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06.02.2024 | Discussion

Beyond key performance indicators

Theoretical-methodological discussion of performance analysis (sports analytics) research

verfasst von: Elia Morgulev, Felix Lebed

Erschienen in: German Journal of Exercise and Sport Research

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Abstract

Over the past few decades, performance analysis in team invasion sports has become a recognized scientific field. In this paper, we aim to delve into the theoretical and practical aspects of this discipline. To begin, we briefly review the current state of sports analytics, emphasizing its significant role within the professional sports industry. Then, focusing on performance analysis research, we explore three theoretical-methodological challenges at the intersection of theory and practice: (1) measuring what can be easily counted rather than what counts; (2) lack of theorization; and (3) in team invasion sports, knowledge gained about individual and group behavior alters the behavior itself. To conclude, we roughly divide performance analysis into three types of research: (1) fundamental theory-driven performance analysis; (2) practice-oriented applied science; and (3) atheoretical over-simplistic research, which also lacks in practical value. With ever-increasing amounts of data available for analysis and the growing sophistication of statistical tools, the current discussion and the proposed demarcation of performance analysis literature are important for furthering meaningful and ecologically valid research in sports science.
Literatur
Zurück zum Zitat Alamar, B. (2013). Sports analytics: A guide for coaches, managers, and other decision makers. Columbia University Press.CrossRef Alamar, B. (2013). Sports analytics: A guide for coaches, managers, and other decision makers. Columbia University Press.CrossRef
Zurück zum Zitat Cabarkapa, D., Deane, M. A., Fry, A. C., Jones, G. T., Cabarkapa, D. V., Philipp, N. M., & Yu, D. (2022). Game statistics that discriminate winning and losing at the NBA level of basketball competition. Plos one, 17(8), e273427.CrossRefPubMedPubMedCentral Cabarkapa, D., Deane, M. A., Fry, A. C., Jones, G. T., Cabarkapa, D. V., Philipp, N. M., & Yu, D. (2022). Game statistics that discriminate winning and losing at the NBA level of basketball competition. Plos one, 17(8), e273427.CrossRefPubMedPubMedCentral
Zurück zum Zitat Chang, Y. H., Maheswaran, R., Su, J., Kwok, S., Levy, T., Wexler, A., & Squire, K. (2014). Quantifying shot quality in the NBA. In Proceedings of the 8th Annual. Sloan Sports Analytics Conference: MIT Press. Chang, Y. H., Maheswaran, R., Su, J., Kwok, S., Levy, T., Wexler, A., & Squire, K. (2014). Quantifying shot quality in the NBA. In Proceedings of the 8th Annual. Sloan Sports Analytics Conference: MIT Press.
Zurück zum Zitat Clemente, F. M., Martins, F. M. L., Kalamaras, D., Wong, P. D., & Mendes, R. S. (2015). General network analysis of national soccer teams in FIFA World Cup 2014. International Journal of Performance Analysis in Sport, 15(1), 80–96.CrossRef Clemente, F. M., Martins, F. M. L., Kalamaras, D., Wong, P. D., & Mendes, R. S. (2015). General network analysis of national soccer teams in FIFA World Cup 2014. International Journal of Performance Analysis in Sport, 15(1), 80–96.CrossRef
Zurück zum Zitat ‏Davenport, T. H. (2014). Analytics in sports: The new science of winning. International Institute for Analytics, 2, 1–28. ‏Davenport, T. H. (2014). Analytics in sports: The new science of winning. International Institute for Analytics, 2, 1–28.
Zurück zum Zitat Davis, J., Bransen, L., Devos, L., Meert, W., Robberechts, P., Van Haaren, J., & Van Roy, M. (2022). Evaluating sports analytics models: Challenges, approaches, and lessonslearned. In Proceedings of the AI Evaluation beyond Metrics Workshop at IJCAI 2022. EBeM, , 1–11. Vienna, Austria. Davis, J., Bransen, L., Devos, L., Meert, W., Robberechts, P., Van Haaren, J., & Van Roy, M. (2022). Evaluating sports analytics models: Challenges, approaches, and lessonslearned. In Proceedings of the AI Evaluation beyond Metrics Workshop at IJCAI 2022. EBeM, , 1–11. Vienna, Austria.
