Analysing Motion Characteristics and Metabolic Power in Elite Male Handball Players
DOI:
https://doi.org/10.51224/SRXIV.159Keywords:
position data, performance analysis, big data, LPS, player loadAbstract
This study analysed physiological demands of male handball players based on position data from 77 professional handball matches from the German Handball Bundesliga. Distance covered by wings, backcourts, and pivots in different velocity zones and metabolic power were investigated. Results showed that total distance covered varied with playing position with wings covering 3568 ± 1459 m in 42 ± 17 min, backs covering 2462 ± 1145 m in 29 ± 14 min, and pivots covering 2445 ± 1052 m in 30 ± 13 min per game. Wings covered more distance using greater running velocities than backs and pivots, while backs covered the largest distance per minute playing time. Distance covered and equivalent distance showed moderate to large interaction effects between wings and backs (p < .01, ES = 0.73) and between wings and pivots (p < .01, ES = 0.86). The results underline the need for an individualized management of training loads and the potential of using information about locomotion accelerations and decelerations to obtain more precise descriptions of physiological demands underlying handball game performance at the highest level of competition. Future studies should investigate the influence of physical performance on smaller match sequences, like ball possession phases.
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References
Akenhead, R., & Nassis, G. P. (2016). Training load and player monitoring in high-level football: Current practice and perceptions. International Journal of Sports Physiology and Performance, 11(5), 587–593. https://doi.org/10.1123/ijspp.2015-0331
Blauberger, P., Marzilger, R., & Lames, M. (2021). Validation of player and ball tracking with a local positioning system. Sensors, 21(4), 1465. https://doi.org/10.3390/s21041465
Bourdon, P. C., Cardinale, M., Murray, A., Gastin, P., Kellmann, M., Varley, M. C., Gabbett, T. J., Coutts, A. J., Burgess, D. J., Gregson, W., & Cable, N. T. (2017). Monitoring athlete training loads: Consensus statement. International Journal of Sports Physiology and Performance, 12(s2), S2-161-S2-170. https://doi.org/10.1123/IJSPP.2017-0208
Bradley, P. S., & Ade, J. D. (2018). Are current physical match performance metrics in elite soccer fit for purpose or is the adoption of an integrated approach needed? International Journal of Sports Physiology and Performance, 13(5), 656–664. https://doi.org/10.1123/ijspp.2017-0433
Büchel, D., Jakobsmeyer, R., Döring, M., Adams, M., Rückert, U., & Baumeister, J. (2019). Effect of playing position and time on-court on activity profiles in german elite team handball. International Journal of Performance Analysis in Sport, 19(5), 832–844. https://doi.org/10.1080/24748668.2019.1663071
Cardinale, M., Whiteley, R., Hosny, A. A., & Popovic, N. (2017). Activity profiles and positional differences of handball players during the World Championships in Qatar 2015. International Journal of Sports Physiology and Performance, 12(7), 908–915. https://doi.org/10.1123/ijspp.2016-0314
di Prampero, P. E., Fusi, S., Sepulcri, L., Morin, J. B., Belli, A., & Antonutto, G. (2005). Sprint running: A new energetic approach. Journal of Experimental Biology, 208(14), 2809–2816. https://doi.org/10.1242/jeb.01700
di Prampero, P. E., & Osgnach, C. (2018). Metabolic power in team sports - Part 1: An update. International Journal of Sports Medicine, 39(08), 581–587. https://doi.org/10.1055/a-0592-7660
Dos’Santos, T., Thomas, C., Comfort, P., & Jones, P. A. (2018). The effect of angle and velocity on change of direction biomechanics: An angle-velocity trade-off. Sports Medicine, 48(10), 2235–2253. https://doi.org/10.1007/s40279-018-0968-3
Fleureau, A., Lacome, M., Buchheit, M., Couturier, A., & Rabita, G. (2020). Validity of an ultra-wideband local positioning system to assess specific movements in handball. Biology of Sport, 37(4), 351. https://doi.org/10.5114/biolsport.2020.96850
