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GPS and Injury Prevention in Professional Soccer
Abstract
This study investigated the relationship between GPS variables measured in training and gameplay and injury occurrences in professional soccer. Nineteen professional soccer players competing in the Australian Hyundai A-League were monitored for one entire season using 5Hz Global Positioning System (GPS) units (SPI-Pro GPSports, Canberra, Australia) in training sessions and pre-season games. The measurements obtained were Total Distance, High Intensity Running Distance, Very High Intensity Running Distance, New Body Load and Metres per Minute. Non-contact soft tissue injuries were documented throughout the season. Players' seasons were averaged over one and four week blocks according to when injuries occurred. These blocks were compared to each other and to players' seasonal averages. Players performed significantly higher Metres per Minute in the weeks preceding an injury compared to their seasonal averages (+9.6 % and +7.4 % for one and four week blocks respectively) (p<0.01), indicating an increase in training and gameplay intensity leading up to injuries. Furthermore, injury blocks showed significantly lower average New Body Load compared to seasonal averages (-15.4 % and -9.0 % for one and four week blocks respectively) (p<0.01 and p=0.01). Periods of relative under-preparedness could potentially leave players unable to cope with intense bouts of high intensity efforts during competitive matches. Although limited by FIFA regulations, the results of this study isolated two variables predicting soft tissue injuries for coaches and sports scientist to consider when planning and monitoring training.
... Figure 1: Significant difference between meters per minute before injury and the season average. Each block represents a 4-week data collection period [3] According to a report from the Department of Health Science, Australian Catholic University Sydney, by ana-lyzing GPS data of players it was possible to detect characteristics of players in connection with injuries. ...
... In the weeks leading up to an injury, players covered significantly more meters per minute compared to their seasonal averages, suggesting an increase in training and gameplay intensity [3]. ...
... Therefore the system is only capable of analyzing the own players with an invisible opponent team, which leads to the result that injuries caused by opponent players is an additional factor we can not predict. Again, the report from the "Journal of Strength and Conditioning Research" delivers helpful informations [3]. 59% of injuries occur without contact with other players. ...
... Research showed that injury incidence is roughly five times higher during competition than training, therefore emphasizing the importance of distinguishing levels of load for similar exposure (Bowen et al., 2020;Drew & Finch, 2016;Ekstrand, 2008;Ekstrand et al., 2011aEkstrand et al., , 2011bJaspers et al., 2018). Thus, external load during training and competition sessions became of importance in order to avoid the development of injuries (Bowen et al., 2020;Ehrmann et al., 2016;Enright et al., 2020;Jaspers et al., 2018;Nobari et al., 2021;Suarez-Arrones et al., 2020). The next step was to connect injury characteristics and incidence with external load exposure of the players (Drew & Finch, 2016). ...
... The next step was to connect injury characteristics and incidence with external load exposure of the players (Drew & Finch, 2016). There has been a constant effort from sport scientists to assess the association between the key performance indicators (KPIs) of external load and injuries (Bowen et al., 2020;Ehrmann et al., 2016;Enright et al., 2020;Jaspers et al., 2018;Nobari et al., 2021;Suarez-Arrones et al., 2020). Unfortunately, many aspects of the relationship between load and injury, such as magnitude and timing, remain unclear. ...
... Res. 3(1);10-25 (2024) the relationship between external load and injury incidence (Ehrmann et al., 2016;Jaspers et al., 2018;Nobari et al., 2021). ...
Background: Elite football players are monitored daily to minimize injury risks and maximize performance. Objectives: The aim of the study was to investigate injury incidence differences between competition and training and differences in key external load indicators during 1-, 2-, 3- or 4-weeks prior to the injury (WPI) with respect to the season average week (SAW). Methods: Data of 224 unique players of five teams (1st, under-23, under-18, under-17, and under-16) were collected during 3.5 seasons of competition and training resulting in 467 player records in total. Collected data included kinematics from Global Positioning System tracking units (Viper Units, STATSports) and 528 injury incident records. External load was expressed in terms of acceleration counts (ACC), deceleration counts (DEC), total training time (TT), total distance (TD), and distance covered in high-speed zones: 14.4-19.7 km/h (Z4), 19.7-25.1 km/h (Z5), and >25.1 km/h (Z6). Injury incidence was derived as number of injuries per 1000 hours of exposure. Results: Incidence rate was on average 4-11 times higher during competition than training for all teams except under-16 (incidence rate: 2.5, p=.153). In the 1st Team, external load (i.e. ACC, TT, and TD) were significantly different between 1-, 2-, 3-, and 4-WPI and SAW (p=.041, p=.037, and p=.049 respectively). For ACC and TT, the 3-WPI loads, were significantly higher than during SAW (p=.044 and p=.038, respectively). Conclusion: These findings can assist professionals and scientists to improve their understanding of the relationship between external load indicators and injury incidence and consequently improve player health and performance.
... In agreement with those results, many other team-sport investigations indicated significant correlations between sRPE load and injury occurrences (49,50,78,81,82 HSR (58,64,72) were the mostly significantly correlated variables with noncontact injury incidences. On the other hand, four studies did not indicate any significant association between non-contact injury incidences with TDC (61,63,64,71) and HSR (59,61,63,71). The reason for HSR not to be significantly associated with non-contact injury risks could be the fact that utilizing fixed threshold speeds rather than individualized threshold decreases the sensitivity of the outcome of the results (83). ...
... In agreement with those results, many other team-sport investigations indicated significant correlations between sRPE load and injury occurrences (49,50,78,81,82 HSR (58,64,72) were the mostly significantly correlated variables with noncontact injury incidences. On the other hand, four studies did not indicate any significant association between non-contact injury incidences with TDC (61,63,64,71) and HSR (59,61,63,71). The reason for HSR not to be significantly associated with non-contact injury risks could be the fact that utilizing fixed threshold speeds rather than individualized threshold decreases the sensitivity of the outcome of the results (83). ...
... The reason for HSR not to be significantly associated with non-contact injury risks could be the fact that utilizing fixed threshold speeds rather than individualized threshold decreases the sensitivity of the outcome of the results (83). Additionally, Ehrmann et al. (71) found that a higher covered MpM augments soft-tissue non-contact injury incidences in the same week whereas another included study (64) showed that an increased HSR and VHSR are more likely to enhance non-contact injury risk two-week later rather than the present week, as opposed to the finding of Ehrmann et al. Further, Windt et al. (84) showed that rugby players were at heightened risk of injury during the same and the following week when they increased the weekly percentage of HSR-TDC. ...
A systematic review investigating the relationship between training load variables and non-contact injury incidence in soccer players
... In particular, although the present paper included exposure times and running performance during matches, others collected training data 21 or a combination of training and match data. 8 In addition, the current paper is specific for hamstring muscle injury which is an injury with a higher risk of happening during high-intensity actions in competition, whereas previous studies analyzed all types of muscle injuries sustained, including sometimes poorly associated with high-intensity running. 8,21 Concerning accumulated volumes of high-speed running distances, the current study reveals lower cumulative high-speed running distances (>24 km/h) in the 1 and 2 matches before the injury occurred (Table 1). ...
... 8 In addition, the current paper is specific for hamstring muscle injury which is an injury with a higher risk of happening during high-intensity actions in competition, whereas previous studies analyzed all types of muscle injuries sustained, including sometimes poorly associated with high-intensity running. 8,21 Concerning accumulated volumes of high-speed running distances, the current study reveals lower cumulative high-speed running distances (>24 km/h) in the 1 and 2 matches before the injury occurred (Table 1). In contrast, running metrics for the 3 to 4 previous matches had no significance to explain hamstring injury risk, suggesting that underexposure has not to be maintained long in time to produce a deleterious effect on the player's likelihood to suffer a hamstring strain. ...
Background:
Hamstring strain injuries are one of the most prevalent injuries in football (soccer). We examined the influence of accumulated match-play exposure on the occurrence of hamstring strain injury in professional football from 2 teams (Spanish 1st Division, LaLiga) over 3 seasons, and determined specific cut-off points as indicators of injury risk.
Hypothesis:
Overloaded players would be more likely to sustain a hamstring injury.
Study design:
Prospective, controlled, observational study.
Level of evidence:
Level 2b.
Methods:
Playing time, total running distance, and high-speed running (>24 km/h) distance during official matches of players that sustained a hamstring injury were compared with uninjured, paired controls. Cumulative playing time and running performance of 4 matches before the injury was computed. Relative risk (RR) of injury occurrence was estimated by generalized estimating equations. Diagnostic accuracy was determined by receiver operating characteristics and the area under the curve.
Results:
Thirty-seven hamstring strain injuries occurred, representing 23 ± 18 absence days per injury. Thirty-seven controls (uninjured players) were used as comparators. Low match-play exposures during 1 and 2 matches before injury were likely to explain injury occurrence (RR: 14-53%; P < 0.01). Metrics from the match before the hamstring muscle strain demonstrated the best accuracy to predict injury occurrence: high-speed running distance ≤328 m (sensitivity, 64%; specificity, 84%), playing time ≤64 min (sensitivity, 36%; specificity, 97%), and running distance ≤5.8 km (sensitivity, 39%; specificity, 97%).
Conclusion:
Relatively reduced competitive exposure in the previous 2 matches was associated with higher hamstring injury risk in professional football players.
Clinical relevance:
Screening simple metrics such as the accumulated match exposure during official matches and considering specific cut-off points for some running variables may be good indicators of injury risk and may assist in better individual injury management in professional soccer players.
... Systems like GPS trackers, optical tracking systems, and wearables have revolutionized player movement monitoring and analysis (Baysal and Duygulu, 2016;Csanalosi et al., 2020). Player tracking aids in performance analysis and plays a vital role in injury prevention and rehabilitation by identifying risky movement patterns and managing workloads (Ehrmann et al., 2016;Khaustov and Mozgovoy, 2020). Motion vectors, a crucial component of video compression technologies, represent the motion of pixel blocks between consecutive frames in a video sequence (Xu et al., 2016;Furht et al., 1997; ITU-T, Figure 1: Comparison of HOTA (top row) and MOTA (bottom row) for both the MOT17 (left column) and MOT20 (right column) datasets (X-axis: IDF 1 ; see Sec. 4.3 for a description of these metrics) with the state-of-the-art (OC-Sort (Cao et al., 2023), ByteTrack (Zhang et al., 2022), BoT-Sort (Aharon et al., 2022), StrongSort (Du et al., 2023), and MotionTrack (Qin et al., 2023). ...
... The results obtained from the search were organized into categories according to the main topics covered. (Ehrmann et al., 2016), thereby enabling analyses of related data, such as total distance traveled, distances covered at different speeds, and number of accelerations and decelerations . This performance indicator allows the quantification of the external load to which the athlete is subjected and its accumulation throughout the macrocycle of training programming; in this way, sports injuries can be minimized (Bowen et al., 2017), and the level of performance that each athlete shows throughout the competitive season can be verified. ...
... Therefore, previous research determined that large weekly changes in HSR distance and sprint distance increase the injury risk; however, in this study, no significant differences were found in any variables between the injury and pre-injury blocks for 7-day time windows (Malone et al., 2018). Similar analyses were developed by Ehrmann et al. (2016) who compared the injury block for two-time windows (1 and 4 weeks) with the season average load. No significant differences were found for the variables TD, HSR, and very high-intensity running (sprint distance), whereas in this study we showed significant differences in these variables in the 28-day time window. ...
Background
This study aims to investigate how accumulated training load over different time windows (7, 14, and 28 days) influences the incidence of hamstring injuries in elite football players.
Methods
A descriptive and longitudinal study was developed in 343 players in three teams (2nd Team, U-19 team, and U-18 team) from the academy of an elite football club in Spanish La Liga that also competed in the Union of European Football Associations Champions League during four seasons, from 2017/18 to 2020/21. External load variables (total distance, high-speed running, accelerations, etc.) for training and competition have been studied considering the volume variables during three different time windows along the different seasons (7 days, 14 days, and 28 days).
Results
Results did not show differences in the shortest time windows (7- and 14-week periods), showing that strength and conditioning coaches should analyse longer periods of time and compare them to previous periods with the same length in order to improve workload management and reduce injury risk.
Conclusions
It is important consider the accumulated load (chronic) in periods of 28 days to avoid an increase that generates a hamstring injury. The control of the training load in blocks of 28-day time windows seems essential to minimize the injury rate in football players.
... Las variables mecánicas se refieren a los esfuerzos neuromusculares que implican aceleraciones, desaceleraciones, cambios de dirección o saltos (Beenham et al., 2017). La cuantificación de estas variables contribuye a un análisis pormenorizado del desempeño de los futbolistas y así controlar las cargas de las diferentes sesiones entre partidos, optimizando el rendimiento y pudiendo prevenir lesiones (Ehrmann et al., 2016). ...
RESUMEN Este estudio describe las demandas de carga física en jugadores juveniles de fútbol argentino en partidos oficiales, analizándolas por posición y división. Se tomaron datos de divisiones inferiores del Club Atlético Vélez Sarsfield, perteneciente a la máxima categoría del fútbol argentino. Se consideraron aquellos jugadores que completaron la totalidad del partido (186 jugadores en 114 partidos) excluyendo arqueros. Se utilizó GPS Catapult para analizar variables locomotoras (distancia total, distancia total de sprint, distancia total a una velocidad mayor a 19km/h, velocidad máxima) y mecánicas (player load por minuto, aceleración máxima, desaceleración máxima). Se utilizó la prueba no paramétrica Wilcoxon-Test con un nivel de significancia p<0,05. Se encontraron diferencias significativas entre las divisiones más jóvenes y las superiores en la mayoría de las variables, excluyendo las divisiones 8va y 9na debido a diferentes tiempos de juego. Los defensores centrales presentaron los valores más bajos en distancia recorrida y aceleración máxima, mientras que los delanteros centros y extremos mostraron los valores más altos en velocidad máxima. Se observaron diferencias a favor de jugadores argentinos en comparación con datos internacionales. Este estudio proporciona información relevante para personalizar el entrenamiento y optimizar el rendimiento y la prevención de lesiones en el fútbol juvenil argentino. Palabras Clave: fútbol, sistema de posicionamiento global, posiciones de juego, demandas físicas.
... The adoption of GPS technology in football has seen exponential growth, offering a robust means to quantify athletes' workload during both training sessions and matches. This is attributed to its ability to capture locomotion metrics, including accelerations, decelerations, and power (17,18), with longitudinal monitoring proving instrumental in injury prevention (19). However, the low adoption of advanced monitoring tools like GPS among amateur coaches highlights the financial and educational challenges they face. ...
Introduction: The study aimed to describe the practices and perspectives of Czech football coaches regarding the monitoring of players' training load and physical performance, with a focus on identifying key barriers and preferred sources of information. Methods: A total of 235 football coaches completed an online survey comprehending training load monitoring methods, physical performance assessments, barriers to implementation, and information sources. Results: Among respondents, 93.7% reported monitoring training load, with training diaries (70%) being the most utilized method for external load measures and heart rate (45%) for internal load. Despite this, 42.7% of coaches did not monitor internal load and 21.7% did not conduct physical fitness evaluations. The most frequently reported barrier was a lack of resources (74.5%), though elite-level coaches (52.8%) and strength and conditioning coaches (75%) identified human resources as their primary limitation. Across all levels, the Football Association was the preferred source of information (61.7%). Conclusion: The findings highlight the predominance of traditional monitoring practices among the Czech football coaches, alongside with notable gaps in internal load tracking and fitness evaluation. The resource constraints remain a major barrier. Practical recommendations include promoting economical monitoring tools, such as RPE, and enhancing collaboration among stakeholders to improved monitoring strategies. The Football Association's play a key role on support these efforts.