Zurück zum Zitat Drikos, S., & Vagenas, G. (2011). Multivariate assessment of selected performance indicators in relation to the type and result of a typical set in men’s elite volleyball. International Journal of Performance Analysis in Sport, 11(1), 85–95.CrossRef Drikos, S., & Vagenas, G. (2011). Multivariate assessment of selected performance indicators in relation to the type and result of a typical set in men’s elite volleyball. International Journal of Performance Analysis in Sport, 11(1), 85–95.CrossRef
Zurück zum Zitat Fernandez, J., & Bornn, L. (2018). Wide open spaces: A statistical technique for measuring space creation in professional soccer. In. Sloan Sports Analytics Conference: MIT Press. Fernandez, J., & Bornn, L. (2018). Wide open spaces: A statistical technique for measuring space creation in professional soccer. In. Sloan Sports Analytics Conference: MIT Press.
Zurück zum Zitat Fischer, J., Fischer, D., & Keiner, M. (2022). Perturbation profile of elite football—a cross-sectional analysis of the goals and goal scoring opportunities immediately before and after goal scoring of the 1st German Bundesliga. International Journal of Performance Analysis in Sport, 22(4), 491–504.CrossRef Fischer, J., Fischer, D., & Keiner, M. (2022). Perturbation profile of elite football—a cross-sectional analysis of the goals and goal scoring opportunities immediately before and after goal scoring of the 1st German Bundesliga. International Journal of Performance Analysis in Sport, 22(4), 491–504.CrossRef
Zurück zum Zitat Goes, F. R., Brink, M. S., Elferink-Gemser, M. T., Kempe, M., & Lemmink, K. A. (2021). The tactics of successful attacks in professional association football: large-scale spatiotemporal analysis of dynamic subgroups using position tracking data. Journal of Sports Sciences, 39(5), 523–532.CrossRefPubMed Goes, F. R., Brink, M. S., Elferink-Gemser, M. T., Kempe, M., & Lemmink, K. A. (2021). The tactics of successful attacks in professional association football: large-scale spatiotemporal analysis of dynamic subgroups using position tracking data. Journal of Sports Sciences, 39(5), 523–532.CrossRefPubMed
Zurück zum Zitat Goldsberry, K., & Weiss, E. (2013). The Dwight effect: A new ensemble of interior defense analytics for the NBA. In. Sloan Sports Analytics Conference: MIT Press. Goldsberry, K., & Weiss, E. (2013). The Dwight effect: A new ensemble of interior defense analytics for the NBA. In. Sloan Sports Analytics Conference: MIT Press.
Zurück zum Zitat Grisogono, A.-M. (2006). Co-Adaptation. Proceedings of SPIE—the International Society for Optical Engineering. Article, 6039(603903)., . Grisogono, A.-M. (2006). Co-Adaptation. Proceedings of SPIE—the International Society for Optical Engineering. Article, 6039(603903)., .
Zurück zum Zitat Grund, T. U. (2012). Network structure and team performance: The case of English Premier League soccer teams. Social Networks, 34(4), 682–690.CrossRef Grund, T. U. (2012). Network structure and team performance: The case of English Premier League soccer teams. Social Networks, 34(4), 682–690.CrossRef
Zurück zum Zitat Hughes, M. D., & Bartlett, R. M. (2002). The use of performance indicators in performance analysis. Journal of sports sciences, 20(10), 739–754.CrossRefPubMed Hughes, M. D., & Bartlett, R. M. (2002). The use of performance indicators in performance analysis. Journal of sports sciences, 20(10), 739–754.CrossRefPubMed
Zurück zum Zitat Hughes, M., Dawkins, N., David, R., & Mills, J. (1998). The perturbation effect and goal opportunities in soccer. Journal of sports sciences, 16(1), 20. Hughes, M., Dawkins, N., David, R., & Mills, J. (1998). The perturbation effect and goal opportunities in soccer. Journal of sports sciences, 16(1), 20.
Zurück zum Zitat ‏Kaplan, D. (1964). The conduct of inquiry. Chandler Publishing Company. ‏Kaplan, D. (1964). The conduct of inquiry. Chandler Publishing Company.
Zurück zum Zitat Kovalchik, S. A. (2023). Player Tracking Data in Sports. Annual Review of Statistics and Its. Application, Vol. 10 (pp. 677–697). Kovalchik, S. A. (2023). Player Tracking Data in Sports. Annual Review of Statistics and Its. Application, Vol. 10 (pp. 677–697).
