Monitoring Players' Readiness Using Predicted Heart-Rate Responses to Soccer Drills

To examine the ability of multivariate models to predict the heart-rate (HR) responses to some specific training drills from various global positioning system (GPS) variables and to examine the usefulness of the difference in predicted vs actual HR responses as an index of fitness or readiness to perform.

All data were collected during 1 season (2016-17) with players' soccer activity recorded using 5-Hz GPS and internal load monitored using HR. GPS and HR data were analyzed during typical small-sided games and a 4-min standardized submaximal run (12 km·h^-1). A multiple stepwise regression analysis was used to identify which combinations of GPS variables showed the largest correlations with HR responses at the individual level (HR_ACT, 149 [46] GPS/HR pairs per player) and was further used to predict HR during individual drills (HR_PRED). Then, HR predicted was compared with actual HR to compute an index of fitness or readiness to perform (HR_Δ, %). The validity of HR_Δ was examined while comparing changes in HR_Δ with the changes in HR responses to a submaximal run (HR_RUN, fitness criterion) and as a function of the different phases of the season (with fitness being expected to increase after the preseason).

HR_PRED was very largely correlated with HR_ACT (r = .78 [.04]). Within-player changes in HR_Δ were largely correlated with within-player changes in HR_RUN (r = .66, .50-.82). HR_Δ very likely decreased from July (3.1% [2.0%]) to August (0.8% [2.2%]) and most likely decreased further in September (-1.5% [2.1%]).

HR_Δ is a valid variable to monitor elite soccer players' fitness and allows fitness monitoring on a daily basis during normal practice, decreasing the need for formal testing.