... The results obtained from the search were organized into categories according to the main topics covered. (Ehrmann et al., 2016), thereby enabling analyses of related data, such as total distance traveled, distances covered at different speeds, and number of accelerations and decelerations . This performance indicator allows the quantification of the external load to which the athlete is subjected and its accumulation throughout the macrocycle of training programming; in this way, sports injuries can be minimized (Bowen et al., 2017), and the level of performance that each athlete shows throughout the competitive season can be verified. ...
Training load is a modifiable risk factor for successive injury in soccer. A systematic review observed the relationship between some sprint GPS variables and non-contact injuries in soccer players. Therefore, an inappropriate sprint workload during the season can increase injury risk and reduce performance. The purpose of this study were to analyse the association between the total distance (TD), high-speed distance (HSD), sprint distance (SD) and repeated sprint (RS) with non-contact injuries in elite soccer players during a season and to observe the injury risk associated between high- (HL) vs. low-load (LL) level for each of sprint variables. Twenty-one male players from professional soccer team participated in the study. External load monitoring was performed by GPS at each training and match session over the whole season. All noncontact injuries (that is, occurring without contact with foreign material or athletes) were recorded. Non-parametric Mann–Whitney U tests were used to compare the median of the load levels of the sprint variables. In order to detect statistically significant inter-group differences between the means of injuries at the HL and LL levels of the mentioned variables. To estimate the risk of having a HL level compared to a LL level, respectively, of each variable, odds ratio (OR) and relative risk (RR) were calculated. Mean injuries were significantly higher in the high load weeks compared to the low load weeks for all sprint variables. The OR and RR of producing some injury without contact was significantly higher in the weeks of high load compared to the weeks of low load in all sprint variables. In addition, significant RR were found for all variables except for RS. The weeks of high-load levels increase the risk of sustaining non-contact injury within elite soccer players. TD, HSD, and SPD variables could potentially track training and may allow exercise prescription to reduce non-contact injuries.
... The results obtained from the search were organized into categories according to the main topics covered. (Ehrmann et al., 2016), thereby enabling analyses of related data, such as total distance traveled, distances covered at different speeds, and number of accelerations and decelerations . This performance indicator allows the quantification of the external load to which the athlete is subjected and its accumulation throughout the macrocycle of training programming; in this way, sports injuries can be minimized (Bowen et al., 2017), and the level of performance that each athlete shows throughout the competitive season can be verified. ...
Success in sports will always be the main objective of any team. The process to fulfill it must be judicious. Although this has already been studied be several authors, in the Portuguese context, the data are still scarce. Furthermore, there is still a lack of consensus in the specific metrics and actions on field to predict such success. So, this study´s objective was to analyze the most important factors in the processes that led to goal situations, throughout a Portuguese Football Federation team. The sample consisted of 5 senior athletes with the following characteristics: 28.2±0.75 years of age; BMI 22.62±1.13 kg/m2; 16±4.69 years of experience. The instrument used was the GPS Gpexe LT (Version 2.2.8), obtaining the metrics of total distance, high intensity distance, sprint distance, number of accelerations and decelerations. These metrics were analyzed in 24 games in the variables goal/no goal, 1st/2nd half, game home/away, fast attack/positional attack/counter-attack. The results obtained in the 53 shots where superior within the positional attack (n=31), with only 6 resulting in a goal. The means of all actions analyzed were 71.5±22.5m total distance, 9.1±10.8m distance in high intensity, 5.1±12.3m distance in sprint, 0.36±0.5 acceleration and 0.6±0.7 deceleration. Individualizing the attack methods,
the counterattack seems to be the method where the greatest high intensity distances (14.2±14.4m) and sprint distances (9.8±14.1m) are present. The 1st half showed superior total distances at all intensities (75.3±22.6m total; 10.8±11.9m high intensity; 8.6±16.3m sprint). Regarding the shots attempts, the distance metrics that did not achieved a goal (72.9±22.7m total; 9.5±11.3m high intensity; 5.6±13.1m sprint) are all higher than those that ended in a goal. However, in the play site, statistically significant differences were found in the accelerations (p=0.025) and decelerations (p=0.024), with home games having an average of 0.52±0.6 accelerations and 0.79±0.7 decelerations. According to the results of this sample, it can be concluded that the most significant physical metrics found are accelerations/decelerations, with the most important variable being the play site, for achieving success in soccer.
... The results obtained from the search were organized into categories according to the main topics covered. (Ehrmann et al., 2016), thereby enabling analyses of related data, such as total distance traveled, distances covered at different speeds, and number of accelerations and decelerations . This performance indicator allows the quantification of the external load to which the athlete is subjected and its accumulation throughout the macrocycle of training programming; in this way, sports injuries can be minimized (Bowen et al., 2017), and the level of performance that each athlete shows throughout the competitive season can be verified. ...
... The results obtained from the search were organized into categories according to the main topics covered. (Ehrmann et al., 2016), thereby enabling analyses of related data, such as total distance traveled, distances covered at different speeds, and number of accelerations and decelerations . This performance indicator allows the quantification of the external load to which the athlete is subjected and its accumulation throughout the macrocycle of training programming; in this way, sports injuries can be minimized (Bowen et al., 2017), and the level of performance that each athlete shows throughout the competitive season can be verified. ...
“Ciência e Futebol - Uma combinação fundamental” apresenta as mais recentes investigações científicas no domínio do futebol. Fazendo a ponte entre a teoria e a prática, este livro é a coleção mais abrangente da investigação atual sobre futebol, apresentando novos trabalhos importantes em áreas-chave como: (1) Análise de desempenho; (2) Nutrição; (3) Análise de jogos; (4) Jogos de pequena dimensão; (5) Biomecânica; (6) Futebol feminino; (7) Testes; (8) Monitorização; (9) Futsal; (10) Psicologia e sociologia; (11) Identificação e desenvolvimento de talentos; (12) Lesões.Os artigos contidos neste livro foram apresentados pela primeira vez no Congresso Mundial de Ciência e Futebol, realizado em junho de 2022 em Coimbra, Portugal. A reunião foi realizada sob os auspícios do International Steering Group on Science and Football, um membro representativo da Comissão Mundial de Ciência e Desporto.
... Additionally, Springham et al. (2020) identified a linear relationship between chronic high metabolic load and performance in matches with high metabolic load, suggesting that prolonged exposure to high-intensity activity may result in increased high-intensity actions during matches. Moreover, other studies have suggested that maintaining chronically high workloads enhances readiness among professional soccer players (Bowen et al., 2020;Ehrmann et al., 2016), consequently reducing the risk of injury. Our study contributes by indicating that the high load accumulated in preceding weeks may serve as a reliable indicator of high-speed running (HSR) performance in upcoming matches, owing to the positive correlation observed. ...
The aim of this study was to analyse the correlations between internal and external load accumulated in periods of 4 weeks (current+3-weeks previous) and competitive performance in football. The study was conducted in a Spanish semi-professional football team during the 2020/2021 season (22 football players; age 23.21±4.22 years, weight 74.98±5.78 kilograms and height 1.79±0.06 meters). The study was conducted over a full season where participants were daily monitored. All subjects participated voluntarily and anonymously, providing informed consent. This study was conducted in accordance with the ethical standards outlined in the Declaration of Helsinki. The devices used were 10Hz Playertek+ GPS/GNSS with inertial system and the 6-20 points version of the Rate of Perceived Exertion (RPE). The variables used to assess the internal and external workload of the players were: total distance (TD m), high-speed running >21km/h (HSR; m), total Player Load (PL; UA) and session-RPE (s-RPE; session minutes*RPE). All external workload variables over the course of the season, TD (p≤0.001; r=0.23), HSR (p≤0.001; r=0.48) and PL (p≤0.001; r=0.30), showed significant correlations between cumulative workload and competitive performance in HSR; however, this was not the case for internal load measured with s-RPE. Cumulative workload over 4-week periods appears to be significantly related to HSR performance in competition. High intensity actions and their magnitude become relevant to performance and competitive success in football and this finding should be further investigated in future research. Monitoring is essential for coaches in order to obtain information and prepare the athlete, in optimal conditions, for competition.
... Recent advances in data collection and analysis technologies have enhanced our understanding of the workload and physical demands of team sports [1]. These developments have enabled teams to refine their training programmes, thereby improving player performance and reducing injury risks in elite athletes [2,3]. Monitoring workload has become a crucial aspect of sports research, providing a solid foundation for informed decisionmaking and injury prevention [4,5]. ...
The aim of this study was to compare the external load of each session along competitive microcycles on an elite futsal team, considering the positions and relationships of the players. The external load of 10 elite players from a First Division team in the Spanish Futsal League (age 27.5 ± 7 years, height 1.73 ± 0.05 m, weight 70.1 ± 3.8 kg) were recorded across 30 microcycles. The players’ external loads were monitored using OLIVER devices. To analyse the external load, Levene’s test was conducted to assess the homogeneity of variances, followed by one-way analysis of variance (ANOVA) to identify differences in dependent variables across the different microcycle days and player positions. Regarding external load during the microcycle, the day with the lowest external load was MD-1, and the days with the highest external load were MD-3 and MD-4. In addition, considering playing positions, pivots exhibited the lowest loads throughout the microcycle, whereas wingers and defenders exhibited the highest loads, depending on the variables analysed. By providing reference values from elite contexts, this study offers practical insights for S&C coaches to optimize microcycles. Furthermore, it contributes to workload management strategies within sport science and public health frameworks, promoting sustainable performance and athlete wellness in futsal.
... Previous studies have investigated the relationship between training planning based on GPS metrics and the risk of injury [14][15][16][17]. The majority of these studies are retrospective in nature and primarily focus on identifying significant statistical correlations between individual GPS-derived metrics and the incidence of injuries. ...
Noncontact injuries are prevalent among professional football players. Yet, most research on this topic is retrospective, focusing solely on statistical correlations between Global Positioning System (GPS) metrics and injury occurrence, overlooking the multifactorial nature of injuries. This study introduces an automated injury identification and prediction approach using machine learning, leveraging GPS data and player-specific parameters. A sample of 34 male professional players from a Portuguese first-division team was analyzed, combining GPS data from Catapult receivers with descriptive variables for machine learning models—Support Vector Machines (SVMs), Feedforward Neural Networks (FNNs), and Adaptive Boosting (AdaBoost)—to predict injuries. These models, particularly the SVMs with cost-sensitive learning, showed high accuracy in detecting injury events, achieving a sensitivity of 71.43%, specificity of 74.19%, and overall accuracy of 74.22%. Key predictive factors included the player’s position, session type, player load, velocity and acceleration. The developed models are notable for their balanced sensitivity and specificity, efficiency without extensive manual data collection, and capability to predict injuries for short time frames. These advancements will aid coaching staff in identifying high-risk players, optimizing team performance, and reducing rehabilitation costs.
... Only isokinetic quadriceps concentric at 300°/s was associated with risk of hamstring injury when considered categorically. In the multivariate Cox regression analysis, age (HR 11 only 1 study used the subgroup discovery analysis 43 and also 1 investigation calculated its results using a generalised linear model. 36 AUC values for predicting the outcome ranged between 0.45 and 0.84. ...
Background
One of the challenges for professional football players is injuries. Due to their influence on their teams, injuries greatly impact the sports business. This research aims to assess predictive models of injury risk in male professional football players.
Methods
A systematic literature review was performed, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The search was conducted in the PubMed, Web of Science and Scopus databases. Two independent reviewers screened articles, assessed eligibility and extracted data. Methodological quality was determined by the Newcastle–Ottawa Scale.
Results
26 studies met the inclusion criteria.
Discussion
Various statistical techniques were used in research on injury prediction in professional football, with logistic regression being the most used. The assessment predictors, especially the area under the receiver operating characteristic Curve, showed significant variation, which indicates the prediction models’ efficacy. The focus was frequently on lower limb injuries, where several risk predictors, including muscular strength, flexibility and global positioning system-derived data, were found to substantially impact the occurrence of injuries. Prominent predictors included age, position, physiological parameters, injury history and genetic polymorphisms.
Conclusions
This comprehensive analysis highlights the complexity of injury prediction and reinforces the necessity for football injury research to adopt a multivariate approach with accuracy and comprehensiveness.
PROSPERO registration number
CRD42023465524.
... On the physiological level, the recovery status may be monitored before every training session or competition [50][51][52]. Internal load factors such as the heart rate and the session rating of perceived exertion (sRPE), as well as external load factors such as sprints and total distance covered, are also typically related to injuries [18,[53][54][55][56][57][58]. ...
Background
There has been an increasing interest in the development and prevention of sports injuries from a complex dynamic systems perspective. From this perspective, injuries may occur following critical fluctuations in the psychophysiological state of an athlete. Our objective was to quantify these so-called Early Warning Signals (EWS) as a proof of concept to determine their explanatory performance for injuries. The sample consisted of 23 professional youth football (soccer) players. Self-reports of psychological and physiological factors as well as data from heart rate and GPS sensors were gathered on every training and match day over two competitive seasons, which resulted in an average of 339 observations per player (range = 155–430). We calculated the Dynamic Complexity (DC) index of these data, representing a metric of critical fluctuations. Next, we used this EWS to predict injuries (traumatic and overuse).
Results
Results showed a significant peak of DC in 30% of the incurred injuries, in the six data points (roughly one and a half weeks) before the injury. The warning signal exhibited a specificity of 95%, that is, correctly classifying non-injury instances. We followed up on this promising result with additional calculations to account for the naturally imbalanced data (fewer injuries than non-injuries). The relatively low F1 we obtained (0.08) suggests that the model's overall ability to discriminate between injuries and non-injuries is rather poor, due to the high false positive rate.
Conclusion
By detecting critical fluctuations preceding one-third of the injuries, this study provided support for the complex systems theory of injuries. Furthermore, it suggests that increasing critical fluctuations may be seen as an EWS on which practitioners can intervene. Yet, the relatively high false positive rate on the entire data set, including periods without injuries, suggests critical fluctuations may also precede transitions to other (e.g., stronger) states. Future research should therefore dig deeper into the meaning of critical fluctuations in the psychophysiological states of athletes.
Key Points
Complex Systems Theory suggests that sports injuries may be preceded by a warning signal characterized by a short window of increased critical fluctuations.
Results of the current study showed such increased critical fluctuations before 30% of the injuries. Across the entire data set, we also found a considerable number of critical fluctuations that were not followed by an injury, suggesting that the warning signal may also precede transitions to other (e.g., healthier) states.
Increased critical fluctuations may be interpreted as a window of opportunity for the practitioner to launch timely and targeted interventions, and researchers should dig deeper into the meaning of such fluctuations.
