Cite

Angelini, G., & Angelis, L. de (2019). Efficiency of online football betting markets. International Journal of Forecasting, 35(2), 712-721. https://doi.org/10.1016/j.ijforecast.2018.07.008 Search in Google Scholar

Anzer, G., & Bauer, P. (2021). A goal scoring probability model for shots based on synchronized positional and event data in football (soccer). Frontiers in Sports and Active Living, 53. Search in Google Scholar

Ben-Naim, E., Vazquez, F., & Redner, S. (2006). Parity and predictability of competitions. Journal of Quantitative Analysis in Sports, 2(4). Search in Google Scholar

Blomqvist, M., Luhtanen, P., & Laakso, L. (2000). Expert-Novice Differences in Game Performance and Game Understanding of Youth Badminton Players. European Journal of Physical Education, 5(2), 208-219. https://doi.org/10.1080/1740898000050207 Search in Google Scholar

Bradley, P., O’Donoghue, P., Wooster, B., & Tordoff, P. (2007). The reliability of ProZone MatchViewer: a video-based technical performance analysis system. International Journal of Performance Analysis in Sport, 7(3), 117-129. https://doi.org/10.1080/24748668.2007.11868415 Search in Google Scholar

Brito de Souza, D., López-Del Campo, R., Blanco-Pita, H., Resta, R., & Del Coso, J. (2019). An Extensive Comparative Analysis of Successful and Unsuccessful Football Teams in LaLiga. Frontiers in Psychology, 10, 2566. https://doi.org/10.3389/fpsyg.2019.02566 Search in Google Scholar

Brooks, J., Kerr, M., & Guttag, J. (2016). Developing a data-driven player ranking in soccer using predictive model weights. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining (pp. 49-55). Search in Google Scholar

Bush, M., Barnes, C., Archer, D. T., Hogg, B., & Bradley, P. S. (2015). Evolution of match performance parameters for various playing positions in the English Premier League. Human movement science, 39, 1-11. Search in Google Scholar

Castellano, J., Alvarez-Pastor, D., & Bradley, P. S. (2014). Evaluation of research using computerised tracking systems (Amisco and Prozone) to analyse physical performance in elite soccer: A systematic review. Sports Medicine (Auckland, N.Z.), 44(5), 701-712. https://doi.org/10.1007/s40279-014-0144-3. Search in Google Scholar

Castellano, J., Casamichana, D., & Lago, C. (2012). The Use of Match Statistics that Discriminate Between Successful and Unsuccessful Soccer Teams. Journal of Human Kinetics, 31, 139-147. https://doi.org/10.2478/v10078-012-0015-7 Search in Google Scholar

Chu, W. T., & Situmeang, S. (2017). Badminton video analysis based on spatiotemporal and stroke features. In Proceedings of the 2017 ACM on international conference on multimedia retrieval (pp. 448-451). Search in Google Scholar

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155-159. https://doi.org/10.1037/0033-2909.112.L155 Search in Google Scholar

Decroos, T., Bransen, L., Van Haaren, J., & Davis, J. (2019). Actions speak louder than goals: Valuing player actions in soccer. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining (pp. 1851-1861). Search in Google Scholar

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. https://doi.org/10.1080/24748668.2011.11868531 Search in Google Scholar

Dvorak, J., Junge, A., Graf-Baumann, T., & Peterson, L. (2004). Football is the most popular sport worldwide. The American Journal of Sports Medicine, 32(1 Suppl), 3S-4S. https://doi.org/10.1177/0363546503262283 Search in Google Scholar

Evangelos, T., Alexandros, K., & Nikolaos, A. (2005). Analysis of fast breaks in basketball. International Journal of Performance Analysis in Sport, 5(2), 17-22. https://doi.org/10.1080/24748668.2005.11868324 Search in Google Scholar

Fonseca, S., Milho, J., Travassos, B., & Araujo, D. (2012). Spatial dynamics of team sports exposed by Voronoi diagrams. Human Movement Science, 31(6), 1652-1659. Search in Google Scholar

Forrest, D., Goddard, J., & Simmons, R. (2005). Odds-setters as forecasters: The case of English football. International Journal of Forecasting, 21(3), 551-564. https://doi.org/10.1016/j.ijforecast.2005.03.003 Search in Google Scholar