Zurück zum Zitat Kovalchik, S., Ingram, M., Weeratunga, K., & Goncu, C. (2020). Space-time VON CRAMM: Evaluating decision-making in tennis with Variational Generation of Complete Resolution Arcs via Mixture Modeling. arXiv preprint arXiv:2005.12853. Kovalchik, S., Ingram, M., Weeratunga, K., & Goncu, C. (2020). Space-time VON CRAMM: Evaluating decision-making in tennis with Variational Generation of Complete Resolution Arcs via Mixture Modeling. arXiv preprint arXiv:2005.12853.
Zurück zum Zitat Lames, M., & McGarry, T. (2007). On the search for reliable performance indicators in game sports. International Journal of Performance Analysis in Sport, 7(1), 62–79.CrossRef Lames, M., & McGarry, T. (2007). On the search for reliable performance indicators in game sports. International Journal of Performance Analysis in Sport, 7(1), 62–79.CrossRef
Zurück zum Zitat Lebed, F., & Eli, B. M. (2013). Complexity and control in team sports. Dialectics in contesting human systems. Routledge.CrossRef Lebed, F., & Eli, B. M. (2013). Complexity and control in team sports. Dialectics in contesting human systems. Routledge.CrossRef
Zurück zum Zitat ‏Lebed, F. (2017). Complex sport analytics. Routledge.‏ ‏Lebed, F. (2017). Complex sport analytics. Routledge.‏
Zurück zum Zitat ‏Liu, H., Gomez, M. Á., Lago-Peñas, C., & Sampaio, J. (2015). Match statistics related to winning in the group stage of 2014 Brazil FIFA World Cup. Journal of sports sciences, 33(12), 1205–1213. ‏Liu, H., Gomez, M. Á., Lago-Peñas, C., & Sampaio, J. (2015). Match statistics related to winning in the group stage of 2014 Brazil FIFA World Cup. Journal of sports sciences, 33(12), 1205–1213.
Zurück zum Zitat Lord, F., Pyne, D. B., Welvaert, M., & Mara, J. K. (2020). Methods of performance analysis in team invasion sports: A systematic review. Journal of sports sciences, 38(20), 2338–2349.CrossRefPubMed Lord, F., Pyne, D. B., Welvaert, M., & Mara, J. K. (2020). Methods of performance analysis in team invasion sports: A systematic review. Journal of sports sciences, 38(20), 2338–2349.CrossRefPubMed
Zurück zum Zitat Mackenzie, R., & Cushion, C. (2013). Performance analysis in football: A critical review and implications for future research. Journal of sports sciences, 31(6), 639–676.CrossRefPubMed Mackenzie, R., & Cushion, C. (2013). Performance analysis in football: A critical review and implications for future research. Journal of sports sciences, 31(6), 639–676.CrossRefPubMed
Zurück zum Zitat ‏Mandić, R., Jakovljević, S., Erčulj, F., & Štrumbelj, E. (2019). Trends in NBA and Euroleague basketball: Analysis and comparison of statistical data from 2000to 2017. PloS one, 14(10), e0223524. ‏Mandić, R., Jakovljević, S., Erčulj, F., & Štrumbelj, E. (2019). Trends in NBA and Euroleague basketball: Analysis and comparison of statistical data from 2000to 2017. PloS one, 14(10), e0223524.
Zurück zum Zitat Marcelino, R., Sampaio, J., Amichay, G., Gonçalves, B., Couzin, I. D., & Nagy, M. (2020). Collective movement analysis reveals coordination tactics of team players in football matches. Chaos, Solitons & Fractals, 138, 109831.MathSciNetCrossRef Marcelino, R., Sampaio, J., Amichay, G., Gonçalves, B., Couzin, I. D., & Nagy, M. (2020). Collective movement analysis reveals coordination tactics of team players in football matches. Chaos, Solitons & Fractals, 138, 109831.MathSciNetCrossRef
Zurück zum Zitat Martínez, J. H., Garrido, D., Herrera-Diestra, J. L., Busquets, J., Sevilla-Escoboza, R., & Buldú, J. M. (2020). Spatial and temporal entropies in the Spanish football league: A network science perspective. Entropy, 22(2), 172.ADSCrossRefPubMedPubMedCentral Martínez, J. H., Garrido, D., Herrera-Diestra, J. L., Busquets, J., Sevilla-Escoboza, R., & Buldú, J. M. (2020). Spatial and temporal entropies in the Spanish football league: A network science perspective. Entropy, 22(2), 172.ADSCrossRefPubMedPubMedCentral
Zurück zum Zitat ‏Mataruna-Dos-Santos, L. J., Faccia, A., Helú, H. M., & Khan, M. S. (2020). Big Data Analyses and New Technology Applications in Sport Management, an Overview. In Proceedings of the 2020 International Conference on Big Data in Management (pp. 17–22). ‏Mataruna-Dos-Santos, L. J., Faccia, A., Helú, H. M., & Khan, M. S. (2020). Big Data Analyses and New Technology Applications in Sport Management, an Overview. In Proceedings of the 2020 International Conference on Big Data in Management (pp. 17–22).
