Global Positioning System-Derived Workload Metrics and Injury Risk in Team-Based Field Sports: A Systematic Review

Predicting Injuries in Elite Female Football Players With Global-Positioning-System and Multiomics Data

PURPOSE

Injury prevention is a crucial aspect of sports, particularly in high-performance settings such as elite female football. This study aimed to develop an injury prediction model that incorporates clinical, Global-Positioning-System (GPS), and multiomics (genomics and metabolomics) data to better understand the factors associated with injury in elite female football players.

METHODS

We designed a prospective cohort study over 2 seasons (2019-20 and 2021-22) of noncontact injuries in 24 elite female players in the Spanish Premiership competition. We used GPS data to determine external workload, genomic data to capture genetic susceptibility, and metabolomic data to measure internal workload.

RESULTS

Forty noncontact injuries were recorded, the most frequent of which were muscle (63%) and ligament (20%) injuries. The baseline risk model included fat mass and the random effect of the player. Six genetic polymorphisms located at the DCN, ADAMTS5, ESRRB, VEGFA, and MMP1 genes were associated with injuries after adjusting for player load (P < .05). The genetic score created with these 6 variants determined groups of players with different profile risks (P = 3.1 × 10-4). Three metabolites (alanine, serotonin, and 5-hydroxy-tryptophan) correlated with injuries. The model comprising baseline variables, genetic score, and player load showed the best prediction capacity (C-index: .74).

CONCLUSIONS

Our model could allow efficient, personalized interventions based on an athlete's vulnerability. However, we emphasize the necessity for further research in female athletes with an emphasis on validation studies involving other teams and individuals. By expanding the scope of our research and incorporating diverse populations, we can bolster the generalizability and robustness of our proposed model.

Wearable Sensors and the Evaluation of Physiological Performance in Elite Field Hockey Players

Sports performance tracking has gained a lot of interest and widespread use in recent years, especially in elite and sub-elite sports. This makes it possible to improve the effectiveness of training, to calibrate and balance workloads according to real energy expenditure, and to reduce the likelihood of injuries due to excessive physical stress. In this context, the aim of this review was to map the scientific literature on wearable devices used in field hockey, evaluating their characteristics and the available evidence on their validity in measuring physiological and movement parameters. A systematic investigation was carried out by employing five electronic databases and search terms that incorporated field hockey, wearables, and performance analysis. Two independent reviewers conducted assessments of the 3401 titles and abstracts for inclusion, and at the end of the screening process, 102 full texts were analyzed. Lastly, a total of 23 research articles that specifically concentrated on field hockey were incorporated. The selected papers dealt with performance monitoring (6 papers), technical analysis and strategy game (6), injury prevention (1), and physiological measurements (10). To appraise the quality of the evaluations, the Oxford quality scoring system scale was employed. The extraction of information was carried out through the utilization of the participants, intervention, comparison, and outcomes (PICOS) format. The analysis encompassed research studies that implemented wearable devices during training and competitive events. Among elite field hockey competitions, GPS units were identified as the predominant wearable, followed by heart rate monitors. The intraclass correlation coefficient (ICC) related to wearable devices showed reasonably high between-trial ICCs ranging from 0.77 to 0.99. The utilization of wearable devices in field hockey primarily centers around the measurement of player activity profiles and physiological demands. The presence of discrepancies in sampling rates and performance bands makes it arduous to draw comparisons between studies. Nevertheless, this analysis attested to the fact that wearable devices are being employed for diverse applications in the realm of field hockey.

Effect of the Length of the Microcycle on the Daily External Load, Fatigue, Sleep Quality, Stress, and Muscle Soreness of Professional Soccer Players: A Full-Season Study

BACKGROUND

The aim of this study was to analyze the effect of the length of the microcycle (ie, training period from the day after the match to the following match) on the daily external load and perceived wellness of professional soccer players (Spanish LaLiga Smartbank).

HYPOTHESIS

The length of the microcycle has a significant effect on the daily external load and perceived wellness.

STUDY DESIGN

Longitudinal study.

LEVEL OF EVIDENCE

Level 3.

METHODS

Data were collected daily during a full season using perceived wellness questionnaires and electronic performance and tracking systems.

RESULTS

The length of the microcycle had a significant effect on volume- and intensity-related external load variables. There were differences between short, regular, and long microcycles depending on the day of the microcycle. These differences were observed in all external load variables. However, no significant differences between short, regular, or long microcycles were found on match day for any external load variable, except for high-intensity decelerations. Regarding the perceived wellness, the length of the microcycle had no effect on these variables, and there were no significant interactions between the length and the day of the microcycle.

