A Comparison of Methods to Quantify the In-Season Training Load of Professional Soccer Players
01 Mar 2013-International Journal of Sports Physiology and Performance (Int J Sports Physiol Perform)-Vol. 8, Iss: 2, pp 195-202
TL;DR: Comparing various measures of training load derived from physiological, perceptual, and physical data during in-season field-based training for professional soccer suggests physical-performance measures of TD, LSA volume, and player load appear to be more acceptable indicators of external TL.
Abstract: Purpose: 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. Methods: 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], 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. Results: 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. Conclusions: 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.
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01 Jan 2007
TL;DR: This study has provided an indication of the different physical demands of different playing positions in FA Premier League match-play through assessment of movements performed by players.
Abstract: The purpose of this study was to evaluate the physical demands of English Football Association (FA) Premier League soccer of three different positional classifications (defender, midfielder and striker). Computerised time-motion video-analysis using the Bloomfield Movement Classification was undertaken on the purposeful movement (PM) performed by 55 players. Recognition of PM had a good inter-tester reliability strength of agreement (κ = 0.7277). Players spent 40.6 ± 10.0% of the match performing PM. Position had a significant influence on %PM time spent sprinting, running, shuffling, skipping and standing still (p 0.05). Players spent 48.7 ± 9.2% of PM time moving in a directly forward direction, 20.6 ± 6.8% not moving in any direction and the remainder of PM time moving backward, lateral, diagonal and arced directions. The players performed the equivalent of 726 ± 203 turns during the match; 609 ± 193 of these being of 0° to 90° to the left or right. Players were involved in the equivalent of 111 ± 77 on the ball movement activities per match with no significant differences between the positions for total involvement in on the ball activity (p > 0.05). This study has provided an indication of the different physical demands of different playing positions in FA Premier League match-play through assessment of movements performed by players.
637 citations
TL;DR: Higher workloads can have either positive or negative influences on injury risk in elite rugby league players, and players with a high chronic workload are more resistant to injury with moderate-low through moderate-high (0.85–1.35) acute:chronic workload ratios and lessresistant to injury when subjected to ‘spikes’ in acute workload.
Abstract: Aim Investigate whether acute workload (1 week total distance) and chronic workload (4-week average acute workload) predict injury in elite rugby league players. Methods Data were collected from 53 elite players over two rugby league seasons. The 'acute:chronic workload ratio' was calculated by dividing acute workload by chronic workload. A value of greater than 1 represented an acute workload greater than chronic workload. All workload data were classified into discrete ranges by z-scores. Results Compared with all other ratios, a very-high acute:chronic workload ratio (2.11) demonstrated the greatest risk of injury in the current week (16.7% injury risk) and subsequent week (11.8% injury risk). High chronic workload (>16 095 m) combined with a veryhigh 2-week average acute:chronic workload ratio (1.54) was associated with the greatest risk of injury (28.6% injury risk). High chronic workload combined with a moderate workload ratio (1.02-1.18) had a smaller risk of injury than low chronic workload combined with several workload ratios (relative risk range from 0.3 to 0.7×/1.4 to 4.4; likelihood range=88-94%, likely). Considering acute and chronic workloads in isolation (ie, not as ratios) did not consistently predict injury risk. Conclusions Higher workloads can have either positive or negative influences on injury risk in elite rugby league players. Specifically, compared with players who have a low chronic workload, players with a high chronic workload are more resistant to injury with moderate-low through moderate-high (0.85-1.35) acute:chronic workload ratios and less resistant to injury when subjected to 'spikes' in acute workload, that is, very-high acute:chronic workload ratios 1.5.
380 citations
TL;DR: A systematic review of studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes and indications on the reliability of sensor-based performance indicators are provided.
Abstract: Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends.
314 citations
Cites background from "A Comparison of Methods to Quantify..."
...• quantifying physical and technical demands for a specific sport (aerial skiing [175], American football [317], Australian football [259], mixed martial arts [165,182], rugby [130], soccer [109,249,277]) • assessing the effect of playing position (American football [317], Australian Football [73,137,178], handball [210], netball [86,99], rugby [128,130], rugby sevens [296], soccer [152,277]), playing level (elite and sub elite: Australian Football [73], soccer [109,277]), numerical advantage (soccer [235]), playing time [311], playing standard (Australian Football [98], badminton [113], rugby [129,131]), and age group (tennis [163]) • characterising successful teams (rugby [127,129]) • assessing the effect of match score on activity profile and skill performance (Australian football [298])...
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...• determining how external load measures and skill performance contribute to coaches’ perceptions of performance (Australian football [299]) and how these vary between matches (Australian football [178]) • assessing the contribution of running to external load, through a correlation analysis of distance covered (field hockey [253]) • assessing the number of collisions and repeated high-intensity efforts [128] • assessing differences between different training conditions (rugby [133]) and with competition demands (Australian Football [73], mixed martial arts [183], netball [86], rugby [134], soccer [277]) • determining the best load assessment according to training mode (rugby [316]) • investigating agility demands of small-sided games (Australian football [111]), and closed drills [60] • inferring information about internal load (soccer [144]) • assessing the impact of playing experience on internal load, as estimated through the external load [137] • assessing fatigue, from training sessions (rugby [133]), from consecutive days of match play (tennis [145]), and in real time (soccer [66])....
