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The clubs who entered early into big data, now reap the reward. Databases are now so important and grow up so fast that the clubs who do not jump on the bandwagon could find themselves drew away from the top.

The databases by themselves are not enough, their analysis is what allows the staff, the coaches, the decision-makers and the players to improve their performances

Data for a rigorous management

Professional soccer teams became companies worth millions of dollars; therefore, they must generate profit and must undergo rigorous and relevant management. Player transfer, performance prediction, individual shape and injury prediction are all key indicators that allow the decision-makers, coaches and staff to make the best possible decisions (1), in the interest of the club and the players.

External load data take it over

Today, professional staff are used to analyze data coming from the accelerometers and GPS systems worn by the players during the games and training sessions. The physical performances are quantified using the numbers of accelerations, sprints, direction changes, distance ran, kicks etc. Beyond those measured parameters, there are numerous computations (2) regarding the numbers of expected goals (xG) or assists or key interventions for each player (3). The vital importance of sport scientists in the elite clubs is already proven.

And the internal load data?

External load data focus on the constraints imposed by the physical aspect of the game, but only marginally take into account the internal load of the payers. The latter is the physiological impact imposed by the external constraints and the psychological factors around the payers (high stakes, tension with other players/coach/family etc.). For example, a 100 meters sprint will not have the same physiological impact whether the player is in good shape, is tired or if he is stressed by the high stakes of the game or disappointing passed performances for example. 

The professional soccer clubs all have an extended use of the external load, but few of them use the internal load. Yet, the latter is essential because it gives a direct access to the constraints imposed on the physiology of each player. Moreover, it allows to predict the performances, anticipate fatigue and prevent it.

inCORPUS® a unique tool for analysis

inCORPUS® is the only tool using a 10-minute test that allows a measure of the players’ internal load. Thanks to a unique analysis, inCOPRUS® identifies the profiles of good shape or fatigue and therefore is essential to make the best possible decisions for the performances of the club and the player. The evaluation of the internal load is objective, doable at the player’s home or at the club. The construction of external load databases was essential a few years ago, today the construction of such databases is essential. These databases are the future of professional soccer and necessary for the clubs.  

Cross-reference data

It is essential to cross-reference the external and internal load data so that the approach to performance is global and the decision-making process as relevant as possible. It is the only way to better control the risk during match preparation, players recruitment and evaluation and prediction of the performances.

Scientific references

(1)          Ćwiklinski, B.; Giełczyk, A.; Choraś, M. Who Will Score? A Machine Learning Approach to Supporting Football Team Building and Transfers. Entropy Basel Switz. 2021, 23 (1). https://doi.org/10.3390/e23010090.

(2)          Bunker, R. P.; Thabtah, F. A Machine Learning Framework for Sport Result Prediction. Appl. Comput. Inform. 2019, 15 (1), 27–33. https://doi.org/10.1016/j.aci.2017.09.005.

(3)          Baboota, R.; Kaur, H. Predictive Analysis and Modelling Football Results Using Machine Learning Approach for English Premier League. Int. J. Forecast. 2019, 35 (2), 741–755. https://doi.org/10.1016/j.ijforecast.2018.01.003.



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