Goes, F. R., Meerhoff, L. A., Bueno, M. J. O., Rodrigues, D. M., Moura, F. A., Brink, M. S., Elferink-Gemser, M. T., Knobbe, A. J., Cunha, S. A., Torres, R. S., & Lemmink, K. A. P. M [K. A. P. M.] (2021). Unlocking the potential of big data to support tactical performance analysis in professional soccer: A systematic review. European Journal of Sport Science, 21(4), 481-496. https://doi.org/10.1080/17461391.2020.1747552 Search in Google Scholar

Grunz, A., Memmert, D., & Perl, J. (2012). Tactical pattern recognition in soccer games by means of special self-organizing maps. Human Movement Science, 31(2), 334-343. https://doi.org/10.1016Zj.humov.2011.02.008 Search in Google Scholar

Gudmundsson, J., & Horton, M. (2017). Spatio-Temporal Analysis of Team Sports. ACM Computing Surveys, 50(2), 1-34. https://doi.org/10.1145/3054132 Search in Google Scholar

Herold, M., Kempe, M., Bauer, P., & Meyer, T. (2021). Attacking Key Performance Indicators in Soccer: Current Practice and Perceptions from the Elite to Youth Academy Level. Journal of Sports Science & Medicine, 20(1), 158-169. https://doi.org/10.52082/jssm.2021.158 Search in Google Scholar

Hughes, M. D., Cooper, S. M., & Nevill, A. M. (2002). Analysis procedures for nonparametric data in performance analysis of sport. International Journal of Performance Analysis in Sport, 2(1), 6-20. Search in Google Scholar

Hughes, M., & Franks, I. M. (2004). Notational analysis of sport: Systems for better coaching and performance in sport. Routledge. Search in Google Scholar

Hughes, M., Caudrelier, T., James, N., Donnelly, I., Kirkbride, A., & Duschesne, C. (2012). Moneyball and soccer - an analysis of the key performance indicators of elite male soccer players by position. Journal of Human Sport and Exercise, 7(2), 402-412. https://doi.org/10.4100/jhse.2012.72.06 Search in Google Scholar

Hughes, M. D., & Bartlett, R. M. (2002). The use of performance indicators in performance analysis. Journal of Sports Sciences, 20(10), 739-754. https://doi.org/10.1080/026404102320675602 Search in Google Scholar

Hvattum, L. M., & Arntzen, H. (2010). Using ELO ratings for match result prediction in association football. International Journal of Forecasting, 26(3), 460-470. https://doi.org/10.1016/j.ijforecast.2009.10.002 Search in Google Scholar

Jamil, M., Phatak, A., Mehta, S., Beato, M., Memmert, D., & Connor, M. (2021). Using multiple machine learning algorithms to classify elite and sub-elite goalkeepers in professional men’s football. Scientific Reports, 11(1), 22703. https://doi.org/10.1038/s41598-021-01187-5 Search in Google Scholar

Kim, S. (2004). Voronoi Analysis of a Soccer Game. Nonlinear Analysis: Modelling and Control, 9(3), 233-240. https://doi.org/10.15388/NA.2004.9.3.15154 Search in Google Scholar

Lago, C. (2009). The influence of match location, quality of opposition, and match status on possession strategies in professional association football. Journal of Sports Sciences, 27(13), 1463-1469. https://doi.org/10.1080/02640410903131681 Search in Google Scholar

Lago-Peñas, C., & Gomez-Lopez, M. (2014). How important is it to score a goal? The influence of the scoreline on match performance in elite soccer. Perceptual and motor skills, 119(3), 774-784. Search in Google Scholar

Lago-Peñas, C., & Dellal, A. (2010). Ball possession strategies in elite soccer according to the evolution of the match-score: the influence of situational variables. Journal of Human Kinetics, 25, 93-100. Search in Google Scholar

Lago-Peñas, C., Lago-Ballesteros, J., & Rey, E. (2011). Differences in performance indicators between winning and losing teams in the UEFA Champions League. Journal of Human Kinetics, 27(2011), 135-146. https://doi.org/10.2478/v10078-011-0011-3 Search in Google Scholar

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. https://doi.org/10.1080/24748668.2007.11868388 Search in Google Scholar

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 Search in Google Scholar

Leite, W., & Barreira, D. (2014). Are the teams sports soccer, futsal and beach soccer similar. International Journal of Sports Science, 4(6A), 75-84. Search in Google Scholar

