Analysis of the winning probability and the scoring actions in the American professional soccer championship. [Análisis de la probabilidad de ganar y de las acciones que conducen al gol en la liga americana de fútbol profesional].

Albert Altarriba-Bartés, M.Luz Calle, Antonio Susín, Bruno Gonçalves, Marc Vives, Jaime Sampaio, Javier Peña

Resumen


Abstract

This study aimed to assess the effect of the scoring moment on the conditional probability of winning or losing a professional soccer match, as well as identified the most influential variables contributing to victory in Major League Soccer (MLS), the men’s professional league in the United States. Data from 680 matches played in the 2015 and 2016 regular seasons were analysed, by dividing the matches into fifteen-minute periods. Additionally, the influence of playing home or away on the match outcome and the type of technical-tactical actions that lead to a goal was also analysed. The temporal analysis revealed that scoring first increased the probability of winning the match significantly and showed dependency on the time in which the goal was scored. The two principal components of the principal component analysis (PCA) were counterattacks (PC1) and crosses (PC2). These were the most critical variables during open play to determine how MLS teams scored goals. Nevertheless, scoring first, playing as a home team always gave a better chance to win the game than scoring first and playing away (0.72 vs. 0.32 probability). As the match approached the end, winning or losing was even more determinant and less reversible (0.85 vs. 0.72 for the home and away team respectively when they were ahead on the score in the minute 75 or later). These findings can contribute to a better understanding of the performance indicators in professional soccer, helping coaches to determine the right strategies and improving the tactical patterns to succeed in competition.

Resumen

Este estudio tiene como objetivo evaluar el efecto del momento de anotar un gol en la probabilidad condicional de ganar o perder un partido de fútbol profesional, así como identificar las variables más influyentes que contribuyen a la victoria en la Major League Soccer (MLS), la liga masculina profesional de los Estados Unidos. Se analizaron los datos de los 680 partidos jugados durante las temporadas regulares de 2015 y 2016, dividiendo los partidos en períodos de quince minutos. Además, también se analizó la influencia de jugar en casa o fuera en el resultado final del partido y el tipo de acciones técnico-tácticas que conducen a lograr marcar un gol. El análisis temporal reveló que conseguir marcar un gol antes que el rival aumentaba significativamente la probabilidad de ganar el partido y mostró dependencia del período de tiempo en el que se anotó éste. Los dos componentes principales del análisis de componentes principales (PCA) fueron los contraataques (PC1) y los centros (PC2). Estas fueron las variables más determinantes durante el juego abierto para determinar cómo anotan los goles los equipos de la MLS. Sin embargo, anotar primero, jugando como local siempre obtuvo mayores posibilidades de ganar el partido que anotar primero jugando como visitante (probabilidad 0.72 vs 0.32). A medida que el partido se acercaba al final, ganar o perder era aún más determinante y menos reversible (0,85 frente a 0,72 para el equipo local y visitante respectivamente, cuando se tenía ventaja en el marcador en el minuto 75 o posterior). Estos hallazgos pueden contribuir a una mejor comprensión de los indicadores de rendimiento en el fútbol profesional, ayudando a los entrenadores a determinar las estrategias correctas y mejorando los patrones tácticos para tener éxito en la competición.

https://doi.org/10.5232/ricyde2020.05906

References/referencias

Alberti, G.; Iaia, F. M.; Arcelli, E.; Cavaggioni, L., & Rampinini, E. (2013). Goal scoring patterns in major European soccer leagues. Sport Sciences for Health, 9(3), 151–153.

Armatas, V.; Yiannakos, A., & Sileloglou, P. (2007). Relationship between time and goal scoring in soccer games: Analysis of three World Cups. International Journal of Performance Analysis in Sport (Vol. 7).

Armatas, V.; Yiannakos, A.; Papadopoulou, S., & Skoufas, D. (2009). Evaluation of goals scored in top ranking soccer matches: Greek “Superleague” 2006-07. Serbian Journal of Sports Sciences (Vol. 3).

Armatas, V., & Yiannakos, A. (2010). Analysis and evaluation of goals scored in 2006 World Cup. Journal of Sport and Health Research (Vol. 2).

Bradley, P.S.; Lago-Peñas, C.; Rey, E., & Sampaio, J. (2014). The influence of situational variables on ball possession in the English Premier League. Journal of Sports Sciences, 32(20), 1867–1873.
https://doi.org/10.1080/02640414.2014.887850

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, 137–147.
https://doi.org/10.2478/v10078-012-0015-7

Collet, C. (2012). The possession game? A comparative analysis of ball retention and team success in European and international football, 2007–2010. Journal of Sports Sciences, 31(2), 123–136.
https://doi.org/10.1080/02640414.2012.727455

Federolf, P.; Reid, R.; Gilgien, M.; Haugen, P., & Smith, G. (2012) The application of principal component analysis to quantify technique in sports. Scandinavian Journal of Medicine and Science in Sports, 24(3), 491-499.
https://doi.org/10.1111/j.1600

Firdaus, M.; Ali, M.; Katis, A.; Patsika, G., & Kellis, E. (2015). Goal scoring charateristics in soccer: are they technique and time dependent? Asian Pacific Journal Od Advanced Business and Social Studies, 1(1), 186–194.

Gómez, M.Á., & Pollard, R. (2014). Calculating the home advantage in soccer leagues. Journal of Human Kinetics40, 5–6.
https://doi.org/10.2478/hukin-2014-0001

Harriss, D.J., & Atkinson, G. (2015). Ethical standards in sport and exercise science research: 2016 update. International Journal of Sports Medicine. 36, 1121–4.

Hastie, H.; Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York, NY: Springer-Verlag.