... To confront the challenges posed by uncertainty, coaches and their technical staff are increasingly embracing performance analysis to provide objective and quantifiable information about strengths, weaknesses, and areas for improvement of teams and players (Carling et al., 2007). It encompasses diverse aspects, ranging from tactical analysis (Memmert et al., 2017) and analyzing spatio-temporal tracking data (Bialkowski et al., 2014) to training load and fatigue monitoring (Djaoui et al., 2017) and developing injury prevention models (Ehrmann et al., 2016), and more. The integration of these data-driven techniques into the decision-making process marks a significant shift in soccer, offering immense potential to empower coaches in navigating the inherent uncertainty and variability of the sport. ...
Effective management of a soccer team requires informed decision-making that profoundly influences team success, particularly in the dynamic and uncertain environment of the sport. To navigate the complexities, coaches have increasingly adopted data-driven techniques, resulting in an abundance of analyses that can lead to information overload. Therefore, acquiring a comprehensive understanding of existing soccer performance analysis and leveraging relevant insights become crucial. This study encompasses 3263 papers from Scopus published between 1978 and 2022. Our research employs a two-layer bibliometric analysis approach, involving the construction of a broader keyword co-occurrence network and subsequent nested keyword co-occurrence networks to identify and analyze the main research themes and their sub-themes within the field. Through this nested bibliometric approach, we develop a two-layer hierarchical taxonomy comprising seven overarching research themes and 40 corresponding sub-themes, thereby unveiling the intellectual structure of the literature in soccer performance analysis. Furthermore, our methodology allows us to delve deeper into the data collection process, enabling us to measure the proportion of articles effectively included in the keyword co-occurrence network. By employing this nested bibliometric approach, we evaluate the prevalence of multi-thematic papers in the field, revealing a paucity of truly multi-thematic studies. This research contributes to a deeper understanding of the intellectual structure of soccer performance analysis, providing valuable insights for both practitioners and researchers to advance knowledge in the field and foster a more comprehensive comprehension of soccer performance analysis.
... Even if the scientific community has provided useful contributions, practitioners should take into consideration that the science and practice of periodization is largely based on the hypothesis based on casual observation 78,79 where the datadriven approach has shed light and supported the concept of training prescription. 2,3,6,8,9,19,21,23,80,81 Starting from the knowledge provided by exercise physiologists, evidence of specific adaptations to imposed demands (SAID) 82 should be kept in mind during the training prescription phase. The SAID principle allows coaches to facilitate neural and metabolic adaptations, as well as muscle fibers changes for increased strength and refined motor skill. ...
Data-driven training prescription based on previous training or match data is thought to be associated with better training outcome, compared to prescription without considering any monitoring data. Understanding the complex relationship between training load, physical performance, fitness status, fatigue and injury risk represents a challenge for health and performance practitioners and researchers. Although studies have revealed a positive correlation between training load and injury risk, this cause-effect relation cannot be determined given the multifactorial nature of injuries. Additionally, conflicting findings have been published explaining the relationship between training load and injuries, underlining the importance of training load management, prescription, and communication within the multidisciplinary team to improve physical performance and reduce injury risk. In this sense, practitioners may benefit from practical examples based on training load data to make informed decisions for prescribing training. This narrative review provides real-world examples of training decisions based on training load data in soccer, including training prescription, drill design and multidisciplinary team communication. Finally, a framework was provided to make informed training prescription from a physiological standpoint and elucidate the relationship between training load and injury risk.
... Football stands out because of the intermittent physical participation of the players according to their position and the moment of the game, which implies periods in which the players perform high-intensity activity interspersed with actions of lower intensity or recovery [1]. During the 90 min match, each player covers an average total distance of approximately 11 km, with 5% of this distance covered at high speed and 3% at sprint speed [2]. The ability to perform and repeat these intense actions during the match has been considered one of the key factors for the performance of football players [3]. ...
The aim was to analyse the consequences of a congested schedule (due to the COVID-19 lockdown) on creatine kinase (CK) in elite football players using GPS tracking technology. A total of 17 elite football players were monitored in training and competition with a global positioning system. Variables including total distance, high-intensity distance, and distance acceleration and deceleration were analysed. Different measurements of serum creatine kinase (CK) concentration were performed on match day (MD) and at 24 h (MD+1), 48 h (MD+2), and 72 h (MD+3) after each match to study the muscle damage of each individual player caused during the match. The results showed a significant increase in physical demands in training (in relative terms regarding the match) at MD+3 compared to MD+1 and MD+2. Furthermore, at +72 h, CK decreases to a value almost the same as that before MD. On the other hand, the players with lower demands for high-intensity actions in the match showed a higher reduction in the concentration of CK at MD+3 compared to MD+1 and MD+2 (p < 0.05). It became evident that players with high-intensity demand and a high number of accelerations and decelerations need more time to assimilate the match load and can remain in a state of muscle fatigue for up to 3 days. In addition, a congested schedule can lead to a state of chronic fatigue in elite football players, limiting physical performance and possibly increasing the potential risk of injury for football players.
... In this context, welldeveloped physical qualities, such as joint mobility, muscle strength and flexibility, and the ability to perform high-speed running are essential in preparing high-performance teams (5,(9)(10)(11). Due to the intense match demands, training loads of elite soccer players are also high (12,13), explaining around 76% of the common variance between matches and training sessions (14), which may explain, at least in part, the high incidence of muscle injuries. Ekstrand et al. (2) investigated players from the UEFA Elite Club for 21 seasons between 2001/02 and 2021/22 and observed that hamstring injuries represented 19% of all reported injuries, with the proportion of all injuries increasing from 12% during the first season to 24% in the last season. ...
Purpose: The aim of this pilot study was to analyze the potential financial loss and a range of potential risk factors for hamstring muscle injuries in elite Brazilian soccer. Methods: Thirty-four male players (age: 25 ± 6 years; stature: 180 ± 8 cm; body mass: 78 ± 9 kg; minutes played in matches: 2243 ± 1423 min) from an elite professional soccer club were monitored during a 12-month season. Muscle injury was identified by magnetic resonance imaging and the severity was defined according to the number of days away: minimal (1-3 days), mild (4-7 days), moderate (8-28 days), severe (>28 days). Potential financial loss due to the team's under achievements was determined. Dorsiflexion range of motion, eccentric knee flexor strength and isokinetic tests were performed during the pre-season. Association between dependent variables and the occurrence of injury was evaluated. Results: Nine hamstring muscle injuries with moderate severity were found in 8 athletes. Recovery time was 22 days off the field on average. Potential financial loss was $-43.2 million USD and earnings on merit money was 21%. Previous injury, increased flexor deficit 60°/sec and increased flexor fatigue index 300°/sec were all associated with a greater chance of hamstring muscle injury. Ankle dorsiflexion range of motion was significantly lower in the injured group (35.6 ± 3°vs. 39.1 ± 4.9°; p = 0.017, effect size = −0.74). Conclusion: High financial burden was found in elite Brazilian soccer during one full season. Injured athletes had high hamstring fatigue index, knee flexor strength deficit, ankle range of motion restriction and previous hamstring muscle injury when compared to non-injured athletes. Therefore, preventive approaches in professional soccer players with previous hamstring injuries should be a priority.
KEYWORDS muscle strain, eccentric knee flexor strength, isokinetic, football (soccer), global positioning satellite system (GPS)
... Advancements in technology and analytical methodologies have opened new avenues for monitoring training load through wearable global positioning system (GPS) devices combined with accelerometers, gyroscopes, and heart rate monitoring systems (Ehrmann et al., 2016). These technologies offer a wide range of external and internal training load variables, relating to mechanical load imposed on the players and the corresponding physiological responses, respectively (Gabbett, 2016;Akenhead and Nassis, 2016;Silva et al., 2023). ...
Sports injuries pose significant challenges in athlete welfare and team dynamics, particularly in high-intensity sports like soccer. This study used machine learning algorithms to assess non-contact injury risk in professional male soccer players from physiological and mechanical load variables. Twenty-five professional male soccer players with a first-time, non-contact muscle injury were included in this study. Recordings of external load (speed, distance, and acceleration/deceleration data) and internal load (heart rate) were obtained during all training sessions and official matches over a 4-year period. Machine learning model training and evaluation features were calculated for each of nine different metrics for a 28-day period prior to the injury and an equal-length baseline epoch. The acute surge in the values of each workload metric was quantified by the deviation of maximum values from the average, while the variations of cumulative workload over the last four weeks preceding injury were also calculated. Seven features were selected by the model as prominent estimators of injury incidence. Three of the features concerned acute load deviations (number of sprints, training load score-incorporating heart rate and muscle load-and time of heart rate at the 90-100% of maximum). The four cumulative load features were (total distance , high speed and sprint running distance and training load score). The accuracy of the muscle injury risk assessment model was 0.78, with a sensitivity of 0.73 and specificity of 0.85. Our model achieved high performance in injury risk detection using a limited number of training load variables. The inclusion, for the first time, of heart rate related variables in an injury risk assessment model highlights the importance of physiological overload as a contributor to muscle injuries in soccer. By identifying the important parameters, coaches may prevent muscle injuries by controlling surges of training load during training and competition .
... 11 Additionally, 1 to 4 weeks of cumulative external load has also been associated with injury risk. 12 Specifically, these authors showed that, during the preseason, the 3-week total distance and sprint distance were associated with a higher risk of a player sustaining an injury, whereas during in-season 3-and 4-week acceleration-related metrics presented similar results regarding injury risks. From a different perspective, adequate training chronic load and aerobic status seemed to be associated with a better tolerance to weekly large increases in speed distances (14.4 and 19.8 km/h) and a decreased risk of injury throughout a football season. ...
Objective: To analyze the influence of congested and noncongested fixture periods during 2 seasons in a professional male football team on soft-tissue injury incidence and external load. Methods: Thirty-three professional football players from a Portuguese Liga I team participated in this study. Weekly external load and soft-tissue injury rate and burden of 2 consecutive seasons (2021-22 and 2022-23) were analyzed. Results: Total soft-tissue injury rate and burden for the 2 seasons were 3.9 and 3.2 injuries per 1000 hours and 71.8 and 60.5 days per 1000 hours for congested and noncongested periods, respectively. No significant differences were observed between congested and noncongested periods. Total high-speed running, sprint distance, distance above 80% and 90% of maximal velocity, and meters accelerating and decelerating above 2 m/s 2 were significantly higher for noncongested weeks. Match accelerations and decelerations above 3 m/s 2 were higher during congested periods and training during noncongested periods. No differences between the 2 periods were observed for the total number of accelerations and decelerations above 3 m/s 2. Overall, physical outputs per week were higher for training during noncongested weeks, whereas matches during congested periods registered higher external load. Conclusions: No effect of a congested schedule was observed on soft-tissue injury rates and injury burden. Higher match exposure during congested periods increased external load performed per week, and during noncongested periods, training load was superior to congested weeks.
... In addition, athletes may regularly be perturbed by unenjoyable training sessions and bad performances [43]. On the physiological level, internal load factors such as the heart rate and the session rating of perceived exertion (sRPE), as well as external load factors such as sprints and total distance covered are typically related to injuries [17,39,[54][55][56][57][58]. ...
Background
There has been an increasing interest in the development and prevention of sports injuries from a complex dynamic systems perspective. From this perspective, injuries may occur following critical fluctuations in the psychophysiological state of an athlete. Our objective was to quantify these so-called Early Warning Signals (EWS) to determine their predictive validity for injuries. The sample consisted of 23 professional youth football (soccer) players. Self-reports of psychological and physiological factors as well as data from GPS sensors were gathered on every training and match day over two competitive seasons, which resulted in an average of 339 observations per player (range = 155–430). We calculated the Dynamic Complexity (DC) index of these data, representing a metric of critical fluctuations. Next, we used this EWS to predict injuries based on different mechanisms (traumatic and overuse) and duration.
Results
Results showed a significant peak of DC in 31% of the incurred injuries, regardless of mechanism and duration, in the seven data points (roughly one and a half weeks) before the injury. The warning signal exhibited a specificity of 94%, that is, correctly classifying non-injury instances. We followed up on this promising result with additional calculations to account for the naturally imbalanced data (fewer injuries than non-injuries). The relatively low F1 we obtained (0.08) suggests that the model's overall ability to discriminate between injuries and non-injuries is rather poor, due to the high false positive rate.
Conclusion
By detecting critical fluctuations preceding one-third of the injuries, this study provided support for the complex systems theory of injuries. Furthermore, it suggests that increasing critical fluctuations may be seen as an EWS on which practitioners can intervene. Yet, the relatively high false positive rate on the entire data set, including periods without injuries, suggests critical fluctuations may also precede transitions to other (e.g., stronger) states. Future research should therefore dig deeper into the meaning of critical fluctuations in the psychophysiological states of athletes.
... p 5 0.048} (51). In addition, Ehrmann et al. (63) reported that players had significantly lower Body Load 1 week (15.4% lower) and 4 weeks (9.0%) before injury when compared with the season average. This was suggested to possibly reflect voluntary or involuntary reduced outputs before the injury due to fatigue or soreness. ...
Athlete load monitoring using upper back-mounted Global Navigation Satellite System (GNSS) player tracking is common within many team sports. However, accelerometer-based load monitoring may provide information that cannot be achieved with GNSS alone. This review focuses on the accelerometer-based metrics quantifying the accumulation of accelerations as an estimation of athlete training load, appraising the validity and reliability of accelerometer use in upper back-mounted GNSS player tracking systems, the accelerometer-based metrics, and their potential for application within athlete monitoring. Reliability of GNSS-housed accelerometers and accelerometer-based metrics are dependent on the equipment model, signal processing methods, and the activity being monitored. Furthermore, GNSS unit placement on the upper back may be suboptimal for accelerometer-based estimation of mechanical load. As there are currently no feasible gold-standard comparisons for field-based whole-body biomechanical load, the validity of accelerometer-based load metrics has largely been considered in relation to other measures of training load and exercise intensity. In terms of convergent validity, accelerometer-based metrics (e.g., PlayerLoadTM, Dynamic Stress Load, Body LoadTM) have correlated, albeit with varying magnitudes and certainty, with measures of internal physiological load, exercise intensity, total distance, collisions and impacts, fatigue, and injury risk and incidence. Currently, comparisons of these metrics should not be made between athletes due to mass and/or technique differences, or between manufacturers due to processing variations. Notable areas for further study include the associations between accelerometer-based metrics and other parts of biomechanical load-adaptation pathways of interest, such as internal biomechanical loads or methods of manipulating these metrics through effective training design.
... These results highlight the importance of paying attention to the management of loads according to the player's status, in order to avoid substantial changes when following micro-cycles configured with different amounts of days between games (e.g., 6 or 7 days shown in the present study). According to previous studies (Cross et al., 2016;Ehrmann et al., 2016;Gabbett et al., 2016) there is evidence to suggest that an increase in the load placed on players may be linked to a higher risk of injury. ...