Liu, H., Gómez, 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, 22(12), 1205-1213. https://doi.org/10.1080/02640414.2015.1022578 Search in Google Scholar

Liu, H., Gómez, M.-A., Gonçalves, B., & Sampaio, J. (2016). Technical performance and match-to-match variation in elite football teams. Journal of Sports Sciences, 34(6), 509-518. https://doi.org/10.1080/02640414.2015.1117121 Search in Google Scholar

Low, B., Coutinho, D., Gonçalves, B., Rein, R., Memmert, D., & Sampaio, J. (2019). A systematic review of collective tactical behaviours in football using positional data. Sports Medicine,50, 343-385. Search in Google Scholar

Low, B., Rein, R., Raabe, D., Schwab, S., & Memmert, D. (2021a). The porous high-press? An experimental approach investigating tactical behaviours from two pressing strategies in football. Journal of Sports Sciences, 39(19), 2199-2210. Search in Google Scholar

Low, B., Schwab, S., Rein, R., & Memmert, D. (2021b). Defending in 4-4-2 or 5-3-2 formation? Small differences in footballers’ collective tactical behaviours. Journal of Sports Sciences, 40(3), 351-363. Search in Google Scholar

Lüdin, D., Donath, L., Cobley, S., & Romann, M. (2021). Effect of bio-banding on physiological and technical-tactical key performance indicators in youth elite soccer. European Journal of Sport Science, 1-9. https://doi.org/10.1080/17461391.2021.1974100 Search in Google Scholar

Lutz, J., Memmert, D., Raabe, D., Dornberger, R., & Donath, L. (2019). Wearables for Integrative Performance and Tactic Analyses: Opportunities, Challenges, and Future Directions. International Journal of Environmental Research and Public Health, 17(1). https://doi.org/10.3390/ijerph17010059 Search in Google Scholar

Mackenzie, R., & Cushion, C. (2013). Performance analysis in football: A critical review and implications for future research. Journal of Sports Sciences, 31(6), 63W676. https://doi.org/10.1080/02640414.2012.746720 Search in Google Scholar

Memmert, D. (Ed.) (2021). Match Analysis. Abingdon: Routledge. Search in Google Scholar

Memmert, Lemmink, K. A. P. M, & Sampaio, J. (2017). Current Approaches to Tactical Performance Analyses in Soccer Using Position Data. Sports Medicine (Auckland, N.Z.), 47(1), 1-10. https://doi.org/10.1007/s40279-016-0562-5 Search in Google Scholar

Memmert, D., Raabe, D., Schwab, S., & Rein, R. (2019). A tactical comparison of the 4-2-3-1 and 3-5-2 formation in soccer: A theory-oriented, experimental approach based on positional data in an 11 vs. 11 game set-up. PloS One, 14(1), e0210191. https://doi.org/10.1371/journal.pone.0210191 Search in Google Scholar

Memmert, D., & Raabe, D. (2018). Data analytics in football: Positional data collection, modelling and analysis. Routledge. Search in Google Scholar

Memmert, D., Klemp, M., Schwab, S. & Low, B. (2023). Individual attention capacity enhances in-field group performances in soccer. International Journal of Sport and Exercise Psychology, 1-18. Search in Google Scholar

Nakagawa, S., & Cuthill, I. C. (2007). Effect size, confidence interval, and statistical significance: A practical guide for biologists. Biological Reviews, 82(4), 591-605. doi: 10.1111/j .1469-185X.2007.00027.x Search in Google Scholar

Nevill, A., Atkinson, G., & Hughes, M. (2008). Twenty-five years of sport performance research in the Journal of Sports Sciences. Journal of Sports Sciences, 26(4), 413–426. https://doi.org/10.1080/02640410701714589 Search in Google Scholar

Perl, J., Grunz, A., & Memmert, D. (2013). Tactics analysis in soccer^an advanced approach. International Journal of Computer Science in Sport, 12(1), 33-44. Search in Google Scholar

Pettersen, S. A., Johansen, H. D., Baptista, I. A. M., Halvorsen, P., & Johansen, D. (2018). Quantified Soccer Using Positional Data: A Case Study. Frontiers in Physiology, 9, 866. https://doi.org/10.3389/fphys.2018.00866 Search in Google Scholar

Phatak, A. A., Rein, R., & Memmert, D. (2021). The dirty league: English premier league provides higher incentives for fouling as compared to other European soccer leagues. Journal of Human Kinetics, 80(1), 263-276. Search in Google Scholar

