Variability of within-step acceleration and daily wellness monitoring in Collegiate American Football.

Objectives: It is commonplace to consider accelerometer load and any resultant neuromuscular fatigue in training programs. With these data becoming accepted in sport alongside wellness questionnaires this study aimed to investigate if a deeper analysis of the accelerometry data can provide actionable insight into training-induced disruptions.

Design: Accelerometer data from Collegiate American Football athletes (n=63) were collected during training and matches across a regular season.

Methods: These data were processed to: identify instances of high speed running, extract step waveforms from those sections, and determine the variability of those waveforms via a within- and between-section co-efficient of multiple determination. Athletes completed wellness questionnaires prior to sessions that were used to flag areas of muscle soreness as well as fatigue, or disturbed sleep quality. Linear mixed models were used to assess associations between inter stride variability and flags in wellness/soreness markers.

Results: An increase in acute (7d) load saw an increased stride variability in these athletes. Feeling less fatigued and/or lower muscle soreness was associated with higher stride variability.

Conclusions: The assessment of variability has the potential to identify athletes who are displaying physical symptoms that would indicate the need to modify training.