The Challenge of Evaluating the Intensity of Short Actions in Soccer: A New Methodological Approach Using Percentage Acceleration

PURPOSE: There are several approaches to quantifying physical load in team sports using positional data. Distances in different speed zones are most commonly used. Recent studies have used acceleration data in addition in order to take short intense actions into account. However, the fact that acceleration decreases with increasing initial running speed is ignored and therefore introduces a bias. The aim of our study was to develop a new methodological approach that removes this bias. For this purpose, percentage acceleration was calculated as the ratio of the maximal acceleration of the action (a(max,action)) and the maximal voluntary acceleration (a(max)) that can be achieved for a particular initial running speed (percentage acceleration [%] = a(max,action) / a(max) * 100). METHODS: To define a(max), seventy-two highly trained junior male soccer players (17.1 ± 0.6 years) completed maximal sprints from standing and three different constant initial running speeds (v(init); trotting: ~6.0 km·h(–1); jogging: ~10.8 km·h(–1); running: ~15.0 km·h(–1)). RESULTS: The a(max) was 6.01 ± 0.55 from a standing start, 4.33 ± 0.40 from trotting, 3.20 ± 0.49 from jogging and 2.29 ± 0.34 m·s(–2) from running. The a(max) correlated significantly with v(init) (r = –0.98) and the linear regression equation of highly-trained junior soccer players was: a(max) = –0.23 * v(init) + 5.99. CONCLUSION: Using linear regression analysis, we propose to classify high-intensity actions as accelerations >75% of the a(max), corresponding to acceleration values for our population of >4.51 initiated from standing, >3.25 from trotting, >2.40 from jogging, and >1.72 m·s(–2) from running. The use of percentage acceleration avoids the bias of underestimating actions with high and overestimating actions with low initial running speed. Furthermore, percentage acceleration allows determining individual intensity thresholds that are specific for one population or one single player.