... However, a solid body of evidence confirms the effectiveness of intense WU routines in acutely improving physical performance (Zois et al., 2015) and reducing the risk of injury (van Beijsterveldt et al., 2013). Interestingly, soccer players that covered higher distances in high-speed running (>14.4 km h −1 ) and sprinting (>19.8 km h −1 ) were at reduced noncontact injury risk than their counterparts (Malone et al., 2018) probably because these players are better prepared to cope with match demands (Ehrmann et al., 2016). Moreover, exposing players to chronic higher loads may be crucial to ensure their fitness preparedness, minimizing the noncontact injury risk, as long as that exposure occurs without sudden and excessive load spikes (Bowen et al., 2020). ...
This study compared the differences in acceleration and deceleration demands between three different warm‐up (WU) strategies (Reaction speed [exercises with reaction to a stimulus], Run [self‐paced running], and Speed [exercises such as shuttle running or circuits]) applied to highly trained soccer players. Nineteen players were monitored for 4 weeks using a 10 Hz Global Positioning System. Accelerations and decelerations magnitudes were classified as low (25%–50%), moderate (50%–75%), and high (>75%) intensities. Additionally, efforts were analyzed according to their respective starting speeds (<5, 5–10, 10–15, 15–20, 20–25, and >25 km h⁻¹). Differences between WU strategies were estimated via paired mean differences along with effect sizes. The three WU strategies led to few efforts starting >15 km h⁻¹ and high‐intensity efforts (<1 effort per minute). Players performed more high‐intensity accelerations during Speed than Reaction Speed (ES: 0.74 [90% CI: 0.21, 1.33]); more moderate‐intensity accelerations during Reaction Speed than Run (ES: 1.29 [90% CI: 0.72, 2.00]); more moderate‐intensity decelerations during Reaction Speed than Run (ES: 0.64 [90% CI: 0.04, 1.32]) and Speed (ES: 0.89 [90% CI: 0.37, 1.50]); more decelerations started at 20–25 km h⁻¹ during Speed than Reaction Speed (ES: 0.81 [90% CI: 0.20, 1.49]) and Run (ES: 0.76 [90% CI: 0.42, 1.18]); and more decelerations started at >25 km h⁻¹ during Speed than Reaction Speed (ES: 3.57 [90% CI: 2.88, 4.58]). In conclusion, Speed elicited higher acceleration and deceleration demands than the Reaction Speed and Run WU strategies, and this should be considered when designing training sessions.
... This technology assists in tracking players and providing precise data on the number and type of activities they have engaged in. Consequently, it aids in optimizing training loads and helps in injury prevention (Ehrmann, 2016 tools. This aligns with their answers regarding the difficulties they face in the physical preparation process, as these teams often lack access to and the utilization of technological resources in their training routines. ...
The aim of this study was to identify the practices and perceptions of coaches on mental and physical preparation in Skikda province, Algeria. The sample consisted of 40 coaches of senior amateur soccer teams. A cross-sectional design was employed in this study. An electronic questionnaire was distributed online to collect data. It consisted of six sections, including informed consent from the coaches, demographics, mental preparation, physical preparation, the relationship between mental and physical preparation, and the challenges coaches face in preparing players mentally and physically. The results revealed that the majority of amateur soccer coaches believe that the goal of mental preparation for amateur soccer players is to enhance self-confidence, improve focus, develop decision-making skills, and alleviate pressure and anxiety before competition. They also see the goal of physical preparation as developing aerobic and anaerobic endurance, injury prevention, and enhancing strength and power. However, their practices in both mental and physical preparation were limited. Regarding the relationship between mental and physical preparation, coaches emphasized the importance of both aspects for amateur players. The absence of sports psychologists, a lack of modern technological resources for training, and limited sports facilities were identified as significant challenges hindering the process of mental and physical preparation. Based on these results, the researchers recommend addressing the identified challenges and reinforce the idea of paying more attention to amateur soccer in Algeria.
... 19 Lack of knowledge for a sports demands can lead to athletes being underprepared for their sport, influencing subsequent injury risk. 20 A better understanding of hamstring demands during specific sporting tasks associated with injury may facilitate the development of targeted prevention and rehabilitation strategies for HSI. With knowledge regarding hamstring muscle activation, muscle and related joint kinetics, clinicians can match known exercise demands in a controlled rehabilitation setting before exposure to various intensities in return to running programs. ...
Introduction: Hamstring strain injury (HSI) remains a performance, economic, and player availability burden in sport. High-speed
running (HSR) is cited as a common mechanism for HSI. While evidence exists regarding the high physical demands on the hamstring muscles in HSR, meta-analytical synthesis of related
activation and kinetic variables is lacking.
Methods: A systematic search of Medline, Embase, Scopus, CINAHL, SportDiscus, and Cochrane library databases was conducted in accordance with the PRISMA 2020 guidelines. Studies reporting hamstring activation (electromyographic [EMG]) or hamstring muscle/related joint kinetics were included where healthy adult participants ran at or beyond 60% of maximum speed (activation studies) or 4 m per second (m/s (kinetic studies).
Results: A total of 96 studies met the inclusion criteria. Run intensities were categorized as “slow,” “moderate,” or “fast” in both activation and kinetic based studies with appropriate relative, and raw measures, respectively. Meta-analysis revealed pooled mean lateral hamstring muscle activation levels of 108.1% (95% CI: 84.4%–131.7%) of maximal voluntary isometric contraction (MVIC) during “fast” running. Meta-analysis found swing phase peak knee flexion internal moment and power at 2.2 Newton meters/kilogram (Nm/kg) (95% CI: 1.9–2.5) and
40.3 Watts/kilogram (W/kg) (95% CI: 31.4–49.2), respectively. Hip extension peak moment and power was estimated as 4.8 Nm/kg (95% CI: 3.9–5.7) and 33.1 W/kg (95% CI: 17.4–48.9),
respectively.
Conclusions: As run intensity/speed increases, so do the activation and kinetic demands on the hamstrings. The presented data will enable clinicians to incorporate more objective measures into the design of injury prevention and return-to- play
decision-making strategies.
... Since clubs and national teams may present different (sometimes antagonistic) goals at any given moment, it is fundamental to foster communication between the different multidisciplinary teams for a long-term non-zero sum for all intervenient (club-player, national team) [21]. Communication (e.g., information exchange) between these two entities is considered vital for the mitigation of injury risk and training program development [47], given the documented association between training load (internal and external) and performance [48][49][50][51][52] and injury in soccer [53][54][55][56][57][58][59][60]. Otherwise, reduced personal responsibility regarding performance may ensue, resulting in decreased productivity [36,37]. ...
The increase in the economic value of soccer occurred in parallel with an increase in competing demands. Therefore, clubs and federations evolved to greater specialization (e.g., state-of-the-art facilities and high-profile expertise staff) to support players’ performance and health. Currently, player preparation is far from exclusively club or national team centered, and the lack of control in each player’s environment can be more prevalent than expected. For example, an elite group of professional players faces disruptions in the season club-oriented planification due to involvement in national teams. Moreover, as elite players’ financial resources grow, it is common for them to employ specialized personal staff (e.g., strength and conditioning, nutritionist, and sports psychologist) to assist in their preparation, resulting in complex three-fold relationships (i.e., club, player’s staff, national team). Although efforts have been made to improve communication with and transition from the club to the national team supervision, this new reality (club-players’ staff) may generate serious compound role-related problems and difficulties in monitoring load and training adaptation and having a unified message. Therefore, efforts must be implemented to ensure a more informed management of the players’ performance environment, where the existence and impact of these various personal staff are considered to avoid a long-term non-zero sum for all intervening parties. If left unchecked, current professional thinking may collide or overlap, potentially triggering conflict escalation and impairing athletic performance or health, especially if effective communication routes are not adequately established. Moreover, diluted personal responsibility regarding performance may ensue, resulting in decreased productivity from all involved, which may cause more harm than benefits for the player’s overall health and performance. This emerging reality calls for developing a joint working framework (i.e., between the player’s personalized support team and the clubs’ team) and better managing of a player-centered process.
... Internet of Things (IoT) refers to the set of physical objects with sensors and programs connected to other devices and systems through a network. One of the practical applications of this type of technology would be to extract a high volume of data from lifestyles, training, and sport events [48]. AI could use all this data and integrate it with other sources of information to generate algorithms to make clinical decisions or predict adverse events. ...
Artificial intelligence (AI) refers to computer capabilities that resemble human intelligence. AI implies the ability to learn and perform tasks that have not been specifically programmed. Moreover, it is an iterative process involving the ability of computerized systems to capture information, transform it into knowledge, and process it to produce adaptive changes in the environment. A large labeled database is needed to train the AI system and generate a robust algorithm. Otherwise, the algorithm cannot be applied in a generalized way. AI can facilitate the interpretation and acquisition of radiological images. In addition, it can facilitate the detection of trauma injuries and assist in orthopedic and rehabilitative processes. The applications of AI in musculoskeletal conditions are promising and are likely to have a significant impact on the future management of these patients.
... GPS devices allow an accurate follow-up of the players on the field (Casamichana & Castellanos 2011b;Ehrmann et al., 2016), information that allows the coaching staff to identify possible trends that can expose the athlete to overloads and injuries (Oliveira et al., 2019). It also provides data to correctly schedule weekly training sessions according to the demands of each player and team (De Silva et al., 2018), and finally to optimize the players' athletic performance throughout the season (Terrier & Schutz, 2005). ...
This study analyze the number of sprints and distances traveled at high speed by Chilean professional soccer players considering the playing position with a GPS device. Methods: The data from high-speed efforts of 10 professional soccer players were recorded. The amount of effort in sprints (> 21 km·h−1) and the distances covered in zone 4 (> 21 km·h−1 and < 25 km·h−1) and in zone 5 (> 25 km·h−1) were analyzed, differentiating and grouping the players by playing position. A Global Positioning System (GPS) device was used to collect the data, and the results were recorded in the program cloud. Results: Statistically significant differences were noted between playing positions in zone 4 (p=0.03), zone 5 (p=0.01), and number of sprints (p=0.01), with the wide forwards presenting the greatest number of sprints and distance traveled at high speed compared to the other positions, whereas the central defenders show a tendency to travel less in zones 4 and 5 and have a lower number of sprints. Conclusion: The number of sprints and distances covered at high intensity (zones 4 and 5) are different and will be specific according to the characteristics of the playing position.
... • GPS monitoring and increase in training and gameplay intensity could predict soft tissue injuries [10]. ...
Football players are prone to sports injuries such as ankle sprain, groin pain, ACL injury, and so on. Muscle strain injury also frequently occurs in football games or practice. As previous studies show, previously injured players have altered muscle and neural functions as well as tissue properties associated with muscle strain injury. They have altered vibration sense, tissue stiffness, and increases in micro-muscle damage. However, training load or conditioning programs are provided the same as those for uninjured players in most cases. In this chapter, the conditioning strategies for players who have previous muscle injuries will be suggested according to the phenomenon after muscle strain injury.
... The GPS devices allowed the measurement (relative to each minute of played SSG) of: total distance (TD) (m·min-1); low intensity running (LIR) (distance covered at <15 km·h-1 in m·min-1); high intensity running (HIR) (distance covered >15km·h-1 in m·min-1); sprint distance (SPD) (distance covered >2m·s-2 or >20km·h-1 in m·min-1); accelerations (ACC; changes in velocity >2m/s2) (n·min-1); decelerations (DEC; changes in velocity <-2m/ s2 (n·min-1)(Vázquez-Guerrero et al., 2020); repeated sprints (RS) defined as 2 consecutive sprints in less than 20 seconds (n·min-1); Bodyload (BL) (Arbitrary Unit·min-1). Bodyload was determined through the GPS's 100 Hz triaxial accelerometer, which combines the body movement axes (vertical (y), horizontal (x), and anteroposterior (z)) (Ehrmann et al., 2016) and it´s largely correlated with Edward´s TRIMP (Rabbani et al., 2019). To be able to compare results, speed thresholds were based on previous research (Ramos et al., 2017). ...
Purpose: The aim of this study was to describe and compare the external loads response of elite female soccer players to different small-sided games (SSG). Twelve elite female soccer players (26.5 ± 5.7 years, 58.6 ± 5.6 kg, 164.4 ± 5.3 cm) performed four different 6vs6 SSG: two different sizes (20x20m and 30x30m) and with minigoals (MG) and without mini-goals (NG). Methods: Total distance (TD),
low-intensity running distance (LIR), high-intensity running distance (HIR), sprint distance (SD), accelerations (ACC), decelerations (DEC), repeated sprints (RS) and Bodyload (BL) was collected using a 15Hz global positioning satellite system. The variables were compared across all SSG formats using a one-way analysis of variance (ANOVA) (p<.05) and non-clinical magnitude-based inferences (Cohen´s d). Results: Compared to 20x20m SSG, the 30x30m SSG induced greater TD (p=.001, d=1.20), LIR (p=.001, d=1.06), HIR (p=.001, d=1.20) and BL (p=.008, d=1.04) in NG condition. Similarly, in SSG with MG, greater number of ACC (p=.003, d=.38), DEC (p=.005, d=.42), LIR (p=.009, d=.86) and HIR (p=.070 d=.61) occurred in 30x30m vs. 20x20m. When NG 30x30m and 20x20m SSG were played, greater TD (p=.001, d=1.70; p=.001, d=1.13; respectively), LIR (p=.001, d=1.84; p=.001, d=1.39), ACC (p=.54, d=.39; p=.003, d=.74; respectively) and BL (p=.001, d=1.60; p=.001, d=1.15; respectively) were noted compared to MG. Conclusion: greater external load response of elite female soccer players was observed in SSG without mini-goals and played in greater pitch sizes. These findings are usefulness for coaches and physical trainers to design proper training tasks according to game demands.
... Specifically, the external load (EL) is usually described by the total distance, range of speed covered, accelerations, metabolic power [14], and other derived measures. Global position systems (GPS) technology has been largely used by practitioners to assess EL allowing for time-motion analysis in technical-tactical tasks [6,[15][16][17]. However, in the last few years, several microelectromechanical systems (MEMS) have been developed and are available and these include triaxial accelerometers, triaxial gyroscopes, magnetometers, and pressure sensors. ...
Background:
Wearable inertial sensors are poorly used in soccer to monitor external load (EL) indicators. However, these devices could be useful for improving sports performance and potentially reducing the risk of injury. The aim of this study was to investigate the EL indicators (i.e., cinematic, mechanical, and metabolic) differences between playing positions (i.e., central backs, external strikers, fullbacks, midfielders, and wide midfielder) during the first half time of four official matches (OMs).
Methods:
13 young professional soccer players (Under-19; age: 18.5 ± 0.4 years; height: 177 ± 6 cm; weight: 67 ± 4.8 kg) were monitored through a wearable inertial sensor (TalentPlayers TPDev, firmware version 1.3) during the season 2021-2022. Participants' EL indicators were recorded during the first half time of four OMs.
Results:
significant differences were detected in all the EL indicators between playing positions except for two of them (i.e., distance traveled in the various metabolic power zones (<10 w) and the number of direction changes to the right >30° and with speed >2 m). Pairwise comparisons showed differences in EL indicators between playing positions.
Conclusions:
Young professional soccer players showed different loads and performances during OMs in relation to playing positions. Coaches should consider the different physical demands related to playing positions in order to design the most appropriate training program.
