Brownlee, T

Girard, J

Komar, J

McRobert, AP

English

LJMU Research Online (Liverpool John Moores University)

Performance Analysis in Professional Ice HockeyUsing Tracking Data to combine Tactical and Physiological Analysis• No difference of activity demand between regular season and play-offs• Time on ice is strongly correlated with Heart Rate and can be used to quantify the physiological demand • The “rate of recovery” is independent on the intensity and duration of the previous boutRESULTS & DISCUSSION- Mainly due to the different available players for the different lines, a significant difference appeared in Time on Ice in Activity between player’s position (offensive line between defensive line). Although the total time per game is very stable between games for each player, a high variability is observed within a game (between thirds), showing that a player highly used in the first third is usually less used in the last third (Figure 2). Player’s activity management has to be considered when preparing the tactics of the game.- The Heart Rate indicators (max HR, time spent above 80% of maxHR, time spent above 90% of maxHR) were all correlated with the time on ice in activity (Figure 3) – with all p < 0.001. John Komar1, Jules Girard2, Thomas E. Brownlee3, Allistair P. McRobert3INTRODUCTIONIce hockey is a sport that requires repeated, high-intensity bouts of skating, interspersed with on-ice gliding and rest between bouts, leading to high rotations between players (i.e., every 40 seconds in average) (1). Although heart rate (HR) has been used to assess the fitness demands of such an intermittent activity (2), in the present research we sought to investigate the HR of players in relation to actual time on ice versus time in activity and time at rest. METHODDuring a regular season and during the playoffs (quarter-final to the final) of the French National Hockey League, the HR of every player was recorded during all the games using a Firstbeat® wireless system. This allowed physiological tracking of players specific to periods spent in activity (on ice with the clock running) and resting periods (based on player tracking data). Both time series were subsequently synchronized (Figure 1). In addition to regular measurement (HRmax, time above 80%HRmax, time above 90%HRmax, see (2)), “rate of recovery” was calculated as the exponential decrease of HR during the 60 s from the end of each bout of play. The sampling rate of all measurement was set at 1Hz. Figure 1. Tracking of Time On Ice in activity (on ice with the clock running) and heart rate of a ice hockey player in a playoff game.- In orange: time on icewhile the clock is running- In green: time on ice whilethe clock is stoppedHeart Rate (bpm)Time (sec)REFERENCES1 - Swartz, T. B. (2017). Hockey Analytics. In N. Balakrishnan, T. Colton, B. Everitt, W. Piegorsch, F. Ruggeri, & J. L. Teugels (eds), Wiley, Chichester, UK. 2 - Barry A. Spiering, Meredith H. Wilson, Daniel A. Judelson, AND Kenneth W. Rundell. (2003). Evaluation of Cardiovascular Demands of Game Play and Practice in Women’s Ice Hockey. Journal of strength and condition research, 17(2), 329-333. • Are the heart rate indicators correlated with the time in activity?• Is there a difference in player’s activity between the regular season and the play-off?• Investigate the use of the rate of discovery as an indicator of fatigue during the seasonTiers 1 Tiers 2 Tiers 3TIME ON ICE10 - HUBACEKPlay    00:44 Rest    03:3871 - GUTTIGPlay    00:51 Rest    04:1437 - BEDINPlay    00:43 Rest    04:040102030Time (min)0102030Time (min)0102030Time (min)Figure 2. Time on Ice in activity for one player during the first half of the seasonm+1sdm-1sd1 National institute of Education, Nanyang Technological University, 1 Nanyang Walk, Singapore, john.Komar@nie.edu.sg2 Normandy University, UNIROUEN, Boulevard Siegfried, Mont-Saint-Aignan, France, jules.girard@outlook.com3 Liverpool John Moores University, 5 Primrose Hill, Liverpool, L3 2EX, {T.brownlee,A.P.McRobert}@ljmu.ac.uk- I addition, no significant difference between the games of the regular season and the play-off was observed neither in time on ice nor in heart rate indicators, showing that the - The rate of recovery (i.e. the exponential coefficient) was not correlated with the time of ice. In addition, the value of this coefficient did not show any differencebetween the different thirds, neither between the regular season and the play-offs• Is Heart rate monitoring necessary in Ice Hockey?• Can we use tracking playerto assess the demand of agame?• Are the play-off games more intense?y = 0,4388x + 42,771R² = 0,3407y = 0,6288x + 73,512R² = 0,2666Figure 3. Association between Time on Ice in Activity and the time spent above 80% of the HR max – the color shows the time in the season (game 1 early season and game 16 play offs) Figure 4. Association between Time on Ice in Activity and the time spent above 90% of the HR max – the color shows the time in the season (game 1 early season and game 16 play offs) Time spent above 80% of HR max (sec)Time spent above 90% of HR max (sec)Time on ice in activity (sec) Time on ice in activity (sec)Figure 4. Average value of the exponential coefficient per third during the game. Third 1 Third 2 Third 3Exponential coefficient

PERFORMANCE ANALISYS IN PROFESIONAL ICE HOCKEY: USING TRACKING DATA TO COMBINE TACTICAL AND PHYSIOLOGICAL ANALYSIS

http://researchonline.ljmu.ac.uk/id/eprint/12941/1/ECSS_2019_PRAGUE.pdf

PERFORMANCE ANALISYS IN PROFESIONAL ICE HOCKEY: USING TRACKING DATA TO COMBINE TACTICAL AND PHYSIOLOGICAL ANALYSIS

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