Gómez-Carmona, C. D., Bastida-Castillo, A., Ibáñez, S. J., & Pino-Ortega, J. (2020). Accelerometry as a method for external workload monitoring in invasion team sports. A systematic review. PLOS ONE, 15(8), e0236643. https://doi.org/10.1371/journal.pone.0236643
González-Haro, P. J., Gómez-Carmona, C. D., Bastida-Castillo, A., Rojas-Valverde, D., Gómez-López, M., & Pino-Ortega, J. (2020). Analysis of playing position and match statusrelated differences in external load demands on amateur handball: A case study. Revista Brasileira de Cineantropometria & Desempenho Humano, 22, e71427. https://doi.org/10.1590/1980-0037.2020v22e71427
Gray, A. J., Shorter, K., Cummins, C., Murphy, A., & Waldron, M. (2018). Modelling movement energetics using global positioning system devices in contact team sports: Limitations and solutions. Sports Medicine, 48(6), 1357–1368. https://doi.org/10.1007/s40279-018-0899-z
Guerrero-Calderón, B., Klemp, M., Castillo-Rodriguez, A., Morcillo, J. A., & Memmert, D. (2021). A new approach for training-load quantification in elite-level soccer: Contextual factors. International Journal of Sports Medicine, 42(8), 716–723. https://doi.org/10.1055/a-1289-9059
Hoppe, M. W., Baumgart, C., Polglaze, T., & Freiwald, J. (2018). Validity and reliability of GPS and LPS for measuring distances covered and sprint mechanical properties in team sports. PLoS ONE, 13(2), 1–21. https://doi.org/10.1371/journal.pone.0192708
Hoppe, M. W., Baumgart, C., Slomka, M., Polglaze, T., & Freiwald, J. (2017). Variability of metabolic power data in elite soccer players during pre-season matches. Journal of Human Kinetics, 58(1), 233–245. https://doi.org/10.1515/hukin-2017-0083
Jakobsmeyer, Rasmus, Schnittker, Reinhard, Timmermann, Robert, Zorn, Rene, Rückert, Ulrich, & Baumeister, Jochen. (2013). Running performance analysis in basketball using recorded trajectory data. In Peters, Derek & O’Donoghue, Peter (Eds.), Performance Analysis of Sport IX. Routledge.
Karcher, C., & Buchheit, M. (2014). On-court demands of elite handball, with special reference to playing positions. Sports Medicine, 44(6), 797–814. https://doi.org/10.1007/s40279-014-0164-z
Klemp, M., Wunderlich, F., & Memmert, D. (2021). In-play forecasting in football using event and positional data. Scientific Reports, 11(1), 24139. https://doi.org/10.1038/s41598-021-03157-3
Lepschy, H., Wäsche, H., & Woll, A. (2020). Success factors in football: An analysis of the German Bundesliga. International Journal of Performance Analysis in Sport, 20(2), 150–164. https://doi.org/10.1080/24748668.2020.1726157
Linke, D., Link, D., & Lames, M. (2020). Football-specific validity of TRACAB’s optical video tracking systems. PLoS ONE, 15(3), e0230179. https://doi.org/10.1371/journal.pone.0230179
Malone, S., Solan, B., Collins, K., & Doran, D. (2017). The metabolic power and energetic demands of elite Gaelic football match play. The Journal of Sports Medicine and Physical Fitness, 57(5). https://doi.org/10.23736/S0022-4707.16.06233-2
Manchado, C., Pueo, B., Chirosa-Rios, L. J., & Tortosa-Martínez, J. (2021). Time–motion analysis by playing positions of male handball players during the European Championship 2020. International Journal of Environmental Research and Public Health, 18(6), 2787. https://doi.org/10.3390/ijerph18062787
Manchado, C., Tortosa Martínez, J., Pueo, B., Cortell Tormo, J. M., Vila, H., Ferragut, C., Sánchez Sánchez, F., Busquier, S., Amat, S., & Chirosa Ríos, L. J. (2020). High-performance handball player’s time-motion analysis by playing positions. International Journal of Environmental Research and Public Health, 17(18), 6768. https://doi.org/10.3390/ijerph17186768
Manzi, V., Impellizzeri, F., & Castagna, C. (2014). Aerobic fitness ecological validity in elite soccer players: A metabolic power appraoch. Journal of Strength and Conditioning Research, 28(4), 6.