... Current athlete monitoring practice in team sports is mainly based on position data measured by local or global positioning systems 24,25 . These systems monitor activity with GPS-based metrics such as distance covered, average running velocity or accelerometry-based metrics such as PlayerLoad 26,27,28 . A disadvantage of these measures is that they do not include lower extremity kinematics. ...
... Nearly four thousand injuries, from which 23.3% were noncontact and 17.6% were overuse injuries, were reported in over 450,330 AEE 12 . Further, Ehrmann et al. 13 reported that players performed higher meters per minute (matches and training) in the weeks preceding an injury when compared to their seasonal averages. Additionally, injuries may predispose athletes to future injuries as larger inter-limb asymmetries during bilateral CMJ tests have been reported in those with prior injuries 14 . ...
Introduction: The purpose of this study was to assess the repeated measures correlations between the sums of training load (TL) variables preceding matchday and matchday countermovement jump (CMJ) height in NCAA Division I (DI) women’s soccer athletes. Methods: A total of 23 female soccer players (20 ± 1.2 years; 1.69 ± 0.06 m) participated in this study. Repeated measures correlations were used to determine the relationships between matchday CMJ height and TL variables. Results: Matchday CMJ height showed very weak to weak negative relationships with the sums of the TL variables for the microcycle preceding the match: sRPE-TL (r = -0.184, p = 0.036), TD (r = -0.229, p = 0.008), TLS (r = -0.192, p = 0.028), HSD (r = -0.229, p = 0.008), ML (r = -0.204, p = 0.020), and number of sprints (r = -0.237, p = 0.006). Conclusions: Although significant negative weak relationships were observed, the results suggest that the sums of TL variables preceding matchday may not be the most reliable indicators of matchday preparedness in collegiate DI women’s soccer. Future research should aim to investigate other strategies to predict matchday readiness in collegiate women’s soccer.
... Worldwide, GPS technologies are the main instrument used to monitor external load in football. According to the literature, TD, HSR, ACC, and DEC are predictive factors of players' risk of injury [36].The relationship between external load and the likelihood of sports injury occurrence has recently been discussed using those GPS metrics [25,[37][38][39][40][41]. Indeed, a recent systematic review on this topic reinforced the importance of monitoring players' external load across training sessions [27]. ...
One of the most challenging issues professional football players face throughout their careers is injuries. Those injuries often result from suboptimal training programs that were not designed according to the players' individual needs. This prospective study aimed to examine in detail the effects of sports injuries on professional football players' weekly external load performances. Thirty-three male professional football players were monitored using 10-Hz Global Positioning System (GPS) units (Apex pro series, StatSports) during an entire season. The variables considered in the analysis were total distance (TD), high-speed running (HSR), accelerations (ACC), and decelerations (DEC). The comparisons were made between the four-week block before injury (-4T), four-week block after return (+4T), and players' season averages (S). Players displayed significantly higher values of TD, HSR, ACC, and DEC in the-4T, compared to the other two moments (+4T and S). Furthermore, the comparison between the +4T and S showed no significant variations in the GPS metrics. It was shown that a significant increase in players' weekly external load performance over a four-week period may have a negative effect on the occurrence of injuries from a professional football standpoint. Future research should consider the effects of injury severity on players' external load variations.
This study aimed (i) to analyze the relationship between weekly accumulated training load (TL) and match physical demands in the same week and (ii) to describe the training/match ratios of different external load measures considering variations across different training days. Twenty-one Spanish male professional soccer players were involved in the study. Total distance (TD), medium speed running (MSR, distance 10.8–18.0 km·h−1), high-speed running (HSR, >21 km·h−1), very high-speed running (VHSR, 18.0–25.2 km·h−1), sprinting-speed running distance (Sprint, >25.2 km·h−1), player load (PL), number of accelerations (ACC), and decelerations (DEC) were recorded during training sessions and matches using 10 Hz GPS devices. Correlations between the weekly TL and match physical demands were trivial and negative for TD (r = −0.08) and PL (r = −0.05); trivial and positive for MSR (r = 0.02), HSR (r = 0.07), Sprint (r = 0.09), and DEC (r = 0.06); and small and positive for VHSR (r = 0.22) and ACC (r = 0.19). The greatest TD, MSR, VHSR, Sprint, HSR, and PL values and their derivate ratios occurred in MD–3. The present study highlights the need for soccer athletes to be exposed to similar demands to those observed during matches.
This systematic review synthesizes evidence on biomarker responses to physiological loads in professional male team sport athletes, providing insights into induced fatigue states. Structured searches across major databases yielded 28 studies examining various biomarkers in elite team sport players. Studies evaluated muscle damage markers, anabolic/catabolic hormones reflecting metabolic strain, inflammatory markers indicating immune activity and tissue damage, immunological markers tied to infection risk, and oxidative stress markers showing redox imbalances from excessive physiological load. Responses were examined in official matches and training across competitive seasons. The evidence shows that professional team sports induce significant alterations in all studied biomarkers, reflecting measurable physiological strain, muscle damage, oxidative stress, inflammation, and immunosuppression during intensive exercise. These effects tend to be larger and more prolonged after official matches compared to training. Reported recovery time courses range from 24-h to several days post-exercise. Monitoring biomarkers enables quantifying cumulative fatigue and physiological adaptations to training/competition loads, helping to optimize performance while mitigating injury and overtraining. Key biomarkers include creatine kinase, testosterone, cortisol, testosterone/cortisol ratio, salivary immunoglobulin-A, and markers of inflammation and oxidative stress. Further research should extend biomarker monitoring to cover psychological stress and affective states alongside physiological metrics for deeper insight into athlete wellness and readiness.
El objetivo de esta tesis doctoral fue registrar, analizar y cuantificar, por primera vez, el perfil CT y CF mediante tecnología IMU en jugadores profesionales de fútbol durante partidos.
La investigación está basada en un diseño observacional del análisis de la CT y CF
durante partidos de un equipo profesional de fútbol. Un total de 18 futbolistas
profesionales (n=18) de 24.6 ± 2.7 años, 1.78 ± 0.32 estatura (m), 74.6 ± 4.5 masa (kg), 23.54 ± 2.7 IMC (kg.m2), 9.76 ± 2.20 % graso, y 65.6 ± 2.7 VO2 Max (ml·kg·min2) pertenecientes a un mismo equipo, tomaron parte en este estudio. En el estudio se realizaron un total de 103 registros, los jugadores fueron clasificados de acuerdo a su posición específica: Defensa Lateral (DL: n=4), Defensa Central (DC: n=3), Mediocampista (MD: n=4), Extremo (EX: n=4) y Delantero (DT. n=3).
En el análisis de las variables CF encontramos que WR (m/min) (p= ≤ 0.001, ES: 0.92), DR (m) (p= 0.02, ES: 0.57), DAI (m) (p= 0.01, ES: 0.27), DAI (m/min) (p= ≤ 0.001, ES:0.36), DS (m) (p= 0.02, ES: 0.21), DS (m/min) (p= 0.01, ES: 0.23), SP (#) (p= 0.04, ES:0.29), SP (#/min) (p= 0.01, ES: 0.37), DRZ3 (p= 0.01, ES: 0.31), DRZ4 (p= 0.01, ES:0.26) y DRZ5 (p= 0.02, ES: 0.24), generan valores significativamente mayores en la primera parte que en la segunda. Con respecto a las diferentes posiciones específicas, se observaron diferencias significativas por puestos tanto para variables de CT como para variables de CF. Atendiendo a variables de CT, por puestos específicos los MD son los que generaron un mayor registro de TT, sin alcanzar diferencias significativas con DC (p= 0.84), pero obteniendo diferencias significativas con DL (p = 0.01) y con DT (p ≤0.001). Estos resultados enfatizan la naturaleza independiente de CT desde la CF, y brindan información valiosa sobre las demandas técnicas de los jugadores en diferentes posiciones durante los partidos.
Como conclusión principal, se afirma que el perfil de CF de los futbolistas profesionales, en función de su posición de juego, resulta independiente del desarrollo de CT observado durante los partidos. Por lo tanto, monitorear, cuantificar y controlar tanto el perfil de CT y CF de los jugadores de fútbol ofrece una comprensión más integral y holística de las demandas en los partidos en comparación con el análisis únicamente de CF.
Background
The influence of external workload variables on the development of calf muscle strainsin football players has not been previously explored.
Hypothesis
Overloaded players would have an increased risk of calf muscle strain injury.
Study Design
Prospective observational study.
Level of Evidence
Level 4.
Methods
A total of 41 professional football players from 1 team were monitored for 2 consecutive seasons. Total distance covered (TD), and distances covered at high-intensity running, high sprint running, low (LACC) and high (HACC) acceleration, low (LDEC) and high (HDEC) deceleration, and at high metabolic load distance (HMLD) were monitored with GPS units. Accumulated players’ external workload in the week before injury was compared with the weekly mean value of the 6 weeks before injury occurred for each player.
Results
Ten players (24.3%) suffered 16 calf muscle strain injuries (3.1 injuries per 1000 hours of match play; 0.5 injuries per 1000 hours of training exposure). Players with a calf muscle injury were older ( p = 0.03), with higher body weight ( p = 0.01) and height ( p = 0.03). Injured players displayed substantially higher total training volume ( p < 0.01), TD ( p < 0.01), LACC ( p < 0.01), LDEC ( p < 0.01), HACC ( p < 0.01), HDEC ( p < 0.01), and HMLD ( p = 0.03) in the week before injury, in comparison with the mean values of these variables in the 6 weeks before injury.
Conclusion
A week with a higher-than-habitual external workload might increase the risk of calf muscle strain injury in professional football players. Calf muscle injuries were preceded by a week with unusually high workloads associated with accelerating and decelerating distances and higher training volumes.
Clinical Relevance
Monitoring external workload indicators may be helpful in determine players with a higher risk of calf muscle strain injury due to excessive workload during training/competition.
US college sports teams are increasingly adopting personal data technologies, such as wearable sensors, with a goal of improving individual and team performance as well as individual safety. These tools can also reinforce the power that coaches hold over student-athletes and compromise student-athletes' needs for privacy and agency. To investigate preferred, and anti-preferred, approaches for navigating this complex sociotechnical challenge, we used a speculative design approach in which student athletes and technology design students developed three videos that portray tensions between student-athletes and coaches around the use of sports tracking technologies. We then shared these videos with 15 participants including student-athletes, coaches, and designers. Drawing on the perspectives of student-athletes, team staff, and designers embedded in the videos and expressed in reaction to the videos, we describe preferences for boundaries on tracking and sharing, how tracking data represent athletes, and for data practices. We also propose design requirements and recommendations for use to better align tracking technologies with these preferences.
This chapter introduces the topic of predictive models in sports. These models are driven by the idea of coming up with the most accurate data-based estimates of the probabilities of future events. This includes aspects as diverse as the outcomes of sports competitions, the tactical behaviour of teams on the field, or the frequency of injuries. The ability to accurately forecast such events enables bookmakers to improve their business model in the sports betting market. Moreover, it gives competitive advantages to sports teams with regard to both sporting and financial aspects. Predictive models, therefore, represent a relevant and highly interdisciplinary field of research that connects the domains of sports science, economics, mathematics, and computer science.
Objectives
Elite youth football players miss out on a large part of seasonal training due to injury. Limited research suggests an association between external and internal training load (TL) and injury incidence in elite youth football. This study analysed external and internal TL variables and their association with injury incidence in a group of male elite youth football players over four seasons.
Methods
Measures of external and internal TL and injury incidence of 56 male elite youth football players (age 17–19 years) were collected throughout four seasons. Heart rate, session rating of perceived exertion andGlobal Positioning System (GPS) variables were analysed. Individual players’ TL during the 30 days leading up to injury was compared with 30-day injury-free control periods. Change in TL through the periods was also analysed.
Results
Eighty-five injuries were included for analysis, showing that for most TL variables, the average levels were significantly lower during the period leading up to injury. Significant increases for the majority of TL variables were also found during the periods leading up to injury, while the control periods did not show any significant change.
Conclusion
A lower and/or increasing average TL volume over 30 days might increase the risk of injury in male elite youth football players. Avoiding long-term drops in TL and balance increases in TL might be beneficial to reduce injury risk.
Background:
Monitoring muscle damage in athletes assists not only coaches to adjust the training workload but also medical staff to prevent injury. Measuring blood myoglobin concentration can help evaluate muscle damage. The novel portable device utilized in this study allows for easy on-site measurement of myoglobin, providing real-time data on the player's muscle damage. This study investigated the relationship between external load (global positioning system parameters) and internal loads (myoglobin concentration and creatine kinase activity) in 15 male professional football players before and after a match.
Methods:
Whole blood samples from participants' fingertips were collected before the match (baseline) and at 2, 16, and 40 h after the match. Myoglobin concentrations were measured using the IA-100 compact immunoassay system. Creatine kinase concentrations were measured in a clinical laboratory, and match loads were monitored using a global positioning system device.
Results:
The mean myoglobin concentration was significantly higher at 2 h than at the other time points (P<0.05), and decreased to baseline levels within 16 h post-match. The mean creatine kinase concentration increased after the match but did not reach a significant level. Muscle damage monitored by myoglobin after football match-play was strongly associated with acceleration/deceleration metrics rather than the sprint/high-speed running distance.
Conclusions:
Our findings indicate that myoglobin is a more sensitive marker of muscle damage than creatine kinase after football match-play. Monitoring myoglobin in athletes can aid in determining their recovery status from the previous training load and help practitioners manage the training load.
Professional soccer is a physically demanding sport that requires players to be highly trained. Advances using GPS allow the tracking of external workloads for individual players in practice and competition, however, there is a lack of evidence on how these measures impact match results. Therefore, we analyzed external workloads by player position and determined if they vary depending on the result of competitive matches. External workloads were analyzed in professional soccer players (n = 25) across 28 competitive games. One-way ANOVA determined if workloads varied by position (striker - ST, wide midfielder - WM, central midfielder - CM, wide defender - WD, central defender - CD) or across games won (n = 8), lost (n = 13) or tied (n = 7). Repeated-measures ANOVA assessed differences in workloads specific to each position in each of the result categories. Statistical significance was set at p < 0.05. Across all games, more high-speed and very-high speed running was done by ST and WD compared to CD (p < 0.001) and CM (p < 0.001 - 0.02). Whole-team data showed no differences in any external workload variable with respect to match result (p > 0.05), however, in games won ST did more very high-speed running than in losing games (p = 0.03) and defending players did more high and very high-speed running in games tied vs. those won or lost (p < 0.05). Whole-team external workloads do not vary depending on the match result; however, high speed running may be a differentiating factor at the positional level. Coaches should consider position-specific analysis when examining player workloads.
This study presents the filter design of GNSS/IMU integration for wearable EPTS (Electronic Performance and Tracking System) of football players. EPTS has been widely used in sports fields recently, and GNSS (Global Navigation Satellite System) and IMU (Inertial Measurement Unit) in wearable EPTS have been used to measure and provide players’ athletic performance data. A sensor fusion technique can be used to provide high-quality analysis data of athletic performance. For this reason, the integration filter of GNSS data and IMU data is designed in this study. The loosely-coupled strategy is considered to integrate GNSS and IMU data considering the specification of the wearable EPTS product. Quaternion is used to estimate a player’s attitude to avoid the gimbal lock singularity in this study. Experiment results validate the performance of the proposed GNSS/IMU loosely-coupled integration filter for wearable EPTS of football players.