CONCLUSION

The length of the microcycle had a significant effect on volume- and intensity-related external load variables, but no significant effect on perceived wellness was observed.

CLINICAL RELEVANCE

These data may help strength and conditioning coaches understand that workload periodization should take this contextual variable into account, especially for external training load. In addition, this study may serve as a guide for practitioners to know the physical requirements of professional soccer players in Spanish LaLiga Smartbank, because the weekly external load profile and perceived wellness have been reported for different lengths of the microcycles. Thus, these data may be used for player load management.

Moving beyond velocity derivatives; using global positioning system data to extract sequential movement patterns at different levels of rugby league match-play

This study aims to (a) quantify the movement patterns during rugby league match-play and (b) identify if differences exist by levels of competition within the movement patterns and units through the sequential movement pattern (SMP) algorithm. Global Positioning System data were analysed from three competition levels; four Super League regular (regular-SL), three Super League (semi-)Finals (final-SL) and four international rugby league (international) matches. The SMP framework extracted movement pattern data for each athlete within the dataset. Between competition levels, differences were analysed using linear discriminant analysis (LDA). Movement patterns were decomposed into their composite movement units; then Kruskal-Wallis rank-sum and Dunn post-hoc were used to show differences. The SMP algorithm found 121 movement patterns comprised mainly of "walk" and "jog" based movement units. The LDA had an accuracy score of 0.81, showing good separation between competition levels. Linear discriminant 1 and 2 explained 86% and 14% of the variance. The Kruskal-Wallis found differences between competition levels for 9 of 17 movement units. Differences were primarily present between regular-SL and international with other combinations showing less differences. Movement units which showed significant differences between competition levels were mainly composed of low velocities with mixed acceleration and turning angles. The SMP algorithm found 121 movement patterns across all levels of rugby league match-play, of which, 9 were found to show significant differences between competition levels. Of these nine, all showed significant differences present between international and domestic, whereas only four found differences present within the domestic levels. This study shows the SMP algorithm can be used to differentiate between levels of rugby league and that higher levels of competition may have greater velocity demands.Highlights This study shows that movement patterns and movement units can be used to investigate team sports through the application of the SMP frameworkOne hundred and twenty-one movement patterns were found to be present within rugby league match-play, with the walk- and jog-based movement units most prevalent. No movement pattern was unique to a single competition level.Further analysis revealed that the majority of movement units analysed had significant differences between international and domestic rugby league, whereas only four movement units (i.e. f,m,n,q) had significant differences within the two domestic rugby league levels.International rugby league had higher occurrences of the movement patterns consisting of higher velocity movement units (ie. T,S,y). This suggests that international rugby league players may need greater high velocity exposure in training.

Effect of playing position and microcycle days on the acceleration speed profile of elite football players

The aim of this study was to analyse the differences in the A-S profile of elite football players induced by playing position and the microcycle day. Players belonged to a second division club in the Spanish La Liga competition. They were classified into five playing positions: central defenders (CD), full backs (FB), midfielders (MF), wide midfielders (WMF) and forwards (FW). Microcycle days were categorised according to the days until matchday (MD, MD-1, MD-2, MD-3, MD-4 and MD-5). Data was collected along six microcycles, including one match per microcycle. The variables analysed were: maximal theoretical acceleration (A₀), maximal theoretical speed (S₀), maximal acceleration (ACC_max), maximal speed (S_max) and A-S slope (AS_slope). Significant differences were found within positions and microcycle day for all variables (p < 0.05). Match day (MD) showed greater values than the training sessions in A₀, ACC_max and S_max (p < 0.05). The highest values for variables associated with acceleration capabilities were found in CD on MD, whereas speed variables were higher in WMF. MD-2 showed the lowest values in all variables except for AS_slope. Maximal acceleration and sprint abilities are therefore affected by playing position. Wide positions showed the highest speed capacity, and CD presented a likely acceleration profile. Higher values for all variables concerning the microcycle day, were achieved on MD, and were not reproduced during training with the consequent injury risk and performance decrease it takes.