Jackson, J. E. (1991). A user’s guide to principal components. New York, NY: Wiley.

Jolliffe I .T. (2002). Principal component analysis, 2nd ed. New York, NY: Springer-Verlag.

Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: a review and recent developments. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 374(2065), 20150202.
https://doi.org/10.1098/rsta.2015.0202

Johnson, S.C. (1967). Hierarchical clustering schemes. Psychometrika, 32, 241–254

Jones, M., & Harwood, C. (2008). Psychological Momentum within Competitive Soccer: Players’ Perspectives. Journal of Applied Sport Psychology, 20, 57–72.
https://doi.org/10.1080/10413200701784841

Lago-Peñas, C.; Lago-Ballesteros, J.; Dellal, A., & Gomez, M. (2010). Game-related statistics that discriminated winning, drawing and losing teams from the Spanish soccer league. Journal of Sports Science and Medicine, 9(2), 288–293.

Leite, W.S.S. (2013). Euro 2012: Analysis and Evaluation of Goals Scored. International Journal of Sports Science, 3(4), 102–106.
https://doi.org/10.5923/j.sports.20130304.02

Li, Y.; Chiusano, S., & D’Elia, V. (2010) Modeling Athlete Performance Using Clustering Techniques. Proceedings of the Third International Symposium on Electronic Commerce and Security Workshops (ISECS ’10) Guangzhou, P. R. China, 29-31, July 2010, pp. 169-171

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

Mitrotasios, M., & Armatas, V. (2014). Analysis of goal scoring patterns in the 2012 European Football Championship. The Sport Journal, (50), 1–9.

Moura, F. A.; Martins, L.E.B., & Cunha, S. A. (2014). Analysis of football game-related statistics using multivariate techniques. Journal of Sports Sciences, 32(20), 1881–1887.
https://doi.org/10.1080/02640414.2013.853130

Nevill, A.; Balmer, N., & Mark Williams, A. (2002). The influence of crowd noise and experience upon refereeing decisions in football. Psychology of Sport and Exercise, 3(4), 261–272.
https://doi.org/10.1016/S1469-0292(01)00033-4

Nevill, A. M.; Newell, S.M., & Gale, S. (1996). Factors associated with home advantage in English and Scottish soccer matches. Journal of Sports Sciences, 14(2), 181–186.
https://doi.org/10.1080/02640419608727700

Nevo, D., & Ritov, Y. (2013). Around the goal: Examining the effect of the first goal on the second goal in soccer using survival analysis methods. Journal of Quantitative Analysis in Sports, 9(2), 165–177.
https://doi.org/10.1515/jqas-2012-0004

Njororai Simiyu, W. (2005). Analysis of the goals scored at the 17th World Cup Soccer Tournament in South Korea-Japan 2002. African Journal for Physical, Health Education, Recreation and Dance, 10.
https://doi.org/10.4314/ajpherd.v10i4.24678

Njororai W. (2007). Scoring goals. What the coach should know about the timing. Soccer Journal, 11, 34-36.

O’Donoghue, P. (2010). Research methods for sports performance analysis. London: Routledge.

Prabu, M.; Sudhaghar, J.; Viswajith, R.; Venkata Narsimha, I., & Srikaanth, A.K. (2019). Efficient Data Mining Methodology for Sports. International Journal of Innovative Technology and Exploring Engineering, 8(6S), 2278-3075.

Rampinini, E.; Impellizzeri, F. M.; Castagna, C.,;Coutts, A. J., & Wisløff, U. (2009). Technical performance during soccer matches of the Italian Serie A league: Effect of fatigue and competitive level. Journal of Science and Medicine in Sport, 12(1), 227–233.
https://doi.org/10.1016/j.jsams.2007.10.002

Saavedra García, M.; Aguilar, Ó.G.; Marques, P.S.; Tobío, G.T., & Romero, J. J. F. (2013). Calculating Home Advantage in the First Decade of the 21th Century UEFA Soccer Leagues. Journal of Human Kinetics, 38(38), 141–150.
https://doi.org/10.2478/hukin-2013-0054

Sánchez, P. A.; García-Calvo, T.; Leo, F. M.; Pollard, R., & Gómez, M. A. (2009). An analysis of home advantage in the top two Spanish professional football leagues. Perceptual and Motor Skills, 108(3), 789–797.
https://doi.org/10.2466/PMS.108.3.789-797

Shafizadeh, M.; Taylor, M., & Peñas, C. L. (2013). Performance consistency of international soccer Teams in Euro 2012: A time series analysis. Journal of Human Kinetics, 38(1), 213–226.
https://doi.org/10.2478/hukin-2013-0061

Wilkinson, L., & Friendly, M. (2009) The History of the Cluster Heat Map. The American Statistician, 63(2), 179-184.
https://doi.org/10.1198/tas.2009.0033

Williams, A.M. (2013). Science and soccer: Developing elite performers (1st edition). Abingdon, OX: Routledge.

Wright, C.; Polman, R.; Jones, B., & Sargeson, L. (2011). Factors Associated with Goals and Goal Scoring Opportunities in Professional Soccer. International Journal of Performance Analysis in Sport, 11, 438–449.
https://doi.org/10.1080/24748668.2011.11868563

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, 178–188.
https://doi.org/10.1080/24748668.2006.1186836.


Palabras clave/key words


goals; principal component analysis; coaching; goles; análisis de componentes principales; entrenamiento; deportes de equipo., team sports.

Texto completo/Full Text:

PDF (English) PDF




------------------------ 0 -------------------------

RICYDE. Revista Internacional de Ciencias del Deporte
logopublisher_168


Publisher: Ramón Cantó Alcaraz
ISSN:1885-3137 - Periodicidad Trimestral / Quarterly
Creative Commons License