Podium and Influence: A Network Analysis of the Most Important Formula One Drivers
Resumo
This paper presents a network analysis to recognize the most important Formula One drivers, focusing on podium finishes as a metric of influence. We investigated a dataset comprising 855 drivers, 1,079 races, and 25,840 results to explore the relationships and performance dynamics among drivers. The use of centrality measures and community detection in network analysis offers a novel approach to evaluating Formula One drivers, beyond traditional metrics like championship or race wins. In our comprehensive analysis, it was determined that PageRank yielded the most insightful results, effectively capturing the essential contributions and setting a new benchmark for assessing excellence in Formula One racing and other sports.Referências
Budzinski, O., and Feddersen, A. (2019). Measuring Competitive Balance in Formula One Racing. SSRN Electronic Journal. DOI: 10.2139/ssrn.3357687
Cintia, P., Coscia, M., and Pappalardo, L. (2016). The Haka network: Evaluating rugby team performance with dynamic graph analysis. In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 1095-1102). IEEE. DOI: 10.1109/ASONAM.2016.7752377
De Meo, P., Ferrara, E., Fiumara, G., and Provetti, A. (2011). Generalized Louvain method for community detection in large networks. In 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA) (pp. 88-93). IEEE. DOI: 10.1109/ISDA.2011.6121636
Ge, Y., and He, Y. (2022). Research on Importance and Correlation Evaluation of Music Network Nodes Based on Page Rank Algorithm. Journal of Applied Mathematics and Computation, 6(2), 267-272. DOI: 10.26855/jamc.2022.06.012,
Hamilton, M. (2022). Formula 1: The Official History. Welbeck.
Jones, B. (2023). The Formula One Record Book: Grand Prix Results, Team & Driver Stats, All-Time Records. Welbeck. Kindle Edition.
Judde, C., Booth, R., and Brooks, R. (2013). Second Place Is First of the Losers: An Analysis of Competitive Balance in Formula One. Journal of Sports Economics, 14(4), 411-439. DOI: 10.1177/1527002513496009
Kanal, S. (2021, May 29). After Bottas, Hamilton and Verstappen, which other trios have shared an F1 podium most often? Formula 1. [link]. Accessed: 2024_03_22
McHale, G. and Relton, S. D. (2018). Identifying key players in soccer teams using network analysis and pass difficulty. European Journal of Operational Research, 268(1), 339-347. DOI: 10.1016/j.ejor.2018.01.018
Motegi, S. and Masuda, N. (2012). A network-based dynamical ranking system for competitive sports. Scientific Reports, 2, 904. DOI: 10.1038/srep00904
Motor Sport Magazine. (n.d.). 1983 Brazilian Grand Prix. Retrieved from [link]. Accessed: 2024_03_22
Mourao, P. R. (2024). Drivers’ moves in Formula One Economics: A network analysis since 2000. SPORT TK-Revista EuroAmericana de Ciencias del Deporte, 13, 9. DOI: 10.6018/sportk.540441
Piezunka, H., Lee, W., Haynes, R., and Bothner, M. S. (2018). Escalation of competition into conflict in competitive networks of Formula One drivers. Proceedings of the
National Academy of Sciences of the United States of America, 115(15), E3361-E3367. DOI: 10.1073/pnas.1717303115
Piquero, A. R., Piquero, N. L., and Han, S. (2021). Identifying the Most Successful Formula 1 Drivers in the Turbo Era. The Open Sports Sciences Journal, 14, 151-157. [link]
Van Kesteren, E.-J. and Bergkamp, T. (2023). Bayesian analysis of Formula One race results: Disentangling driver skill and constructor advantage. Journal of Quantitative Analysis in Sports, 19(4), 273–293. DOI: 10.1515/jqas-2022-0021
Vopani. (2023, August). Formula 1 World Championship (1950 - 2023). Kaggle. [link]. Accessed: 2024_03_22
Xia, V., Jain, K., Krishna, A., and Brinton, C. G. (2018). A network-driven methodology for sports ranking and prediction. In 2018 52nd Annual Conference on Information Sciences and Systems (CISS) (pp. 1-6). IEEE. DOI: 10.1109/CISS.2018.8362324
Cintia, P., Coscia, M., and Pappalardo, L. (2016). The Haka network: Evaluating rugby team performance with dynamic graph analysis. In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 1095-1102). IEEE. DOI: 10.1109/ASONAM.2016.7752377
De Meo, P., Ferrara, E., Fiumara, G., and Provetti, A. (2011). Generalized Louvain method for community detection in large networks. In 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA) (pp. 88-93). IEEE. DOI: 10.1109/ISDA.2011.6121636
Ge, Y., and He, Y. (2022). Research on Importance and Correlation Evaluation of Music Network Nodes Based on Page Rank Algorithm. Journal of Applied Mathematics and Computation, 6(2), 267-272. DOI: 10.26855/jamc.2022.06.012,
Hamilton, M. (2022). Formula 1: The Official History. Welbeck.
