Abstract

Sanders, GJ, Roll, B, Peacock, CA, and Kollock, RO. Maximum movement workloads and high-intensity workload demands by position in NCAA Division I collegiate football. J Strength Cond Res 34(7): 1974-1981, 2020-The purpose of the study was to quantify the average and maximum (i.e., peak) movement workloads, and the percent of those workloads performed at high intensity by NCAA Division I football athletes during competitive games. Using global positioning system devices (Catapult Sports), low, moderate, and high and total multidirectional movement workloads were quantified by each position. Strategically achieving maximal workloads may improve both conditioning and rehabilitation protocols for athletes as they prepare for competition or return to play after an injury. A total of 40 football athletes were included in the analysis. For the data to be included, athletes were required to participate in ≥75% of the offensive or defensive snaps for any given game. There was a total of 286 data downloads from 13 different games for 8 different football positions. Data were calculated and compared by offensive and defensive position to establish the mean, SD, and maximum workloads during competitive games. The percent high-intensity workload profile was established to assess the total number and percent of high-intensity movement workloads by position. The profile was calculated by dividing a position's maximal high-intensity movement workload by the total (e.g., sum of maximal low, moderate, and high-intensity movements) movement workload. One-way analysis of variances revealed that there was a main effect of football position for total movement workloads and the percent of workloads performed at high intensities (p ≤ 0.025 for all). Maximal high-intensity workloads were 1.6-4.3 times greater than average high-intensity workloads, and the percent of total workloads performed at high intensities varied greatly by position. Strategically training for and using maximal movement workloads can help ensure that athletes are achieving workloads that are similar to the greatest demands of a competitive game.

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