The relationship between accelerometer and GPS derived data in elite men’s hockey competition Rodney Kennedy1, Owen Magee1 & Gerard McMahon2 1Ulster University, 2Sports Institute Northern Ireland INTRODUCTION The advancements in micro-technology have enabled the quantification of external load in many team sports using GPS derived data. However, it has been proposed that an accelerometer derived variable, such as player load (PL), may provide a superior measurement system [1]. The aim of this study was to examine the relationship between PL and distance covered in hockey competition. Defenders completed less relative distance (MID P < 0.001, d = 0.95; FOR P < 0.001, d = 1.24) and had lower relative load (MID P < 0.001, d = 0.86; FOR P < 0.001, d = 1.15) than the other positions. There were very large correlations between relative distance and load for all positions (r = 0.702-0.927, P = 0.01) and overall (r = 0.872, P < 0.01). The relative distance to load relationship was weaker in DEF compared with MID (Z = 3.48, P = 0.0005) and FOR (Z = 2.14, P = 0.0324). Table 1. Absolute and relative data (mean ± SD), with correlations between distance and load. Absolute Duration (mins) Distance (m) Load (AU) r Defenders 46.8 ± 12.4 a,b 5463 ± 1226 491 ± 111 0.902 Midfielders 39.9 ± 8.1 5125 ± 910 475 ± 87 0.911 Forwards 39.4 ± 7.0 5161 ± 903 479 ± 79 0.956 All Players 42.2 ± 10.1 5258 ± 1036 482 ± 94 0.910 Relative Distance (m∙min-1) Load (AU∙min-1) 118 ± 11 a,b 10.7 ± 1.5 a,b 0.702 a,b 130 ± 13 12.1 ± 1.9 0.927 132 ± 11 12.2 ± 1.3 0.872 126 ± 13 11.6 ± 1.7 METHOD With institutional ethics approval, 25 elite male hockey players wore tracking devices (OptimEye S5, Catapult Sports, Australia) in 8 international matches. Players were classified as defenders (DEF), midfielders (MID) and forwards (FOR). Absolute and relative values were determined for PL and distance. A one-way ANOVA was used to compare groups, with the Bonferroni post-hoc test used to identify any differences. Cohen’s effect size (d) was calculated to establish the magnitude of differences. Pearson’s correlation coefficients (r) were calculated to determine the relationship between PL and distance. The Fisher Z test was used to compare the relationships between groups. Abbreviation: AU, arbitrary units a Significantly different from forwards (P < 0.05). b Significantly different from midfielders (P < 0.05) CONCLUSIONS The strong relationships between these variables suggest that PL is simply a proxy for distance covered and it appears to be heavily influenced by the vertical accelerations that occur during foot strike at any running speed. Therefore, additional research is required to examine how PL can be modified to fully represent all hockey specific activities. The numerical spread of data may have influenced the positional relationships for the relative values. RESULTS There were no differences between positions for absolute distance or load, with only trivial to small effect sizes. DEF however played more absolute minutes than the other positions (MID P = 0.003, d = 0.65; FOR P = 0.001, d = 0.72). There were very large correlations between absolute distance and load for all positions (r = 0.902-0.956, P = 0.01) and overall (r = 0.910, P < 0.01). The absolute distance to load relationship was not different between positions. REFERENCES 1. Boyd, L.J., Ball, K. & Aughey, R.J. (2011). The reliability of MinimaxX accelerometers for measuring physical activity in Australian Football. International Journal of Sports Physiology and Performance, 6(3), 311-321.