Antequera, D. R., Garrido, D., Echegoyen, I., López del Campo, R., Resta Serra, R., & Buldú, J. M. (2020). Asymmetries in Football: The Pass Goal Paradox. Symmetry, 12(6), 1052.
Araya, J. A., & Larkin, P. (2013). Key performance variables between the top 10 and bottom 10 teams in the English Premier League 2012/13 season. Human Movement, Health and Coach Education (HMHCE), 2, 17-29.
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.
Buraimo, B., Paramio, J. L., & Campos, C. (2010). The impact of televised football on stadium attendances in English and Spanish league football. Soccer & Society, 11(4), 461-474.
Buldú, J. M., Busquets, J., Martínez, J. H., Herrera-Diestra, J. L., Echegoyen, I., Galeano, J., & Luque, J. (2018). Using network science to analyse football passing networks: Dynamics, space, time, and the multilayer nature of the game. Frontiers in psychology, 9, 1900.
Carmichael, F., Thomas, D., & Ward, R. (2000). Team performance: the case of English premiership football. Managerial and decision Economics, 21(1), 31-45.
Castellano, J., & Echeazarra, I. (2019). Network-based centrality measures and physical demands in football regarding player position: Is there a connection? A preliminary study. Journal of Sports Sciences, 37(23), 2631-2638.
Clemente, F. M., Martins, F. M., & Mendes, R. (2014). Applying Networks and graph theory to match analysis: identifying the general properties of a graph. In VIII Congreso Internacional de la Asociación Española de Ciencias del Deporte (Vol. 2, pp. 587-590).
Clemente, F. M., Martins, F. M. L., Couceiro, M. S., Mendes, R. S., & Figueiredo, A. J. (2014). A network approach to characterize the teammates interactions on football: A single match analysis. Cuadernos de Psicología del Deporte, 14(3), 141-148.
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.
Destefanis, S., Addesa, F., & Rossi, G. (2022). The impact of COVID-19 on home advantage: a conditional order-m analysis of football clubs’ efficiency in the top-5 European leagues. Applied Economics, 54(58), 6639-6655.
Gama, J., Dias, G., Couceiro, M., Passos, P., Davids, K., & Ribeiro, J. (2016). An ecological dynamics rationale to explain home advantage in professional football. International Journal of Modern Physics C, 27(09), 1650102.
Grund, T. U. (2016). The relational value of network experience in teams: Evidence from the English Premier League. American Behavioral Scientist, 60(10), 1260-1280.
Santana, H. A., Bettega, O. B., & Dellagrana, R. (2021). An analysis of Bundesliga matches before and after social distancing by COVID-19. Science and Medicine in Football, 5(sup1), 17-21.
Jones, P. D., James, N., & Mellalieu, S. D. (2004). Possession as a performance indicator in soccer. International Journal of Performance Analysis in Sport, 4(1), 98-102.
Kubayi, A., & Larkin, P. (2020). Technical performance of soccer teams according to match outcome at the 2019 FIFA Women’s World Cup. International Journal of Performance Analysis in Sport, 20(5), 908-916.
Lago-Ballesteros, J., & Lago-Peñas, C. (2010). Performance in team sports: Identifying the keys to success in soccer. Journal of Human kinetics, 25(2010), 85-91.
Lago-Peñas, C., & Lago-Ballesteros, J. (2011). Game location and team quality effects on performance profiles in professional soccer. Journal of sports science & medicine, 10(3), 465.
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.
Legaz-Arrese, A., Moliner-Urdiales, D., & Munguía-Izquierdo, D. (2013). Home advantage and sports performance: evidence, causes and psychological implications. Universitas Psychologica, 12(3), 933-943.
Maimone, V. M., & Yasseri, T. (2021). Football is becoming more predictable; network analysis of 88 thousand matches in 11 major leagues. Royal Society Open Science, 8(12), 210617.
Mangiafico, S.S. 2016. Summary and Analysis of Extension Program Evaluation in R, version 1.20.05,revised2023.rcompanion.org/handbook/.(Pdfversion:rcompanion.org/docume nts/RHandbookProgramEvaluation.pdf.)
Oberstone, J. (2009). Differentiating the top English premier league football clubs from the rest of the pack: Identifying the keys to success. Journal of Quantitative Analysis in Sports, 5(3).
Passos, P., Davids, K., Araújo, D., Paz, N., Minguéns, J., & Mendes, J. (2011). Networks as a novel tool for studying team ball sports as complex social systems. Journal of Science and Medicine in Sport, 14(2), 170-176.
Pollard, R., & Pollard, G. (2005). Venteja de ser el equipo local en fútbol: una reseña de su existencia y causas. Rev Int Fútbol Ciencia, 3(1), 31-44.
Ponzo, M., & Scoppa, V. (2018). Does the home advantage depend on crowd support? Evidence from same-stadium derbies. Journal of Sports Economics, 19(4), 562-582.
Pina, T. J., Paulo, A., & Araújo, D. (2017). Network characteristics of successful performance in association football. A study on the UEFA champions league. Frontiers in Psychology, 8, 266057.
Ribeiro, J., Silva, P., Duarte, R., Davids, K., & Garganta, J. (2017). Team sports performance analysed through the lens of social network theory: implications for research and practice. Sports medicine, 47, 1689-1696.
Sarmento, H., Clemente, F. M., Araújo, D., Davids, K., McRobert, A., & Figueiredo, A. (2018). What performance analysts need to know about research trends in association football (2012 2016): A systematic review. Sports medicine, 48, 799-836.
Zeng, Y., & Zhang, H. (2022). Analysis of influencing factors of passes in the chinese super league. BMC Sports Science, Medicine and Rehabilitation, 14(1), 1-10.