Zurück zum Zitat McGarry, T., Anderson, D. I., Wallace, S. A., Hughes, M. D., & Franks, I. M. (2002). Sport competition as a dynamical self-organizing system. Journal of sports sciences, 20(10), 771–781.CrossRefPubMed McGarry, T., Anderson, D. I., Wallace, S. A., Hughes, M. D., & Franks, I. M. (2002). Sport competition as a dynamical self-organizing system. Journal of sports sciences, 20(10), 771–781.CrossRefPubMed
Zurück zum Zitat ‏Mehta, S., Furley, P., Raabe, D., & Memmert, D. (2023). Examining how data becomes information for an upcoming opponent in football. International Journal of Sports Science & Coaching, 17479541231187871. ‏Mehta, S., Furley, P., Raabe, D., & Memmert, D. (2023). Examining how data becomes information for an upcoming opponent in football. International Journal of Sports Science & Coaching, 17479541231187871.
Zurück zum Zitat ‏Memmert, D., Lemmink, K. A., & Sampaio, J. (2016). Current approaches to tactical performance analyses in soccer using position data. Sports medicine, 47(1), 1–10. ‏Memmert, D., Lemmink, K. A., & Sampaio, J. (2016). Current approaches to tactical performance analyses in soccer using position data. Sports medicine, 47(1), 1–10.
Zurück zum Zitat Milanović, D., Vuleta, D., & Ohnjec, K. (2018). Performance indicators of winning and defeated female handball teams in matches of the 2012 Olympic Games tournament. Journal of human kinetics, 64(1), 247–253.CrossRefPubMedPubMedCentral Milanović, D., Vuleta, D., & Ohnjec, K. (2018). Performance indicators of winning and defeated female handball teams in matches of the 2012 Olympic Games tournament. Journal of human kinetics, 64(1), 247–253.CrossRefPubMedPubMedCentral
Zurück zum Zitat Moore, E. (2017). Formalism and strategic fouls. Journal of the Philosophy of Sport, 44(1), 95–107.CrossRef Moore, E. (2017). Formalism and strategic fouls. Journal of the Philosophy of Sport, 44(1), 95–107.CrossRef
Zurück zum Zitat Nocera, A., Sbrollini, A., Romagnoli, S., Morettini, M., Gambi, E., & Burattini, L. (2023). Physiological and Biomechanical Monitoring in American Football Players: A Scoping Review. Sensors, 23(7), 3538.ADSCrossRefPubMedPubMedCentral Nocera, A., Sbrollini, A., Romagnoli, S., Morettini, M., Gambi, E., & Burattini, L. (2023). Physiological and Biomechanical Monitoring in American Football Players: A Scoping Review. Sensors, 23(7), 3538.ADSCrossRefPubMedPubMedCentral
Zurück zum Zitat O’Donoghue, P. (2014). An introduction to performance analysis of sport. Routledge.CrossRef O’Donoghue, P. (2014). An introduction to performance analysis of sport. Routledge.CrossRef
Zurück zum Zitat Ortega, A., Frossard, P., Kovačević, J., Moura, J. M., & Vandergheynst, P. (2018). Graph signal processing: Overview, challenges, and applications. Proceedings of the IEEE, 106(5), 808–828.CrossRef Ortega, A., Frossard, P., Kovačević, J., Moura, J. M., & Vandergheynst, P. (2018). Graph signal processing: Overview, challenges, and applications. Proceedings of the IEEE, 106(5), 808–828.CrossRef
Zurück zum Zitat Prokopenko, M., Boschetti, F., & Ryan, A. J. (2009). An information-theoretic primer on complexity, self-organization, and emergence. Complexity, 15(1), 11–28.ADSMathSciNetCrossRef Prokopenko, M., Boschetti, F., & Ryan, A. J. (2009). An information-theoretic primer on complexity, self-organization, and emergence. Complexity, 15(1), 11–28.ADSMathSciNetCrossRef