Successful training must involve overload, but also must avoid the combination of excessive overload plus inadequate recovery. Athletes can experience short-term performance decrement, without severe psychological, or lasting other negative symptoms. This Functional Overreaching (FOR) will eventually lead to an improvement in performance after recovery. When athletes do not sufficiently respect the balance between training and recovery, Non-Functional Overreaching (NFOR) can occur. The distinction between NFOR and the Overtraining Syndrome (OTS) is very difficult and will depend on the clinical outcome and exclusion diagnosis. The athlete will often show the same clinical, hormonal and other signs and symptoms. A keyword in the recognition of OTS might be ‘prolonged maladaptation’ not only of the athlete, but also of several biological, neurochemical, and hormonal regulation mechanisms. It is generally thought that symptoms of OTS, such as fatigue, performance decline and mood disturbances, are more severe than those of NFOR. However, there is no scientific evidence to either confirmor refute this suggestion. One approach to understanding the aetiology of OTS involves the exclusion of organic diseases or infections and factors such as dietary caloric restriction (negative energy balance) and insufficient carbohydrate and/or protein intake, iron deficiency, magnesium deficiency, allergies, etc., together with identification of initiating events or triggers. In this paper, we provide the recent status of possible markers for the detection of OTS. Currently several markers (hormones, performance tests, psychological tests, biochemical and immune markers) are used, but none of them meets all criteria to make its use generally accepted.
Abstract We compared the match activity profiles of elite footballers from Australian football (AF), rugby league (RL) and soccer (SOC), using identical movement definitions. Ninety-four elite footballers from AF, RL or SOC clubs in Australia participated in this study. Movement data were collected using a 5-Hz global positioning system from matches during the 2008-2011 competitive seasons, including measures of velocity, distance, acceleration and bouts of repeat sprints (RS). Australian footballers covered the greatest relative running distances (129 ± 17 m.min(-1)) compared to RL (97 ± 16 m.min(-1)) and SOC (104 ± 10 m.min(-1)) (effect size [ES]; 1.0-2.8). The relative distance covered (4.92 ± 2.10 m.min(-1) vs. 5.42 ± 2.49 m.min(-1); 0.74 ± 0.78 m.min(-1) vs. 0.97 ± 0.80 m.min(-1)) and the number of high-velocity running (0.4 ± 0.2 no.min(-1) vs. 0.4 ± 0.2 no.min(-1)) and sprint (0.06 ± 0.06 no.min(-1) vs. 0.08 ± 0.07 no.min(-1)) efforts between RL and SOC players were similar (ES; 0.1-0.3). Rugby league players undertook the highest relative number of accelerations (1.10 ± 0.56 no.min(-1)). RS bouts were uncommon for all codes. RL and SOC players perform less running than AF players, possibly due to limited open space as a consequence of field size and code specific rules. While training in football should be code specific, there may be some transference of conditioning drills across codes.
The measurement of heart rate variability (HRV) is often considered a convenient non-invasive assessment tool for monitoring individual adaptation to training. Decreases and increases in vagal-derived indices of HRV have been suggested to indicate negative and positive adaptations, respectively, to endurance training regimens. However, much of the research in this area has involved recreational and well-trained athletes, with the small number of studies conducted in elite athletes revealing equivocal outcomes. For example, in elite athletes, studies have revealed both increases and decreases in HRV to be associated with negative adaptation. Additionally, signs of positive adaptation, such as increases in cardiorespiratory fitness, have been observed with atypical concomitant decreases in HRV. As such, practical ways by which HRV can be used to monitor training status in elites are yet to be established. This article addresses the current literature that has assessed changes in HRV in response to training loads and the likely positive and negative adaptations shown. We reveal limitations with respect to how the measurement of HRV has been interpreted to assess positive and negative adaptation to endurance training regimens and subsequent physical performance. We offer solutions to some of the methodological issues associated with using HRV as a day-to-day monitoring tool. These include the use of appropriate averaging techniques, and the use of specific HRV indices to overcome the issue of HRV saturation in elite athletes (i.e., reductions in HRV despite decreases in resting heart rate). Finally, we provide examples in Olympic and World Champion athletes showing how these indices can be practically applied to assess training status and readiness to perform in the period leading up to a pinnacle event. The paper reveals how longitudinal HRV monitoring in elites is required to understand their unique individual HRV fingerprint. For the first time, we demonstrate how increases and decreases in HRV relate to changes in fitness and freshness, respectively, in elite athletes.
The influence of fixture congestion on injury rates and team performance has only been scarcely investigated.
To study associations between recovery time and match load and injury rates and team performance in professional football.
Exposure and time loss injuries were registered prospectively from 27 teams over 11 seasons. Matches were grouped according to recovery days before each match (≤3 vs >3 days, and ≤4 vs ≥6 days). Injury rates and team performance were compared between groups. Match load in match sequences containing five consecutive matches was determined by the number of days separating the first match and the last training session during that match sequence. Linear regression was used to study associations between match load and injury rates and team performance.
Team performance showed no association with match load, or recovery days prior to matches, except for Europa League matches that indicated more matches lost with short recovery (≤3 days) (p=0.048). Total injury rates and muscle injury rates were increased in league matches with ≤4 days compared with ≥6 days' recovery (RR 1.09, 95% CI 1.00 to 1.18, and RR 1.32, 95% CI 1.15 to 1.51, respectively), specifically hamstring and quadriceps injuries. High match load was associated with increase in muscle injury rate in matches in the same match sequence (p=0.012), and increase in ligament injury rate in training in the subsequent match sequence (p=0.003).
Fixture congestion was associated with increased muscle injury rates but had no, or very limited, influence on team performance.
Background:
The influence of injuries on team performance in football has only been scarcely investigated.
Aim:
To study the association between injury rates and team performance in the domestic league play, and in European cups, in male professional football.
Methods:
24 football teams from nine European countries were followed prospectively for 11 seasons (2001-2012), including 155 team-seasons. Individual training and match exposure and time-loss injuries were registered. To analyse the effect of injury rates on performance, a Generalised Estimating Equation was used to fit a linear regression on team-level data. Each team's season injury rate and performance were evaluated using its own preceding season data for comparison in the analyses.
Results:
7792 injuries were reported during 1 026 104 exposure hours. The total injury incidence was 7.7 injuries/1000 h, injury burden 130 injury days lost/1000 h and player match availability 86%. Lower injury burden (p=0.011) and higher match availability (p=0.031) were associated with higher final league ranking. Similarly, lower injury incidence (p=0.035), lower injury burden (p<0.001) and higher match availability (p<0.001) were associated with increased points per league match. Finally, lower injury burden (p=0.043) and higher match availability (p=0.048) were associated with an increase in the Union of European Football Association (UEFA) Season Club Coefficient, reflecting success in the UEFA Champions League or Europa League.
Conclusions:
Injuries had a significant influence on performance in the league play and in European cups in male professional football. The findings stress the importance of injury prevention to increase a team's chances of success.
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], 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.
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.
Background In modern professional soccer, the ability to recover from official match-play and intense training is often considered a determining factor in subsequent performance.
Objective To investigate the influence of playing multiple games with a short recovery time between matches on physical activity, technical performance and injury rates.
Methods The variation of physical (overall distance, light-intensity, low-intensity, moderate-intensity and high-intensity running) and technical performance (successful passes, balls lost, number of touches per possession and duels won) of 16 international players was examined during three different congested periods of matches (six games in 18 days) from the French League and Cup (n=12), and the UEFA Champions’ League (n=6) during the 2011–2012 season and compared with that reported in matches outside these periods. Data were collected using a computerised match analysis system (Amisco). Injury rate, time loss injuries, as well as the mechanism, circumstances and severity of the injury were also analysed.
Results No differences were found across the six successive games in the congested period, and between no congested and the three congested periods for all the physical and technical activities. The total incidence of injury (matches and training) across the prolonged congested periods did not differ significantly to that reported in the non-congested periods. However, the injury rate during match-play was significantly higher during the congested period compared with the non-congested period (p<0.001). The injury rate during training time was significantly lower during the congested period compared with the non-congested periods (p<0.001). The mean lay-off duration for injuries was shorter during the congested periods compared with the non-congested periods (9.5±8.8 days vs 17.5±29.6 days, respectively p=0.012, effect sizes=0.5).
Conclusions Although physical activity, technical performance and injury incidence were unaffected during a prolonged period of fixture congestion, injury rates during training and match-play and the lay-off duration were different to that reported in matches outside this period.
Objectives:
To examine the relationship between combined training and game loads and injury risk in elite Australian footballers.
Design:
Prospective cohort study.
Methods:
Forty-six elite Australian footballers (mean±SD age of 22.2±2.9 y) from one club were involved in a one-season study. Training and game loads (session-RPE multiplied by duration in min) and injuries were recorded each time an athlete exerted an exercise load. Rolling weekly sums and week-to-week changes in load were then modelled against injury data using a logistic regression model. Odds ratios (OR) were reported against a reference group of the lowest training load range.
Results:
Larger 1 weekly (>1750 AU, OR=2.44-3.38), 2 weekly (>4000 AU, OR=4.74) and previous to current week changes in load (>1250 AU, OR=2.58) significantly related (p<0.05) to a larger injury risk throughout the in-season phase. Players with 2-3 and 4-6 years of experience had a significantly lower injury risk compared to 7+ years players (OR=0.22, OR=0.28) when the previous to current week change in load was more than 1000 AU. No significant relationships were found between all derived load values and injury risk during the pre-season phase.
Conclusions:
In-season, as the amount of 1-2 weekly load or previous to current week increment in load increases, so does the risk of injury in elite Australian footballers. To reduce the risk of injury, derived training and game load values of weekly loads and previous week-to-week load changes should be individually monitored in elite Australian footballers.
There is a need to ascertain if an association exists between excessive progression in weekly volume and development of running related injuries. The purpose of this study was to investigate if GPS can be used to detect deleterious progression in weekly training volume among 60 novice runners included in a 10 week prospective study. All participants used GPS to quantify training volume while running. In case of injury participants attended a clinical examination. The thirteen runners sustaining injuries during follow-up, had a significantly higher weekly progression in total training volume in the week prior to the injury origin of 86 % [95 % CI: 12.9 to 159.9], p = 0.026 compared with other weeks. Although not significant, participants with injuries had an increase in weekly training volume of 31.6 % compared with a 22.1 % increase among the healthy. The error of the GPS measurements in open landscape, forest, and urban area of volume was ≤ 6.2 %. In conclusion, no clinically relevant the measurement errors of the GPS devices were found for training volume. Based on this, GPS has a potential to detect errors training volume which may be associated with development of running related injuries. Based on the results from current study, increases in weekly training progression may become deleterious at a weekly increase above 30 % which is more than the 10 % rule, currently used as guideline for correct progression in weekly volume by runners and coaches. Still, no clear evidence for safe progression of weekly volume exists. But is seems like some individuals may tolerate weekly progressions around 20 to 25 %, at least for a short period of time.
This study examined the relationship between workload indicators used to quantify full training sessions in soccer. Participants were 28 semi-professional male soccer players age 22.9±4.2 years, height 177±5 cm, body mass 73.6±4.4 kg. Players' physical and physiological workload was monitored over 44 training sessions using GPS devices (10 Hz) and Heart-Rate (HR), respectively. After each training session, players' training perceived-exertion (RPE) was assessed using the Borg CR-10 scale. Players' Internal training load was assessed using the session-RPE and the Edwards methods. Total distance, distances covered at arbitrary selected High-intensity speed zones (≥18 and 21 km·h), bout frequency at speed higher than 18 and 21 km·h and work:rest ratio during training drills were considered as signs of physical work-load. Furthermore Player-load assumed as reflection of total center-of-mass acceleration was considered as representative of players' external-load. Very-large association of Player-load with Edwards and session-RPE methods were found. Total distance covered was large-to-very-large associated with Player-Load, Session-RPE and Edwards methods. This study findings provided evidence for the safe use of session-RPE, Edwards methods and Players-Load as valid indicators of training responses in soccer.
The purpose of this study was to examine and compare the criterion validity and test-retest reliability of the CR10 and CR100 rating of perceived exertion (RPE) scales for team sport athletes that undertake high intensity, intermittent exercise. Twenty one male Australian football (AF) players (age: 19.0 ± 1.8 years, body mass: 83.92 ± 7.88 kg) participated the first part (Part A) of this study which examined the construct validity of the session-RPE (sRPE) method for quantifying training load in AF. Ten male athletes (age: 16.1 ± 0.5 years) participated in the second part of the study (Part B), which compared the test-retest reliability of the CR10 and CR100 RPE scales. In Part A, the validity of the sRPE method was assessed by examining the relationships between sRPE, and objective measures of internal (i.e. heart rate) and external training load (i.e. distance travelled), collected from AF training sessions. Part B of the study assessed the reliability of sRPE through examining the test-retest reliability of sRPE during three different intensities of controlled intermittent running (10 km·hr, 11.5 km·hr and 13 km·hr). Results from Part A demonstrated strong correlations for CR10- and CR100-derived sRPE with measures of internal training load (Banisters TRIMP and Edwards TRIMP) (CR10: r = 0.83 and 0.83, and CR100: r = 0.80 and 0.81, p<0.05). Correlations between sRPE and external training load (Distance, higher speed running and player load) for both the CR10 (r = 0.81, 0.71 and 0.83) and CR100 (r = 0.78, 0.69 and 0.80) were significant (p<0.05). Results from Part B demonstrated poor reliability for both the CR10 (31.9% CV) and CR100 (38.6% CV) RPE scales following short bouts of intermittent running. Collectively, these results suggest both CR10 and CR100 derived sRPE methods have good construct validity for assessing training load in AF. The poor levels of reliability revealed under field testing indicate that the sRPE method may not be sensible to detecting small changes in exercise intensity during brief intermittent running bouts. Despite this limitation, the sRPE remains a valid method to quantify training loads in high intensity, intermittent team sport.
Although the potential link between running loads and soft-tissue injury is appealing, the evidence supporting or refuting this relationship in high-performance team sport athletes is nonexistent, with all published studies using subjective measures (e.g., ratings of perceived exertion) to quantify training loads. The purpose of this study was to investigate the risk of low-intensity (e.g., walking, jogging, total distances) and high-intensity (e.g., high acceleration and velocity efforts, repeated high-intensity exercise bouts) movement activities on lower body soft-tissue injury in elite team sport athletes. Thirty-four elite rugby league players participated in this study. Global positioning system data and the incidence of lower body soft-tissue injuries were monitored in 117 skill training sessions during the preseason and in-season periods. The frailty model (an extension of the Cox proportional regression model for recurrent events) was applied to calculate the relative risk of injury after controlling for all other training data. The risk of injury was 2.7 (95% confidence interval 1.2-6.5) times higher when very high-velocity running (i.e., sprinting) exceeded 9 m per session. Greater distances covered in mild, moderate, and maximum accelerations and low- and very low-intensity movement velocities were associated with a reduced risk of injury. These results demonstrate that greater amounts of very high-velocity running (i.e., sprinting) are associated with an increased risk of lower body soft-tissue injury, whereas distances covered at low and moderate speeds offer a protective effect against soft-tissue injury. From an injury prevention perspective, these findings provide empirical support for restricting the amount of sprinting performed in preparation for elite team sport competition. However, coaches should also consider the consequences of reducing training loads on the development of physical qualities and playing performance.