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..., session rating of perceived exertion) to monitor an individual’s response to the training dose [137,144,175,182,208,259,277,316]....
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...Gaelic football [245], netball [86,99], rugby [101,102,127–135,176,208,225,226,297,311,312,316], rugby sevens [296], soccer [66,109,144,152,235,249,277], aerial skiing [175], and tennis [163]....
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TL;DR: A new theoretical framework is proposed in which physiological and biomechanical load-adaptation pathways are considered separately, shedding new light on some of the previously published evidence and can help practitioners and researchers design experiments that can better rationalize training-load monitoring.
Abstract: There have been considerable advances in monitoring training load in running-based team sports in recent years. Novel technologies nowadays offer ample opportunities to continuously monitor the activities of a player. These activities lead to internal biochemical stresses on the various physiological subsystems; however, they also cause internal mechanical stresses on the various musculoskeletal tissues. Based on the amount and periodization of these stresses, the subsystems and tissues adapt. Therefore, by monitoring external loads, one hopes to estimate internal loads to predict adaptation, through understanding the load-adaptation pathways. We propose a new theoretical framework in which physiological and biomechanical load-adaptation pathways are considered separately, shedding new light on some of the previously published evidence. We hope that it can help the various practitioners in this field (trainers, coaches, medical staff, sport scientists) to align their thoughts when considering the value of monitoring load, and that it can help researchers design experiments that can better rationalize training-load monitoring for improving performance while preventing injury.
292 citations
Cites background or result from "A Comparison of Methods to Quantify..."
...values to monitor training load in season and between matches [34, 35], and some studies determined typical profiles in various team sports [34, 36–39]....
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...In fact, this was recognized in three papers where, based on the poor relationship, it was suggested that accumulated accelerometer-based outcomes such as PlayerLoad measure a different construct of the training process than internal physiological loadmeasures such as RPE or HR [35, 38, 42]....
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TL;DR: The authors provide the 1st report of seasonal training load in elite soccer players and observed that periodization of training load was typically confined toMD-1 (regardless of mesocycle), whereas no differences were apparent during MD-2 to MD-5, although no difference was apparent between these latter time points.
Abstract: Purpose: To quantify the seasonal training load completed by professional soccer players of the English Premier League. Methods: Thirty players were sampled (using GPS, heart rate, and rating of perceived exertion [RPE]) during the daily training sessions of the 2011–12 preseason and in-season period. Preseason data were analyzed across 6 × 1-wk microcycles. In-season data were analyzed across 6 × 6-wk mesocycle blocks and 3 × 1-wk microcycles at start, midpoint, and end-time points. Data were also analyzed with respect to number of days before a match. Results: Typical daily training load (ie, total distance, high-speed distance, percent maximal heart rate [%HRmax], RPE load) did not differ during each week of the preseason phase. However, daily total distance covered was 1304 (95% CI 434–2174) m greater in the 1st mesocycle than in the 6th. %HRmax values were also greater (3.3%, 1.3–5.4%) in the 3rd mesocycle than in the first. Furthermore, training load was lower on the day before match (MD-1) than 2 (MD-2) to 5 (MD-5) d before a match, although no difference was apparent between these latter time points. Conclusions: The authors provide the 1st report of seasonal training load in elite soccer players and observed that periodization of training load was typically confined to MD-1 (regardless of mesocycle), whereas no differences were apparent during MD-2 to MD-5. Future studies should evaluate whether this loading and periodization are facilitative of optimal training adaptations and match-day performance.
287 citations
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01 Dec 1969TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
Abstract: Contents: Prefaces. The Concepts of Power Analysis. The t-Test for Means. The Significance of a Product Moment rs (subscript s). Differences Between Correlation Coefficients. The Test That a Proportion is .50 and the Sign Test. Differences Between Proportions. Chi-Square Tests for Goodness of Fit and Contingency Tables. The Analysis of Variance and Covariance. Multiple Regression and Correlation Analysis. Set Correlation and Multivariate Methods. Some Issues in Power Analysis. Computational Procedures.
115,069 citations
49,129 citations
TL;DR: It is concluded that the session RPE method is a valid method of quantitating exercise training during a wide variety of types of exercise and may provide a tool to allow the quantitative evaluation of training periodization plans.