Jones, B. (2023). The Formula One Record Book: Grand Prix Results, Team & Driver Stats, All-Time Records. Welbeck. Kindle Edition.
Judde, C., Booth, R., and Brooks, R. (2013). Second Place Is First of the Losers: An Analysis of Competitive Balance in Formula One. Journal of Sports Economics, 14(4), 411-439. DOI: 10.1177/1527002513496009
Kanal, S. (2021, May 29). After Bottas, Hamilton and Verstappen, which other trios have shared an F1 podium most often? Formula 1. [link]. Accessed: 2024_03_22
McHale, G. and Relton, S. D. (2018). Identifying key players in soccer teams using network analysis and pass difficulty. European Journal of Operational Research, 268(1), 339-347. DOI: 10.1016/j.ejor.2018.01.018
Motegi, S. and Masuda, N. (2012). A network-based dynamical ranking system for competitive sports. Scientific Reports, 2, 904. DOI: 10.1038/srep00904
Motor Sport Magazine. (n.d.). 1983 Brazilian Grand Prix. Retrieved from [link]. Accessed: 2024_03_22
Mourao, P. R. (2024). Drivers’ moves in Formula One Economics: A network analysis since 2000. SPORT TK-Revista EuroAmericana de Ciencias del Deporte, 13, 9. DOI: 10.6018/sportk.540441
Piezunka, H., Lee, W., Haynes, R., and Bothner, M. S. (2018). Escalation of competition into conflict in competitive networks of Formula One drivers. Proceedings of the
National Academy of Sciences of the United States of America, 115(15), E3361-E3367. DOI: 10.1073/pnas.1717303115
Piquero, A. R., Piquero, N. L., and Han, S. (2021). Identifying the Most Successful Formula 1 Drivers in the Turbo Era. The Open Sports Sciences Journal, 14, 151-157. [link]
Van Kesteren, E.-J. and Bergkamp, T. (2023). Bayesian analysis of Formula One race results: Disentangling driver skill and constructor advantage. Journal of Quantitative Analysis in Sports, 19(4), 273–293. DOI: 10.1515/jqas-2022-0021
Vopani. (2023, August). Formula 1 World Championship (1950 - 2023). Kaggle. [link]. Accessed: 2024_03_22
Xia, V., Jain, K., Krishna, A., and Brinton, C. G. (2018). A network-driven methodology for sports ranking and prediction. In 2018 52nd Annual Conference on Information Sciences and Systems (CISS) (pp. 1-6). IEEE. DOI: 10.1109/CISS.2018.8362324
Publicado
21/07/2024
Como Citar
FARIA, José Geraldo Rigotti de; FERREIRA, Fernando Guimarães.
Podium and Influence: A Network Analysis of the Most Important Formula One Drivers. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 13. , 2024, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 144-157.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2024.3054.