To investigate the physical demands of professional rugby league match-play using microtechnology, and to compare these demands with typical training activities used to prepare players for competition.
Prospective cohort study.
Thirty elite rugby league players participated in this study. Seven hundred and eighty-six. training data sets and 104 data sets from National Rugby League matches were collected over one playing season. Movement was recorded using a commercially available microtechnology unit (minimaxX, Catapult Innovations), which provided information on speeds, distances, accelerations, physical collisions and repeated high-intensity efforts.
Mean distances covered during match-play by the hit-up forwards, wide-running forwards, adjustables, and outside backs were 3,569 m, 5,561 m, 6,411 m, and 6,819 m, respectively. Hit-up forwards and wide-running forwards were engaged in a greater number of moderate and heavy collisions than the adjustables and outside backs, and more repeated high-intensity effort bouts per minute of play (1 bout every 4.8-6.3 min). The physical demands of traditional conditioning, repeated high-intensity effort exercise, and skill training activities were all lower than the physical demands of competition.
These results demonstrate that absolute distances covered during professional rugby league matches are greater for outside backs, while the collision and repeated high-intensity effort demands are higher for hit-up forwards and wide-running forwards. The specific physical demands of competitive play, especially those demands associated with collisions and repeated high-intensity efforts, were not well matched by those observed in traditional conditioning, repeated high-intensity effort exercise, and skills training activities. Further research is required to investigate whether modifications need to be made to these training activities to better prepare players for the demands of National Rugby League competition.
The aims of this study were to assess (a) the validity of total body load (TBL)-obtained from the global position system (GPS) devices-to quantify soccer training load, assessing its relationship with session rating of perceived exertion (session-RPE) and (b) to analyze the differences in terms of TBL and session-RPE among defenders, midfielders, and forwards. Twenty-two professional soccer players (Spanish first division, season 2007-2008; 26.74 ± 4.2 years; height 179.74 ± 4.04 cm; weight 73.7 ± 3.35 kg) participated in the study. During 13 training sessions composed predominantly of small-sided games, TBL and RPE multiplied by the minutes of session duration were determined using GPS and the 21-point scale, respectively. In each session, data from 10 players randomly selected and classified according to player position (defenders, midfielders, and forwards) were collected. Although session-RPE was a significant predictor of TBL (β = 0.23, p < 0.05), this method only accounted for 5% of the variance in TBL. No significant differences in terms of TBL and session-RPE were found regarding player position. The results of this study suggest that TBL is not a valid measure to quantify training load because it is not strongly correlated with session-RPE. Furthermore, TBL and session-RPE in small-sided soccer games do not vary according to player positions.
Muscle injuries constitute a large percentage of all injuries in football.
To investigate the incidence and nature of muscle injuries in male professional footballers.
Cohort study; Level of evidence, 2.
Fifty-one football teams, comprising 2299 players, were followed prospectively during the years 2001 to 2009. Team medical staff recorded individual player exposure and time-loss injuries. The first-team squads of 24 clubs selected by the Union of European Football Associations as belonging to the best European teams, 15 teams of the Swedish First League, and another 15 European teams playing their home matches on artificial turf pitches were included. A muscle injury was defined as "a traumatic distraction or overuse injury to the muscle leading to a player being unable to fully participate in training or match play."
In total, 2908 muscle injuries were registered. On average, a player sustained 0.6 muscle injuries per season. A squad of 25 players can thus expect about 15 muscle injuries per season. Muscle injuries constituted 31% of all injuries and caused 27% of the total injury absence. Ninety-two percent of all muscle injuries affected the 4 major muscle groups of the lower limbs: hamstrings (37%), adductors (23%), quadriceps (19%), and calf muscles (13%). Sixteen percent of the muscle injuries were reinjuries. These reinjuries caused significantly longer absences than did index injuries. The incidence of muscle injury increased with age. When separated into different muscle groups, however, an increased incidence with age was found only for calf muscle injuries and not for hamstring, quadriceps, or hip/groin strains.
Muscle injuries are a substantial problem for players and their clubs. They constitute almost one third of all time-loss injuries in men's professional football, and 92% of all injuries affect the 4 big muscle groups in the lower limbs.
To investigate the relationship between training load and injury in professional rugby league players;
Prospective cohort study;
Seventy-nine professional rugby league players (mean±SD age, 23.3±3.8 years) participated in this four-year study. A periodized field, strength, and power training program was implemented, with training loads progressively increased in the general preparatory phase of the season and reduced during the competitive phase of the season. Training loads and injuries were recorded for each training session.
Training load was significantly related (P<0.05) to overall injury (r=0.82), non-contact field injury (r=0.82), and contact field injury (r=0.80) rates. Significant relationships were also observed between the field training load and overall field injury (r=0.68), non-contact field injury (r=0.65), and contact field injury (r=0.63) rates. Strength and power training loads were significantly related to the incidence of strength and power injuries (r=0.63). There was no significant relationship between field training loads and the incidence of strength and power injuries. However, strength and power training loads were significantly (P<0.01) associated with the incidence of contact (r=0.75) and non-contact (r=0.82) field training injuries.
These findings suggest that the harder rugby league players train, the more injuries they will sustain, and that high strength and power training loads may contribute indirectly to field injuries. Monitoring of training loads and careful scheduling of field and gymnasium sessions to avoid residual fatigue is warranted to minimize the effect of training-related injuries on professional rugby league players.
Elite youth soccer players have a relatively high risk for injuries and illnesses due to increased physical and psychosocial stress. The aim of this study is to investigate how measures to monitor stress and recovery, and its analysis, provide useful information for the prevention of injuries and illnesses in elite youth soccer players.
53 elite soccer players between 15 and 18 years of age participated in this study. To determine physical stress, soccer players registered training and match duration and session rating of perceived exertion for two competitive seasons by means of daily training logs. The Dutch version of the Recovery Stress Questionnaire for athletes (RESTQ-Sport) was administered monthly to assess the psychosocial stress-recovery state of players. The medical staff collected injury and illness data using the standardised Fédération Internationale de Football Association registration system. ORs and 95% CIs were calculated for injuries and illnesses using multinomial regression analyses. The independent measures were stress and recovery.
During the study period, 320 injuries and 82 illnesses occurred. Multinomial regression demonstrated that physical stress was related to both injury and illness (range OR 1.01 to 2.59). Psychosocial stress and recovery were related the occurrence of illness (range OR 0.56 to 2.27).
Injuries are related to physical stress. Physical stress and psychosocial stress and recovery are important in relation to illness. Individual monitoring of stress and recovery may provide useful information to prevent soccer players from injuries and illnesses.
To study the injury characteristics in professional football and to follow the variation of injury incidence during a match, during a season and over consecutive seasons.
Prospective cohort study where teams were followed for seven consecutive seasons. Team medical staff recorded individual player exposure and time-loss injuries from 2001 to 2008.
European professional men's football.
The first team squads of 23 teams selected by the Union of European Football Associations as belonging to the 50 best European teams.
Injury incidence.
4483 injuries occurred during 566 000 h of exposure, giving an injury incidence of 8.0 injuries/1000 h. The injury incidence during matches was higher than in training (27.5 vs 4.1, p<0.0001). A player sustained on average 2.0 injuries per season, and a team with typically 25 players can thus expect about 50 injuries each season. The single most common injury subtype was thigh strain, representing 17% of all injuries. Re-injuries constituted 12% of all injuries, and they caused longer absences than non re-injuries (24 vs 18 days, p<0.0001). The incidence of match injuries showed an increasing injury tendency over time in both the first and second halves (p<0.0001). Traumatic injuries and hamstring strains were more frequent during the competitive season, while overuse injuries were common during the preseason. Training and match injury incidences were stable over the period with no significant differences between seasons.
The training and match injury incidences were stable over seven seasons. The risk of injury increased with time in each half of matches.
The aims of this study were to (1) determine the activity profiles of a large sample of English FA Premier League soccer players and (2) examine high-intensity running during elite-standard soccer matches for players in various playing positions. Twenty-eight English FA Premier League games were analysed during the 2005-2006 competitive season (n=370), using a multi-camera computerised tracking system. During a typical match, wide midfielders (3138 m, s=565) covered a greater distance in high-intensity running than central midfielders (2825 m, s= 73, P=0.04), full-backs (2605 m, s=387, P < 0.01), attackers (2341 m, s=575, P < 0.01), and central defenders (1834 m, s=256, P < 0.01). In the last 15 min of a game, high-intensity running distance was approximately 20% less than in the first 15-min period for wide midfielders (467 m, s=104 vs. 589 m, s=134, P < 0.01), central midfielders (429 m, s=106 vs. 534 m, s=99, P < 0.01), full-backs (389 m, s=95 vs. 481 m, s=114, P < 0.01), attackers (348 m, s=105 vs. 438 m, s=129, P < 0.01), and central defenders (276 m, s=93 vs. 344 m, s=80, P < 0.01). There was a similar distance deficit for high-intensity running with (148 m, s=78 vs. 193 m, s=96, P < 0.01) and without ball possession (229 m, s=85 vs. 278 m, s=97, P < 0.01) between the last 15-min and first 15-min period of the game. Mean recovery time between very high-intensity running bouts was 72 s (s=28), with a 28% longer recovery time during the last 15 min than the first 15 min of the game (83 s, s=26 vs. 65 s, s=20, P < 0.01). The decline in high-intensity running immediately after the most intense 5-min period was more evident in attackers (216 m, s=50 vs. 113 m, s=47, P < 0.01) and central defenders (182 m, s=26 vs. 96 m, s=39, P < 0.01). The results suggest that high-intensity running with and without ball possession is reduced during various phases of elite-standard soccer matches and the activity profiles and fatigue patterns vary among playing positions. The current findings provide valuable information about the high-intensity running patterns of a large sample of elite-standard soccer players, which could be useful in the development and prescription of specific training regimes.
The aim of this study was to examine the influence of perceived intensity, duration and load of matches and training on the incidence of injury in rugby league players. The incidence of injury was prospectively studied in 79 semi-professional rugby league players during the 2001 season. All injuries sustained during matches and training sessions were recorded. Training sessions were conducted from December to September, with matches played from February to September. The intensity of individual training sessions and matches was estimated using a modified rating of perceived exertion scale. Training load was calculated by multiplying the training intensity by the duration of the training session. The match load was calculated by multiplying the match intensity by the time each player participated in the match. Training load increased from December (278.3 [95% confidence interval, CI 262.2 to 294.5] units) to February (385.5 [95% CI 362.4 to 408.5] units), followed by a decline until September (98.4 [95% CI 76.5 to 120.4] units). Match load increased from February (204.0 [95% CI 186.2 to 221.8] units) to September (356.8 [95% CI 302.5 to 411.1] units). More training injuries were sustained in the first half of the season (first vs second: 69.2% vs 30.8%, P < 0.001), whereas match injuries occurred more frequently in the latter stages of the season (53.6% vs 46.4%, P < 0.001). A significant relationship (P < 0.05) was observed between changes in training injury incidence and changes in training intensity (r = 0.83), training duration (r = 0.79) and training load (r = 0.86). In addition, changes in the incidence of match injuries were significantly correlated (P < 0.05) with changes in match intensity (r = 0.74), match duration (r = 0.86) and match load (r = 0.86). These findings suggest that as the intensity, duration and load of rugby league training sessions and matches is increased, the incidence of injury is also increased.
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.
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.
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 < 0.01).
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.
We investigated the movement patterns of small-sided training games and compared these movement patterns with domestic, national, and international standard competition in elite women soccer players. In addition, we investigated the repeated-sprint demands of women's soccer with respect to the duration of sprints, number of sprint repetitions, recovery duration, and recovery intensity. Thirteen elite women soccer players [age (mean +/- SD) 21 +/- 2 years] participated in this study. Time-motion analysis was completed during training (n = 39) consisting of small-sided (i.e., three versus three and five versus five) training games, domestic matches against male youth teams (n = 10), Australian national-league matches (n = 9), and international matches (n = 12). A repeated-sprint bout was defined as a minimum of three sprints, with recovery of less than 21 seconds between sprints. The overall exercise to rest ratios for small-sided training games (1:13) were similar to or greater than domestic competition against male youth teams (1:15) and national-league (1:16) and international (1:12) competitions. During the international matches analyzed, 4.8 +/- 2.8 repeated-sprint bouts occurred per player, per match. The number of sprints within the repeated-sprint bouts was 3.4 +/- 0.8. The sprint duration was 2.1 +/- 0.7 seconds, and the recovery time between sprints was 5.8 +/- 4.0 seconds. Most recovery between sprints was active in nature (92.6%). In contrast to international competition, repeated-sprint bouts were uncommon in small-sided training games, domestic competition against male youth teams, and national-league competition. These findings demonstrate that small-sided training games simulate the overall movement patterns of women's soccer competition but offer an insufficient training stimulus to simulate the high-intensity, repeated-sprint demands of international competition.
Background The influence of fixture congestion on injury rates and team performance has only been scarcely investigated.
Objective To study associations between match load, recovery days, injury rates and team match performances in professional football.
Design Prospective cohort study.
Setting European professional football.
Participants 27 teams, all selected by the UEFA and all competing at the highest level of European football, playing 8 150 competitive matches during the 11-year study period were included.
Assessment of risk factors Injury rates and team match performances were compared depending on the number of recovery days between matches using two different cut offs (≤3 vs. >3 days and ≤4 vs. ≥6 days). Match load, injury rates and team match performances were also studied over extended match sequences during the season, each sequence containing five consecutive matches over a mean of 27 days (range 7–104 days).
Main outcome measurements Number of time loss injuries/1000 h of exposure and amount of matches won, lost or drawn.
Results Team performance showed no association with match load except for Europa League matches that indicated more matches lost with ≤3 days compared with >3 days recovery (P=.048). Total injury rates and muscle injury rates, specifically hamstring and quadriceps injuries, were increased in league matches with ≤4 days compared with ≥6 days recovery preceding the match (rate ratio [RR] 1.09, 95% CI 1.00–1.18, and RR 1.32, 95% CI 1.15–1.51, respectively) while no differences were found when using the other cut off (≤3 vs. >3 days). High match load during a match sequence was associated with an increase in muscle injury rates (P=.012).
Conclusions Fixture congestion was associated with increased muscle injury rates but had no, or very limited, influence on team match performances.
Variations in definitions and methodologies have created differences in the results and conclusions obtained from studies of football (soccer) injuries, making interstudy comparisons difficult. Therefore an Injury Consensus Group was established under the auspices of Fédération Internationale de Football Association Medical Assessment and Research Centre. A nominal group consensus model approach was used. A working document on definitions, methodology, and implementation was discussed by the group. Iterative draft statements were prepared and circulated to members of the group for comment before the final consensus statement was produced. Definitions of injury, recurrent injury, severity, and training and match exposures in football together with criteria for classifying injuries in terms of location, type, diagnosis, and causation are proposed. Proforma for recording players’ baseline information, injuries, and training and match exposures are presented. Recommendations are made on how the incidence of match and training injuries should be reported and a checklist of issues and information that should be included in published reports of studies of football injuries is presented.
