Applying econometric models that relate player quality to the physical tracking data, remarkable differences can be found between the specific positions within a football team. Starting off with centre backs, the models showed that a low average sprint distance is an indicator of a high-quality defender. An interpretation for this could be that defenders with a high EPI do not have to compensate their defensive errors by closing gaps at sprinting pace.
For full backs, the total sprint distance covered during a match appears to be a significant indicator of quality. Better full backs turn out to cover a higher distance at sprint pace. Full backs that makes long sprints distances are probably the ones that take part in attacks, making assists and scoring goals and have therefore a high EPI. The same effect of the sprint distance applies to wingers. However, we observe something else when it comes to wingers: the models show that wingers that are able to perform longer sprints at a higher age are in general of higher quality. To give a numerical example: two identical wingers aged 25, only differing in their average sprint distance by 1 meter, results on average in an EPI difference of 90. For strikers, the models show that a lower distance covered at running pace and sprint pace is an indicator of higher player quality. Apparently, strikers that are less active in their movements are in general better than strikers that run and sprint a lot, probably decreasing their efficiency when it comes to converting scoring opportunities. For midfielders, further research needs to be done as it turns out to be hard to capture the many different roles a midfielder can have. For example, a midfielder could be a playmaker, a box-to-box player or a sweeper in front of the defense.
The analysis has taken into account the age of a player, the quality of a player’s teammates and the trend that player quality in the Dutch leagues, in general, is diminishing. For the age of a player, it appears that the relationship with player quality is nonlinear. In fact, it was found that the average player has its peak in EPI around the age of 27.7 after which the EPI diminishes in general. However, differences can be observed across positions. For instance, wingers appear to peak earlier in their career whereas the peak for fullbacks appears to occur later than 27.7.
Remiqz, a developer of a big-data platform that determines the values of players in professional football, advises professional football clubs and players with scientific insights with respect to strategies, finance and the recruitment of players. By making use of the Euro Club Index (ECI), Remiqz offers a trustworthy and accurate quality measure of players, the Euro Player Index (EPI).
JOHAN Sports is a global player in GPS tracking and analytics. Their reliable sensors collect motion and heart data, which can be analysed in a web and mobile environment to get insights into the performance of players during and after their activities. JOHAN focuses on reliable measurements, easy to use software platform and compatibility with other tools.
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