Phatak, A. A., Mehta, S., Wieland, F. G., Jamil, M., Connor, M., Bassek, M., & Memmert, D. (2022). Context is key: normalization as a novel approach to sport specific preprocessing of KPI’s for match analysis in soccer. Scientific Reports, 12(1), 1117. Search in Google Scholar

Rein, R., & Memmert, D. (2016). Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science. SpringerPlus, 5(1), 1-13.. DOI 10.1186/s40064-016-3108-2 Search in Google Scholar

Rein, R., Raabe, D., & Memmert, D. (2017). “Which pass is better?” Novel approaches to assess passing effectiveness in elite soccer. Human Movement Science, 55, 172-181. https://doi.org/10.1016/_j.humov.2017.07.010 Search in Google Scholar

Sarlis, V., & Tjortjis, C. (2020). Sports analytics — Evaluation of basketball players and team performance. Information Systems, 93, 101562. https://doi.org/10.1016/j.is.2020.101562 Search in Google Scholar

Sarmento, H., Marcelino, R., Anguera, M. T., CampaniÇo, J., Matos, N., & LeitÃo, J. C. (2014). Match analysis in football: A systematic review. Journal of Sports Sciences, 32(20), 1831-1843. https://doi.org/10.1080/02640414.2014.898852 Search in Google Scholar

Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological science, 22(11), 1359-1366. Search in Google Scholar

Strumbelj, E., & Sikonja, M. R. (2010). Online bookmakers’ odds as forecasts: The ease of European soccer leagues. International Journal of Forecasting, 26(3), 482-488. https://doi.org/10.1016/j.ij forecast.2009.10.005 Search in Google Scholar

Taki, T., & Hasegawa, J. (2000). Visualization of dominant region in team games and its application to teamwork analysis. In Proceedings Computer Graphics International 2000 (pp. 227-235). IEEE Comput. Soc. https://doi.org/10.1109/CGI.2000.852338 Search in Google Scholar

Tavares, F., & Gomes, N. (2003). The offensive process in basketball - a study in high performance junior teams. International Journal of Performance Analysis in Sport, 3(1), 34-39. https://doi.org/10.1080/24748668.2003.11868272 Search in Google Scholar

Tenga, A., Holme, I., Ronglan, L. T., & Bahr, R. (2010a). Effect of playing tactics on achieving score-box possessions in a random series of team possessions from Norwegian professional soccer matches. Journal of Sports Sciences, 28(3), 245-255. https://doi.org/10.1080/02640410903502766 Search in Google Scholar

Tenga, A., Holme, I., Ronglan, L. T., & Bahr, R. (2010b). Effect of playing tactics on goal scoring in Norwegian professional soccer. Journal of Sports Sciences, 28(3), 237-244. https://doi.org/10.1080/02640410903502774 Search in Google Scholar

Weimar, D., & Wicker, P. (2017). Moneyball Revisited. Journal of Sports Economics, 18(2), 140-161. https://doi.org/10.1177/1527002514561789 Search in Google Scholar

Wunderlich, F., Berge, F., Memmert, D., & Rein, R. (2020). Almost a lottery: the influence of team strength on success in penalty shootouts. International Journal of Performance Analysis in Sport, 20(5), 857-869. https://doi.org/10.1080/24748668.2020.1799171 Search in Google Scholar

Wunderlich, F., & Memmert, D. (2018). The Betting Odds Rating System: Using soccer forecasts to forecast soccer. PloS One, 13(6), e0198668. https://doi.org/10.1371/journal.pone.0198668 Search in Google Scholar

Wunderlich, F., Seck, A., & Memmert, D. (2021). The influence of randomness on goals in football decreases over time. An empirical analysis of randomness involved in goal scoring in the English Premier League. Journal of Sports Sciences, 1-16. https://doi.org/10.1080/02640414.2021.1930685 Search in Google Scholar

Yiannakos, A., & Armatas, V. (2006). Evaluation of the goal scoring patterns in European Championship in Portugal 2004. International Journal of Performance Analysis in Sport, 6(1), 178-188. https://doi.org/10.1080/24748668.2006.11868366 Search in Google Scholar

eISSN:
1684-4769
Idioma:
Inglés
Calendario de la edición:
2 veces al año
Temas de la revista:
Computer Sciences, Databases and Data Mining, other, Sports and Recreation, Physical Education