Player activity profiles of match play provide valuable information for optimal athlete training prescriptions, competition strategies and managing load and recovery and are currently lacking in elite Australian-league (A-League) soccer. The aims of the study were therefore, to (a) determine match activity profiles for elite A-League soccer players and make match-half and positional comparisons, and (b) examine the effect of situational factors including evolving match status (drawing, winning, or losing) and goals being scored and conceded on selected match activity profile variables. Global positioning system tracking devices were used to determine activity profiles of 19 elite male adult soccer players during eight pre-season matches (n = 95 files). Total distance, average speed, high-intensity-running (HIR) distance, and very high-intensity running (VHIR) distance decreased from the first to the second half by 7.92%, 9.47%, 10.10%, and 10.99%, respectively. Midfielders covered 11.69% more total distance, 28.08% more HIR distance, and had a 10.93% higher average speed than defenders (p < 0.05; d = 1.90, 1.03, and 1.83, respectively). Attackers performed 27.50% and 30.24% less medium accelerations than defenders and midfielders, respectively (p < 0.01; d = 1.54, and 1.73). Whilst the team was winning, average speed was 4.17% lower than when the team was drawing (p < 0.05, d = 0.32). Scoring or conceding goals did not appear to affect HIR. This study adds to limited knowledge of match demands in elite A-League soccer. The match activity profiles provide descriptive benchmarks that could be used to make comparisons with other elite level soccer populations while also providing a framework for game-specific training prescription, competition strategy and load management. The generalization that defenders experience a relatively lower match load may be questionable given their relatively high acceleration and deceleration demands.
The present study examined the effect of a 20-day period of competition on salivary cortisol, mucosal immunity, and upper respiratory tract infections (URTI) in young male soccer players (n = 14). The players were monitored during the main under-19 Brazilian soccer championship, in which 7 matches were played in 20 days. Saliva samples were collected in the morning of each match and analyzed for cortisol and immunoglobulin A (IgA). Signs and symptoms of URTI were assessed across the study and a rating of perceived exertion (RPE) was obtained for each match. Compared with match 1, a significant increase in player RPE was observed in matches 4-7 (p < 0.05). Significant (p < 0.05) increases in the reporting of URTI occurred between matches 2 and 3, and 6 and 7, and this was accompanied by significant decreases in salivary IgA levels. Significant (p < 0.05) correlations were also seen between the individual reports of URTI and the decrease in IgA levels in match 2 (r = -0.60) and match 6 (r = -0.65). These results suggest that decrements in mucosal immunity, as measured by salivary IgA concentrations, may lead to a greater incidence of URTI in elite young soccer players. It may be speculated that the physiological and psychological stressors imposed by training and competition in a short timeframe are major contributing factors to these responses. Thus, the monitoring of salivary IgA could provide a useful and noninvasive approach for predicting URTI occurrences in young athletes during short-term competitions, especially if frequent sampling and rapid measurements are made.
Variations in definitions and methodologies have created differences in the results and conclusions obtained from studies of football (soccer) injuries; this has made interstudy comparisons difficult.
An Injury Consensus Group was established under the auspices of Fédération Internationale de Football Association Medical Assessment and Research Centre. Using a nominal group consensus model approach, a working document that identified the key issues related to definitions, methodology, and implementation was discussed by members of the group during a 2-day meeting. After this meeting, iterative draft statements were prepared and circulated to the members of the group for comment before the final consensus statement was produced.
Definitions of injury, recurrent injury, severity, and training and match exposures in football, together with criteria for classifying injuries in terms of location, type, diagnosis, and causation are proposed. Proforma for recording players' baseline information, injuries, and training and match exposures are presented. Recommendations are made on how the incidence of match and training injuries should be reported and a checklist of issues and information that should be included in published reports of studies of football injuries is presented.
The definitions and methodology proposed in the consensus statement will ensure that consistent and comparable results will be obtained from studies of football injuries.
In this study, we assessed the validity and reliability of 5 and 10 Hz global positioning systems (GPS) for measuring instantaneous velocity during acceleration, deceleration, and constant velocity while straight-line running. Three participants performed 80 running trials while wearing two GPS units each (5 Hz, V2.0 and 10 Hz, V4.0; MinimaxX, Catapult Innovations, Scoresby, VIC, Australia). The criterion measure used to assess GPS validity was instantaneous velocity recorded using a tripod-mounted laser. Validity was established using the standard error of the estimate (± 90% confidence limits). Reliability was determined using typical error (± 90% confidence limits, expressed as coefficient of variation) and Pearson's correlation. The 10 Hz GPS devices were two to three times more accurate than the 5 Hz devices when compared with a criterion value for instantaneous velocity during tasks completed at a range of velocities (coefficient of variation 3.1-11.3%). Similarly, the 10 Hz GPS units were up to six-fold more reliable for measuring instantaneous velocity than the 5 Hz units (coefficient of variation 1.9-6.0%). Newer GPS may provide an acceptable tool for the measurement of constant velocity, acceleration, and deceleration during straight-line running and have sufficient sensitivity for detecting changes in performance in team sport. However, researchers must account for the inherent match-to-match variation reported when using these devices.
In sports, the importance of optimizing the recovery-stress state is critical. Effective recovery from intense training loads often faced by elite athletes can often determine sporting success or failure. In recent decades, athletes, coaches, and sport scientists have been keen to find creative, new methods for improving the quality and quantity of training for athletes. These efforts have consistently faced barriers, including overtraining, fatigue, injury, illness, and burnout. Physiological and psychological limits dictate a need for research that addresses the avoidance of overtraining, maximizes recovery, and successfully negotiates the fine line between high and excessive training loads. Monitoring instruments like the Recovery-Stress Questionnaire for Athletes can assist with this research by providing a tool to assess their perceived state of recovery. This article will highlight the importance of recovery for elite athletes and provide an overview of monitoring instruments.
The aims of the study were to (a) determine the high-intensity activity patterns of soccer players at different performance levels and playing positions, (b) investigate temporary and end game fatigue in elite domestic and international soccer matches, and (c) quantify acceleration and maximal running speed profiles of elite soccer players. Elite domestic (n = 100) and international (n = 10) soccer players were analyzed using a multicamera computerized tracking system. No differences were found for high-intensity running distance (2,520 +/- 678 vs. 2,745 +/- 332 m), mean recovery time (67 +/- 15 vs. 71 +/- 26 seconds), or maximal running speed (7.76 +/- 0.31 vs. 7.66 +/- 0.34 mxs-1). The distance covered in high-intensity running irrespective of playing level was 18% lower (p < 0.05) in the last than in the first 15-minute period of the game (391 +/- 117 vs. 478 +/- 141 m). The decline in high-intensity running immediately after the most intense 5-minute period was similar between international (222 +/- 33 vs. 109 +/- 37 m or 51% decline) and elite domestic (243 +/- 81 vs. 114 +/- 51 m or 53% decline) players. Wide midfielders, central midfielders, fullbacks, and attackers covered a greater (p < 0.01) distance in high-intensity running than central defenders (3,243 +/- 625, 2,949 +/- 435, 2,806 +/- 408, 2,618 +/- 745 vs. 2,034 +/- 284 m). Results demonstrate that high-intensity running is reduced during various periods of elite soccer matches, and high-intensity activity profiles and fatigue patterns are similar between international and elite domestic players but vary markedly between playing positions. These data provide valuable information to the fitness coach regarding the high-intensity active profile of elite soccer players that could be used to develop soccer-specific training drills.
The aim of the present investigation was to provide a detailed analysis of the high intensity running activity completed by elite soccer players during match-play. A further aim of the study was to evaluate the importance of high intensity running activity to overall team success. Observations on individual match performance measures were undertaken on 563 outfield players (median of 8 games per player; range=1–57) competing in the English Premier League from 2003/2004 to 2005/2006 using a computerised tracking system (Prozone®, Leeds, England). High intensity activities selected for analysis included total high intensity running distance (THIR), total sprint distance (TSD) and the number and type of sprints undertaken. Total high intensity running distance in possession and without possession of the ball was also analysed. The THIR was dependant upon playing position with wide midfield (1 049±106 m) and central defenders (681±128 m) completing the highest and lowest distance respectively (p<0.001). High intensity activity was also related to team success with teams finishing in the bottom five (919±128 m) and middle ten (917±143 m) league positions completing significantly more THIR compared with teams in the top five (885±113 m) (p=0.003). The THIR and TSD also significantly declined during the 2nd half with the greatest decrements observed in wide midfield and attacking players (p<0.05). Both positional differences in high intensity activity and the observed change in activity throughout the game were also influenced by team success (p<0.05). The results of the present study indicate that high intensity activity in elite soccer match-play is influenced by both playing position and previous activity in the game. These activity patterns are also dependant upon success of the team. This may indicate that overall technical and tactical effectiveness of the team rather than high levels of physical performance per se are more important in determining success in soccer.
There is limited information regarding the validity and reliability of global positioning system (GPS) devices for measuring movement during team sports. The aim of this study was to assess the validity and intra-model reliability of different GPS devices for quantifying high-intensity, intermittent exercise performance. Two moderately trained males each completed eight bouts of a standard circuit that consisted of six laps around a 128.5-m course involving intermittent exercise. Distance and speed were collected concurrently at 1-Hz using six GPS devices (2 SPI-10, 2 SPI Elite and 2 WiSPI, GPSports, Canberra, Australia). Performance measures were: (1) total distance covered for each bout and each lap; (2) high-intensity running distance (>14.4 km h(-1), HIR); very high-intensity running distance (>20 km h(-1), VHIR) during each bout. Peak speed was also measured during a 20-m sprint at the start of each lap of the circuit (N=192). Actual distance was measured using a measuring tape. Mean (+/-SD) circuit total distance was significantly different between each of the GPS devices (P<0.001); however, all devices were within 5m of the actual lap distance and had a good level of reliability (coefficient of variation (CV) <5%). The CV for total distance (3.6-7.1%) and peak speed (2.3-5.8%) was good-to-moderate, but poor for HIR (11.2-32.4%) and VHIR (11.5-30.4%) for all GPS devices. These results show that the GPS devices have an acceptable level of accuracy and reliability for total distance and peak speeds during high-intensity, intermittent exercise, but may not be provide reliable measures for higher intensity activities.
Overtraining is primarily related to sustained high load training, often coupled with other stressors. Studies in animal models have suggested that unremittingly heavy training (monotonous training) may increase the likelihood of developing overtraining syndrome. The purpose of this study was to extend our preliminary observations by relating the incidence of illnesses and minor injuries to various indices of training.
We report observations of the relationship of banal illnesses (a frequently cited marker of overtraining syndrome) to training load and training monotony in experienced athletes (N = 25). Athletes recorded their training using a method that integrates the exercise session RPE and the duration of the training session. Illnesses were noted and correlated with indices of training load (rolling 6 wk average), monotony (daily mean/standard deviation), and strain (load x monotony).
It was observed that a high percentage of illnesses could be accounted for when individual athletes exceeded individually identifiable training thresholds, mostly related to the strain of training.
These suggest that simple methods of monitoring the characteristics of training may allow the athlete to achieve the goals of training while minimizing undesired training outcomes.
To define the causes of injuries to players in English professional football during competition and training.
Lost time injuries to professional and youth players were prospectively recorded by physiotherapists at four English League clubs over the period 1994 to 1997. Data recorded included information related to the injury, date and place of occurrence, type of activity, and extrinsic Playing factors.
In all, 67% of all injuries occurred during competition. The overall injury frequency rate (IFR) was 8.5 injuries/1000 hours, with the IFR during competitions (27.7) being significantly (p < 0.01) higher than that during training (3.5). The IFRs for youth players were found to increase over the second half of the season, whereas they decreased for professional players. There were no significant differences in IFRs for professional and youth players during training. There were significantly (p < 0.01) injuries in competition in the 15 minute periods at the end of each half. Strains (41%), sprains (20%), and contusions (20%) represented the major types of injury. The thigh (23%), the ankle (17%), knee (14%), and lower leg (13%) represented the major locations of injury, with significantly (p < 0.01) more injuries to the dominant body side. Reinjury counted for 22% of all injuries. Only 12% of all injuries were caused by a breach of the rules of football, although player to player contact was involved in 41% of all injuries.
The overall level of injury to professional footballers has been showed to be around 1000 times higher times higher than for industrial occupations generally regarded as high risk. The high level of muscle strains, in particular, indicates possible weakness in fitness training programmes and use of warming up and cooling down procedures by clubs and the need for benchmarking players' levels of fitness and performance. Increasing levels of injury to youth players as a season progresses emphasizes the importance of controlling the exposure of young players to high levels of competition.
Variations in definitions and methodologies have created differences in the results and conclusions obtained from studies of football injuries; this has made inter‐study comparisons difficult.
An Injury Consensus Group was established under the auspices of FIFA Medical Assessment and Research Centre. Using a nominal group consensus model approach, a working document that identified the key issues related to definitions, methodology and implementation was discussed by members of the group during a 2‐day meeting. Following this meeting, iterative draft statements were prepared and circulated to members of the group for comment before the final consensus statement was produced.
Definitions of injury, recurrent injury, severity and training and match exposures in football together with criteria for classifying injuries in terms of location, type, diagnosis and causation are proposed. Proforma for recording players' baseline information, injuries and training and match exposures are presented. Recommendations are made on how the incidence of match and training injuries should be reported and a checklist of issues and information that should be included in published reports of studies of football injuries is presented.
The definitions and methodology proposed in the consensus statement will ensure that consistent and comparable results will be obtained from studies of football injuries.
To investigate the relationship between physical fitness and team success in soccer, and to test for differences in physical fitness between different player positions.
Participants were 306 male soccer players from 17 teams in the two highest divisions in Iceland. Just before the start of the 1999 soccer season, the following variables were tested: height and weight, body composition, flexibility, leg extension power, jump height, and peak O2 uptake. Injuries and player participation in matches and training were recorded through the 4-month competitive season. Team average physical fitness was compared with team success (final league standing) using a linear regression model. Physical fitness was also compared between players in different playing positions.
A significant relationship was found between team average jump height (countermovement jump and standing jump) and team success (P = 0.009 and P = 0.012, respectively). The same trend was also found for leg extension power (P = 0.097), body composition (% body fat, P = 0.07), and the total number of injury days per team (P = 0.09). Goalkeepers demonstrated different fitness characteristics from outfield players. They were taller and heavier, more flexible in hip extension and knee flexion, and had higher leg extension power and a lower peak O2 uptake. However, only minor differences were observed between defenders, midfield players, and attackers.
Coaches and medical support teams should pay more attention to jump and power training, as well as preventive measures and adequate rehabilitation of previous injuries to increase team success.
Prevention, diagnosis, and treatment of the overtraining syndrome: Joint consensus statement of the European College of Sport Science and the American College of sports Medicine
- Meeusen