Planning Training Workload in Football Using Small-Sided Games’ Density

Sangnier S, Cotte T, Brachet O, Coquart J, Tourny C

The purpose was to assess the relation between training workload and
SSGs’ density. The 33 densities data (41 practice games
and 3 full games) were analyzed through global positioning
system (GPS) data collected from 25 professional soccer players (80.7 ± 7.0 kg; 1.83 ± 0.05 m; 26.4 ± 4.9 years). From
total distance, distance metabolic power, sprint distance, and
acceleration distance, the data GPS were divided into 4 categories: endurance, power, speed, and strength. Statistical
analysis compared the relation between GPS values and
SSGs’ densities, and 3 methods were applied to assess models (R-squared, root-mean-square error, and Akaike information
criterion). The results suggest that all the GPS data match the
player’s essential athletic skills. They were all correlated with
the game’s density. Acceleration distance, deceleration distance, metabolic power, and total distance followed a logarithmic regression model, whereas distance and number of sprints
follow a linear regression model. The research reveals options
to monitor the training workload. Coaches could anticipate the
load resulting from the SSGs and adjust the field size to the
players’ number. Taking into account the field size during
SSGs enables coaches to target the most favorable density
for developing expected physical qualities. Calibrating intensity
during SSGs would allow coaches to assess each athletic skill
in the same conditions of intensity as in the competition.