Continuous monitoring of internal end external game and trainingload in professional soccer: innovative possibilities for performance-optimalisation and injury prevention.

During last decade, technological advances during last decade allowed to quantify training and match load of elite team sports in a valid and reliable way. These developments have resulted in an increased use of player tracking tools, and, correspondingly, the increase in research output focusing on novel load indicators. Various studies in professional soccer have described the load during pre-season and in-season periods examining external load measured by global positioning systems (GPS), video tracking, or accelerometry. Internal load was examined as well, generally quantified by rating of perceived exertion (RPE) or heart rate (HR) measures. This research provided valuable insights in training practices and match loads in professional soccer. However, to impact on training outcomes, research focusing on associations between load indicators and changes in fitness or injury risk is warranted. Such insights may aid in improving monitoring strategies to optimize (team) performance and decrease injury risk.

First, the state of knowledge about relationships between load indicators and training outcomes in professional soccer was systematically reviewed. Despite the availability of more detailed training load indicators nowadays, there is few evidence for the relevance of load indicators in relation to training outcomes. In particular, the usefulness of external load indicators, measured by modern athlete tracking technologies such as GPS and LPS, remains relatively unexamined. Additionally, the association between load indicators and injury is even less examined. The implementation of continuous monitoring of external and internal load indicators throughout full seasons in combination with the investigation of relationships between these load indicators’ association and changes in fitness or injury may improve load management strategies.

For the other studies, a professional soccer team was monitored over two full seasons. The external and internal were quantified for training sessions and matches. The external load was quantified using 10 Hz GPS technology and accelerometry. The internal load was obtained using RPE multiplied by duration (sRPE method). Furthermore, perceived wellness data such as fatigue, sleep quality and general muscle soreness were collected for players. Additionally, all injuries were diagnosed and recorded by members of the medical staff.

In the second study, the impact of different techniques and settings for detecting high-intensity efforts using GPS data was examined. It was observed that setting changes in filtering techniques and minimum durations affect the number of high-speed running, sprint and acceleration efforts detected with GPS. Therefore, GPS data of a given training session or match may be differently exported depending on the applied software program or data processing settings in the software itself. Therefore, consistency in data processing is highly recommended. This is crucial when using external load data for practice as well as for research.

The relationship between external load indicators and RPE was examined in the third study. This relationship was examined using machine learning techniques. Decelerations were determined as important external load indicators, next to earlier examined external load indicators. In addition, the predictive ability of RPE was equally for group models in comparison with individual models. These insights can be applied to optimize load monitoring dashboards in professional soccer.

The fourth study focused on the prediction of future perceived wellness based on preceding load and perceived wellness. It was revealed that the external and/or internal load in combination with preceding perceived wellness resulted in the best predictive performances. The inclusion of cumulative load of previous days did not improve the predictive performances. This study indicated the importance of including both acute load and preceding perceived wellness in a holistic monitoring approach.

In the fifth study, training and match load of a professional goalkeeper were quantified along with the investigation of relationships between load indicators and subsequent perceived wellness. Insights were provided about the load undertaken by a goalkeeper and perceived wellness throughout a season in preparation towards, during and after match days. Weak relationships were found between load indicators and perceived wellness. This may indicate that more position-specific load indicators are required for goalkeepers.

Finally, the association between load indicators and overuse injuries was examined in the sixth study. It was found that mainly external load indicators were associated with increased or decreased injury risk. Cumulative weekly loads for distance covered and deceleration efforts (<-1 m.s-2) were associated with increased injury risks. Additionally, acute:chronic workload ratios (ACWR) were examined. This is a ratio between 1-weekly and 4-weekly cumulative loads to identify spikes in load. Exposing players to large relative changes in load may increase injury risk. A high ACWR for high-speed running (>20 km.h-1) was associated with a higher risk for injury. On the contrary, protective effects were found for medium ACWR for acceleration (>1 m.s-2) and deceleration (<-1 m.s-2) efforts as well as RPE multiplied by duration. For optimizing load management in professional soccer, the monitoring of various external and internal load indicators over different time frames and for ACWR is recommended.

In conclusion, a combination of external and internal load indicators should be considered in a multifactorial monitoring approach for evidence-based decision making with respect to load management, perceived player wellness and injury risk. This may benefit both the long-term player development as well as the overall team performance.