Using global navigation satellite systems for modeling athletic performances in elite football players

This study aims to predict individual Acceleration-Velocity profiles (A-V) from Global Navigation Satellite System (GNSS) measurements in real-world situations. Data were collected from professional players in the Superleague division during a 1.5 season period (2019–2021). A baseline modeling performance was provided by time-series forecasting methods and compared with two multivariate modeling approaches using ridge regularisation and long short term memory neural networks. The multivariate models considered commercial features and new features extracted from GNSS raw data as predictor variables. A control condition in which profiles were predicted from predictors of the same session outlined the predictability of A-V profiles. Multivariate models were fitted either per player or over the group of players. Predictor variables were pooled according to the mean or an exponential weighting function. As expected, the control condition provided lower error rates than other models on average (p = 0.001). Reference and multivariate models did not show significant differences in error rates (p = 0.124), regardless of the nature of predictors (commercial features or extracted from signal processing methods) or the pooling method used. In addition, models built over a larger population did not provide significantly more accurate predictions. In conclusion, GNSS features seemed to be of limited relevance for predicting individual A-V profiles. However, new signal processing features open up new perspectives in athletic performance or injury occurrence modeling, mainly if higher sampling rate tracking systems are considered.

Elite Junior Australian Football Players With Impaired Wellness Are at Increased Injury Risk at High Loads

BACKGROUND

Elite junior Australian football players experience high training loads across levels of competition and training. This, in conjunction with impaired wellness, can predispose athletes to injury.

HYPOTHESIS

Elite junior Australian football players exposed to high loads with poor wellness are more likely to be at risk of injury than those with improved wellness.

STUDY DESIGN

Longitudinal prospective cohort study.

LEVEL OF EVIDENCE

Level 3.

METHODS

Data were collected and analyzed from 280 players across the 2014 season. Internal load was measured via session rating of perceived exertion. Player wellness was reported according to ratings of sleep quality, fatigue, soreness, stress, and mood. Week- and month-based training load measures were calculated, representing a combination of absolute and relative load variables. Principal component analysis factor loadings, based on 17 load and wellness variables, were used to calculate summed variable covariates. Injury was defined as "any injury leading to a missed training session or competitive match." Associations between covariates and injury risk (yes/no) were determined via logistic generalized estimating equations.

RESULTS

A significant interaction term between load and wellness on injury was found [odds ratio (OR) 0.76; 95% CI 0.62-0.92; P < 0.01), indicating that wellness acts as a "dimmer switch" of load on injury. Further, there was evidence of moderated mediation (OR 0.71; 95% CI 0.57-0.87; P < 0.01). When wellness was low, injury risk started to increase substantially at a 1-week load of 3250 au.

CONCLUSIONS

Subjective measures of training load are associated with injury risk through a nonlinear relationship. This relationship is further influenced by player wellness, which can amplify the risk of injury. There is evidence that higher stress is linked with injury and that soreness and sleep mediate any stress-injury relationship.

CLINICAL RELEVANCE

Coaching efforts to manage training load and player adaptive responses, including wellness, may reduce the risk of injury, with stress, soreness, and sleep particularly relevant at this level.

Impact and workload are dominating on-field data monitoring techniques to track health and well-being of team-sports athletes

Participation in sports has become an essential part of healthy living in today's world. However, injuries can often occur during sports participation. With advancements in sensor technology and data analytics, many sports have turned to technology-aided, data-driven, on-field monitoring techniques to help prevent injuries and plan better player management. This review searched three databases, Web of Science, IEEE, and PubMed, for peer-reviewed articles on on-field data monitoring techniques that are aimed at improving the health and well-being of team-sports athletes. It was found that most on-field data monitoring methods can be categorized as either player workload tracking or physical impact monitoring. Many studies covered during this review attempted to establish correlations between captured physical and physiological data, as well as injury risk. In these studies, workloads are frequently tracked to optimize training and prevent overtraining in addition to overuse injuries, while impacts are most often tracked to detect and investigate traumatic injuries. This review found that current sports monitoring practices often suffer from a lack of standard metrics and definitions. Furthermore, existing data-analysis models are created on data that are limited in both size and diversity. These issues need to be addressed to create ecologically valid approaches in the future.

Pain Variability and Subjective Function in Individuals With Patellofemoral Pain: A Short Report

Individuals with patellofemoral pain (PFP) experience discomfort during various functional activities. Long-term pain is a common consequence of PFP, yet little is known about daily pain variability. Our study consisted of 25 individuals with PFP who completed the Anterior Knee Pain Scale (AKPS) and recorded their daily pain over 10 days. Pain was evaluated using 2 measures of intensity (baseline pain, 10-day average pain) and 2 measures of variability (mean square of successive differences, probability of acute change). Associations between AKPS and the 4 pain measures were calculated with Pearson correlations. We calculated a linear regression to examine the amount of variance in the AKPS explained by the 4 pain measures. Greater mean square of successive differences values were moderately associated with lesser AKPS scores (r = -0.648, P < .001). Mean square of successive differences and 10-day averaged pain were the strongest predictors of AKPS (R2 = 0.565, P < .001). Pain variability provided a unique perspective on the pain experience and predicted patient-oriented function in individuals with PFP.