Abstract: The ability to monitor training is critical to the process of quantitating training periodization plans. To date, no method has proven successful in monitoring training during multiple types of exercise. High-intensity exercise training is particularly difficult to quantitate. In this study we evaluate the ability of the session rating of perceived exertion (RPE) method to quantitate training during non-steady state and prolonged exercise compared with an objective standard based on heart rate (HR). In a 2-part design, subjects performed steady state and interval cycle exercise or practiced basketball. Exercise bouts were quantitated using both the session RPE method and an objective HR method. During cycle exercise, the relationship between the exercise score derived using the session RPE method and the HR method was highly consistent, although the absolute score was significantly greater with the session RPE method. During basketball, there was a consistent relationship between the 2 methods of monitoring exercise, although the absolute score was also significantly greater with the session RPE method. Despite using different subjects in the 2 parts of the study, the regression relationships between the session RPE method and the HR method were nearly overlapping, suggesting the broad applicability of this method. We conclude that the session RPE method is a valid method of quantitating exercise training during a wide variety of types of exercise. As such, this technique may hold promise as a mode and intensity-independent method of quantitating exercise training and may provide a tool to allow the quantitative evaluation of training periodization plans.
2,280 citations
TL;DR: Top-class soccer players performed more high-intensity running during a game and were better at the Yo-Yo test than moderate professional players; fatigue occurred towards the end of matches as well as temporarily during the game, independently of competitive standard and of team position; defenders covered a shorter distance in high- intensity running than players in other playing positions.
Abstract: The aim of this study was to assess physical fitness, match performance and development of fatigue during competitive matches at two high standards of professional soccer. Computerized time-motion analyses were performed 2-7 times during the competitive season on 18 top-class and 24 moderate professional soccer players. In addition, the players performed the Yo-Yo intermittent recovery test. The top-class players performed 28 and 58% more (P < 0.05) high-intensity running and sprinting, respectively, than the moderate players (2.43 +/- 0.14 vs 1.90 +/- 0.12 km and 0.65 +/- 0.06 vs 0.41 +/- 0.03 km, respectively). The top-class players were better (11%; P < 0.05) on the Yo-Yo intermittent recovery test than the moderate players (2.26 +/- 0.08 vs 2.04 +/- 0.06 km, respectively). The amount of high-intensity running, independent of competitive standard and playing position, was lower (35-45%; P < 0.05) in the last than in the first 15 min of the game. After the 5-min period during which the amount of high-intensity running peaked, performance was reduced (P < 0.05) by 12% in the following 5 min compared with the game average. Substitute players (n = 13) covered 25% more (P < 0.05) ground during the final 15 min of high-intensity running than the other players. The coefficient of variation in high-intensity running was 9.2% between successive matches, whereas it was 24.8% between different stages of the season. Total distance covered and the distance covered in high-intensity running were higher (P < 0.05) for midfield players, full-backs and attackers than for defenders. Attackers and full-backs covered a greater (P < 0.05) distance in sprinting than midfield players and defenders. The midfield players and full-backs covered a greater (P < 0.05) distance than attackers and defenders in the Yo-Yo intermittent recovery test (2.23 +/- 0.10 and 2.21 +/- 0.04 vs 1.99 +/- 0.11 and 1.91 +/- 0.12 km, respectively). The results show that: (1) top-class soccer players performed more high-intensity running during a game and were better at the Yo-Yo test than moderate professional players; (2) fatigue occurred towards the end of matches as well as temporarily during the game, independently of competitive standard and of team position; (3) defenders covered a shorter distance in high-intensity running than players in other playing positions; (4) defenders and attackers had a poorer Yo-Yo intermittent recovery test performance than midfielders and full-backs; and (5) large seasonal changes were observed in physical performance during matches.
1,859 citations
TL;DR: The results of this study show that the session-RPE can be considered a good indicator of global internal load of soccer training and can be very useful and practical for coaches and athletic trainer to monitor and control internal load, and to design periodization strategies.
Abstract: Purpose The ability to accurately control and monitor internal training load is an important aspect of effective coaching. The aim of this study was to apply in soccer the RPE-based method proposed by Foster et al. to quantify internal training load (session-RPE) and to assess its correlations with various methods used to determine internal training load based on the HR response to exercise. Methods Nineteen young soccer players (mean +/- SD: age 17.6 +/- 0.7 yr, weight 70.2 +/- 4.7 kg, height 178.5 +/- 4.8 cm, body fat 7.5 +/- 2.2%, VO2max, 57.1 +/- 4.0 mL x kg x min) were involved in the study. All subjects performed an incremental treadmill test before and after the training period during which lactate threshold (1.5 mmol x L above baseline) and OBLA (4.0 mmol x L) were determined. The training loads completed during the seven training weeks were determined multiplying the session RPE (CR10-scale) by session duration in minutes. These session-RPE values were correlated with training load measures obtained from three different HR-based methods suggested by Edwards, Banister, and Lucia, respectively. Results Individual internal loads of 479 training sessions were collected. All individual correlations between various HR-based training load and session-RPE were statistically significant (from r = 0.50 to r = 0.85, P Conclusion The results of this study show that the session-RPE can be considered a good indicator of global internal load of soccer training. This method does not require particular expensive equipment and can be very useful and practical for coaches and athletic trainer to monitor and control internal load, and to design periodization strategies.
1,013 citations