Zurück zum Zitat Ribeiro, J., Davids, K., Araújo, D., Silva, P., Ramos, J., Lopes, R., & Garganta, J. (2019). The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance. Sports Medicine, 49, 1337–1344.CrossRefPubMed Ribeiro, J., Davids, K., Araújo, D., Silva, P., Ramos, J., Lopes, R., & Garganta, J. (2019). The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance. Sports Medicine, 49, 1337–1344.CrossRefPubMed
Zurück zum Zitat ‏Rolland, G., Vuillemot, R., Bos, W. J., & Rivière, N. (2020). Characterization of space and time-dependence of 3‑point shots in basketball. In MIT Sloan Sports Analytics Conference.‏ ‏Rolland, G., Vuillemot, R., Bos, W. J., & Rivière, N. (2020). Characterization of space and time-dependence of 3‑point shots in basketball. In MIT Sloan Sports Analytics Conference.‏
Zurück zum Zitat Sutton, R. I., & Staw, B. M. (1995). What theory is not. Administrative science quarterly, , 371–384. Sutton, R. I., & Staw, B. M. (1995). What theory is not. Administrative science quarterly, , 371–384.
Zurück zum Zitat Szymanski, S. (2020). Sport analytics: Science or alchemy? Kinesiology Review, 9(1), 57–63.CrossRef Szymanski, S. (2020). Sport analytics: Science or alchemy? Kinesiology Review, 9(1), 57–63.CrossRef
Zurück zum Zitat Torres-Ronda, L., Beanland, E., Whitehead, S., Sweeting, A., & Clubb, J. (2022). Tracking systems in team sports: a narrative review of applications of the data and sport specific analysis. Sports Medicine-Open, 8(1), 1–22.CrossRef Torres-Ronda, L., Beanland, E., Whitehead, S., Sweeting, A., & Clubb, J. (2022). Tracking systems in team sports: a narrative review of applications of the data and sport specific analysis. Sports Medicine-Open, 8(1), 1–22.CrossRef
Zurück zum Zitat Wäsche, H., Dickson, G., Woll, A., & Brandes, U. (2017). Social network analysis in sport research: an emerging paradigm. European Journal for Sport and Society, 14(2), 138–165.CrossRef Wäsche, H., Dickson, G., Woll, A., & Brandes, U. (2017). Social network analysis in sport research: an emerging paradigm. European Journal for Sport and Society, 14(2), 138–165.CrossRef
Zurück zum Zitat Yichen, W., & Yamashita, H. (2021). Lineup optimization model of basketball players based on the prediction of recursive neural networks. International Journal of Economics and Management Engineering, 15(3), 287–293. Yichen, W., & Yamashita, H. (2021). Lineup optimization model of basketball players based on the prediction of recursive neural networks. International Journal of Economics and Management Engineering, 15(3), 287–293.
Zurück zum Zitat Zając, T., Mikołajec, K., Chmura, P., Konefał, M., Krzysztofik, M., & Makar, P. (2023). Long-Term Trends in Shooting Performance in the NBA: An Analysis of Two-and Three-Point Shooting across 40 Consecutive Seasons. International Journal of Environmental Research and Public Health, 20(3), 1924.CrossRefPubMedPubMedCentral Zając, T., Mikołajec, K., Chmura, P., Konefał, M., Krzysztofik, M., & Makar, P. (2023). Long-Term Trends in Shooting Performance in the NBA: An Analysis of Two-and Three-Point Shooting across 40 Consecutive Seasons. International Journal of Environmental Research and Public Health, 20(3), 1924.CrossRefPubMedPubMedCentral
Metadaten
Titel
Beyond key performance indicators
Theoretical-methodological discussion of performance analysis (sports analytics) research
verfasst von
Elia Morgulev
Felix Lebed
Publikationsdatum
06.02.2024
Verlag
Springer Berlin Heidelberg
Erschienen in
German Journal of Exercise and Sport Research
Print ISSN: 2509-3142
Elektronische ISSN: 2509-3150
DOI
https://doi.org/10.1007/s12662-024-00944-8

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