Local Positioning System-Derived External Load of Female and Male Varsity Ice Hockey Players During Regular Season Games

Abstract

PurposeThe purposes of this study were to quantify the external load for female and male varsity ice hockey players during regular season games using a local positioning system (LPS), compare LPS-derived external load between sexes and positions, and compare skating distances in absolute and relative speed zones.MethodsData were collected for 21 female (7 defense, 14 forwards; 20.0 ± 1.4 yrs., 69.1 ± 6.7 kg, 167.1 ± 5.4 cm) and 25 male (8 defense, 17 forwards; 21.9 ± 1.1 yrs., 85.9 ± 5.4 kg, 181.1 ± 5.2 cm) varsity ice hockey players. Measures included skating distance (total, and in absolute and relative speed zones), peak skating speed, peak acceleration and deceleration, accumulative acceleration load, and number of accelerations, decelerations, turns, skating transitions, direction changes, and impacts.ResultsFemale and male players had a high external load during games, with average peak skating speeds >28 km/h and average skating distances >4.4 km. Most LPS-derived measures showed greater external load in males than females (p < 0.05). Forwards skated further at higher speeds compared to defense in both sexes (p < 0.001). Skating distances were significantly different when comparing absolute and relative speed zones (p < 0.001), with absolute speed zones potentially overestimating skating at very slow, very fast, and sprint speeds and underestimating skating at slow and moderate speeds.ConclusionThis was the first study to measure external load in female ice hockey players with a LPS. Both female and male varsity players had high external loads during games, with forwards having greater external load at higher intensities and defense having greater external load at lower intensities. Sex and positional differences outline the importance of individualized athlete monitoring.

The recovery of muscle function and glycogen levels following game‐play in young elite male ice hockey players

“…The total distance covered during the game and distance covered at high skating speeds are in line with previous time‐motion studies in competitive ice hockey 3,4 and with a more pronounced high‐intensity activity pattern in forwards compared to defensemen confirming previous results 3,5,25 . In addition, the average heart rate during the game was ~77% of HR MAX (between‐shifts included) with peak values approaching maximal levels, as previously reported 7 .…”

“…The total distance covered during the game and distance covered at high skating speeds are in line with previous time-motion studies in competitive ice hockey 3,4 and with a more pronounced high-intensity activity pattern in forwards compared to defensemen confirming previous results. 3,5,25 In addition, the average heart rate during the game was ~77% of HR MAX (between-shifts included) with peak values approaching maximal levels, as previously reported. 7 In contrast, the 31% reduction in muscle glycogen postgame is less than previously reported, 1,7,17 however, the starting level was higher in the present study, meaning that in absolute levels, the glycogen degradation was comparable with previous observations.…”

A Framework for the Standardization of Game Analysis in Ice Hockey

“…Understanding the game and training demands can lead to the development of game-replicating training programs and permit coaches to prescribe an optimal training dose that increases performance and minimizes risk of either overtraining or undertraining. Accordingly, research in ice hockey has utilized various methods of athlete monitoring such as video time-motion analysis, 2,4 heart rate (HR) monitoring, 3,[10][11][12][13][14][15] local positioning system technology, [16][17][18] and wearable sensor/ accelerometer technology. 1,[19][20][21][22][23][24] Primarily, these investigations have focused on the game demands, [2][3][4]16,18,19 but some studies have also included analyses on the training demands.…”

“…Accordingly, research in ice hockey has utilized various methods of athlete monitoring such as video time-motion analysis, 2,4 heart rate (HR) monitoring, 3,[10][11][12][13][14][15] local positioning system technology, [16][17][18] and wearable sensor/ accelerometer technology. 1,[19][20][21][22][23][24] Primarily, these investigations have focused on the game demands, [2][3][4]16,18,19 but some studies have also included analyses on the training demands. 1,[10][11][12][13][14][15][20][21][22][23]…”

The physiology of ice hockey performance: An update

“…Per shift, this may accumulate to ~23 s spent at maximal or near maximal skating speed for forwards 11 . Furthermore, Gamble et al 15 observed higher peak sprint speed, as well as peak acceleration and deceleration intensities, in varsity level forward compared to defensemen players. Thus, these studies clearly suggest an accentuated emphasis on intensity of play in forwards compared to defensemen, which is reflected by often more brief and less frequent on‐ice shifts for forwards, but with limited differences in fitness characteristics between positional roles 5,6,16,17 .…”