed across all the training modes: rehearsal sessions (r=0.74, p=0.001), contemporary (r=0.60, p=0.001), and ballet (r=0.46, p=0.018) sessions. This study shows that session-RPE can be considered as a valid method to assess ITL for vocational dance students, and that notably there is some variation between session-RPE and HR-based TL in different dance activities.

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.