Physiological Monitoring Detected Changes During Women's Soccer Anterior Cruciate Ligament Injury

A growing number of studies utilizing wearable technologies are examining the influence of the autonomic nervous system (ANS) on intense training, recovery, and injury risk. Exercise biometric (EB) data were collected on collegiate, female soccer players during a preseason camp. One player sustained an anterior cruciate ligament (ACL) injury. Baseline anthropometric and EB data were compared to non-injured, position-matched teammates.

All players had similar baseline testing. The injured athlete had a higher body mass index (BMI) and slower vision reaction time (RT). On the day of her injury (DOI), relative percentage heart rate recovery (tHRR) between intense training sets was calculated. Relative percentage tHRR was much lower for the injured athlete, indicating reduced recovery between training sets immediately prior to the injury. Also on DOI, the injured athlete had a lower glomerular filtration rate (GFR).

In addition to BMI and RT differences, the lower relative percentage tHRR and GFR on the DOI observed for the injured athlete may reflect an imbalanced ANS recovery, and potentially to risk factors leading to her ACL injury.

Athlete Workloads During Collegiate Women's Soccer Practice: Implications for Return to Play

CONTEXT

Athlete monitoring via wearable technology is often used in soccer athletes. Although researchers have tracked global outcomes across soccer seasons, little information exists on athlete loads during individual practice drills. Understanding these demands is important for athletic trainers in making decisions about return to play.

OBJECTIVE

To provide descriptive information on total distance, total player load (PL), total distance per minute, and PL per minute for practice drill structures and game play by player position among female soccer athletes across a competitive season.

DESIGN

Retrospective observational study.

SETTING

National Collegiate Athletic Association Division I university.

PATIENTS OR OTHER PARTICIPANTS

A total of 32 female collegiate soccer players (age = 20 ± 1 years, height = 168.75 ± 4.28 cm).

INTERVENTION(S)

Athletes wore a single global positioning system and triaxial accelerometer unit during all practices and games in a single soccer season. Individual practice drills were labeled by the team's strength and conditioning coach and binned into physical, technical and tactical skills and large- and small-sided competition drill structures.

MAIN OUTCOME MEASURE(S)

Descriptive analyses were used to assess the median total distance, total PL, total distance per minute, and PL per minute by drill structure and player position (defender, forward or striker, and midfielder) during practices and games.

RESULTS

Large- and small-sided competition drills imposed the greatest percentage of workload across all measures for each position (approximately 20% of total practice), followed by physical drills. When comparing technical and tactical skills drills, we found that technical skills drills required athletes to cover a greater distance (approximately 17% for technical skills and 15% for tactical skills), and tactical skills drills required higher play intensity during practices across all positions (approximately 18% for technical skills and 13% for tactical skills). Defenders had the highest median PL outcomes of all positions during practices.

CONCLUSIONS

Different practice drill types imposed various levels of demands, which simulated game play, on female soccer athletes. Athletic trainers and other clinicians may use this information in formulating objective return-to-play guidelines for injured collegiate women's soccer players.

Training Load and Injury: Causal Pathways and Future Directions

Causal pathways between training loads and the mechanisms of tissue damage and athletic injury are poorly understood. Here, the relation between specific training load measures and metrics, and causal pathways of gradual onset and traumatic injury are examined. Currently, a wide variety of internal and external training load measures and metrics exist, with many of these being commonly utilized to evaluate injury risk. These measures and metrics can conceptually be related to athletic injury through the mechanical load-response pathway, the psycho-physiological load-response pathway, or both. However, the contributions of these pathways to injury vary. Importantly, tissue fatigue damage and trauma through the mechanical load-response pathway is poorly understood. Furthermore, considerable challenges in quantifying this pathway exist within applied settings, evidenced by a notable absence of validation between current training load measures and tissue-level mechanical loads. Within this context, the accurate quantification of mechanical loads holds considerable importance for the estimation of tissue damage and the development of more thorough understandings of injury risk. Despite internal load measures of psycho-physiological load speculatively being conceptually linked to athletic injury through training intensity and the effects of psycho-physiological fatigue, these measures are likely too far removed from injury causation to provide meaningful, reliable relationships with injury. Finally, we used a common training load metric as a case study to show how the absence of a sound conceptual rationale and spurious links to causal mechanisms can disclose the weaknesses of candidate measures as tools for altering the likelihood of injuries, aiding the future development of more refined injury risk assessment methods.