2203. An Algorithm For Quantifying Accelerometry Data In Ice Hockey: Identifying A Reliable G-force Profile

Malachy P. McHugh1, Susan Y. Kwiecien1, Julianna Villella1, Dominic McHugh2, Stephen J. Nicholas1

1Nicholas Institute of Sports Medicine and Athletic Trauma, New York, NY. 2Digital Forensics Ireland Ltd, Belfast, United Kingdom. (Sponsor: Malachy P McHugh, FACSM)


PURPOSE: There is little consensus on how best to use accelerometry data to quantify loads imposed on athletes in team sports. The purpose of this study was to develop a time-based analysis of G-forces in ice hockey games and establish reliable load metrics.
METHODS: Skaters on a male junior hockey team playing in the United States Hockey League wore triaxial accelerometers during 46 games (total 841 player-games). Accelerations in 3 planes of motion were recorded at 100 Hz and the resultant G-force was calculated for each time interval. Time spent above 1.1G, 1.2G, etc. was calculated for 0.1G increments up to 6.0G and was then expressed as a percentage of the player’s time on ice (TOI) for each game. The G-force threshold at which no player’s time exceeded their TOI was identified as the threshold representing on-ice activity. Intra-subject coefficients of variation (CoV) were calculated at each G-force threshold for each player and averaged across players.
RESULTS: Time above 1.1G exceeded TOI for more than 50% of player-games and averaged 102±46% TOI. Time above 1.2G exceeded TOI for only 1.5% of player-games and averaged 59±19% of TOI. Time above 1.3G did not exceed TOI for any player-game and averaged 41±8% of TOI (range 20-75% of TOI). Times above each subsequent G-force threshold precipitously declined from 31±6% of TOI for time above 1.4G, to 0.9±0.4% for time above 3.0G and 0.06±0.04% for time above 6.0G.Intra-subject CoV ranged from a low of 11.4% for time above 1.5G to a high of 38.7% for time above 6.0G. The CoVs for time above 1.4G to 1.7G were very similar (11.6%, 11.4%, 11.5%, 11.6%), with CoVs progressively increasing at each subsequent G-force threshold. Inter-subject CoV exceeded intra-subject CoV at every G-force threshold with a low of 19% for time above 1.3G to a high of 57.8% for time above 6.0G. On average inter-subject CoV was 1.9±0.3 times higher than intra-subject CoV.
CONCLUSIONS: Time spent above 1.3G in a hockey game represents the load associated with a player’s TOI. The times above 1.4G, 1.5G, 1.6G and 1.7G were the most reliable metrics and accounted for 31±6%, 24±5%, 19±4% and 15±5% of TOI. The low intra-subject variability and high inter-subject variability indicate that players have signature G-force profiles. The times above 1.4-1.7G can be used to quantify the load imposed on a player in a game.