Mernagh, D., Weldon, A., Wass, J., Phillips, J., Parmar, N., Waldron, M., & Turner, A. (2021). A comparison of match demands using ball-in-play versus whole match data in professional soccer players of the English championship. Sports, 9(6), 76. https://doi.org/10.3390/sports9060076
Miguel, M., Oliveira, R., Loureiro, N., García-Rubio, J., & Ibáñez, S. J. (2021). Load measures in training/match monitoring in soccer: A systematic review. International Journal of Environmental Research and Public Health, 18(5), 2721. https://doi.org/10.3390/ijerph18052721
Minetti, A. E., & Pavei, G. (2018). Update and extension of the ‘Equivalent Slope’ of speed changing level locomotion in humans: A computational model for shuttle running. Journal of Experimental Biology, 221, jeb.182303. https://doi.org/10.1242/jeb.182303
Nobari, H., Khalili, S. M., Oliveira, R., Castillo-Rodríguez, A., Pérez-Gómez, J., & Ardigò, L. P. (2021). Comparison of official and friendly matches through acceleration, deceleration and metabolic power measures: A full-season study in professional soccer players. International Journal of Environmental Research and Public Health, 18(11), 5980. https://doi.org/10.3390/ijerph18115980
Osgnach, C., Poser, S., Bernardini, R., Rinaldo, R., & di Prampero, P. E. (2010). Energy cost and metabolic power in elite soccer: A new match analysis approach. Medicine & Science in Sports & Exercise, 42(1), 170–178. https://doi.org/10.1249/MSS.0b013e3181ae5cfd
Polglaze, T., & Hoppe, M. W. (2019). Metabolic power: A step in the right direction for team sports. International Journal of Sports Physiology and Performance, 14(3), 407–411. https://doi.org/10.1123/ijspp.2018-0661
Pueo, B., Tortosa‐Martínez, J., Chirosa‐Rios, L. J., & Manchado, C. (2021). Throwing performance by playing positions of male handball players during the European Championship 2020. Scandinavian Journal of Medicine & Science in Sports, sms.14100. https://doi.org/10.1111/sms.14100
Reche-Soto, P., Cardona-Nieto, D., Diaz-Suarez, A., Bastida-Castillo, A., Gomez-Carmona, C., Garcia-Rubio, J., & Pino-Ortega, J. (2019). Player Load and Metabolic Power Dynamics as Load Quantifiers in Soccer. Journal of Human Kinetics, 69(1), 259–269. https://doi.org/10.2478/hukin-2018-0072
Rein, R., & Memmert, D. (2016). Big data and tactical analysis in elite soccer: Future challenges and opportunities for sports science. SpringerPlus, 5(1), 1410. https://doi.org/10.1186/s40064-016-3108-2
Scott, M. T. U., Scott, T. J., & Kelly, V. G. (2016). The validity and reliability of global positioning systems in team sport: A brief review. Journal of Strength and Conditioning Research, 30(5), 1470–1490. https://doi.org/10.1519/JSC.0000000000001221
Vallat, R. (2018). Pingouin: Statistics in Python. Journal of Open Source Software, 3(31), 1026. https://doi.org/10.21105/joss.01026
Winter, D. A. (2009). Biomechanics and motor control of human movement (4th ed). Wiley.
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