FIFA World Cup and climate change: correlation is not causation. [Copa del Mundo FIFA y cambio climático: correlación no implica causalidad].
Sports analytics is defined as the process that identifies and acquires knowledge and insight about players and teams’ performances. To do so, analysts use a wide variety of data sources coming from matches and individual players’ performances (O'Donoghue & Holmes 2014; Jayal, McRobert, Oatley & O’Donoghue, 2018). Nowadays, detailed data from different nature including technical skills, individual physiological performances, team formations, or injuries are analysed on a daily basis by the analytics departments belonging to sports clubs and professional franchises. Even private companies like STATS or OPTA generate important revenues offering their movement tracking values and advanced metrics to media and fans. In the emerging field of Sports Analytics, as in many others, analysts must be aware of spurious correlations. These can come up due to the size (not nature) of data, a common-causal variable or just due to serendipity. For this reason, we always must keep in mind the lessons of the statistician Stephen John Senn and his sharp quote on the matter: “Statistics is not just about merely warning that correlation is not causation. Sometimes correlation isn’t even correlation”. Thus, we will explain an example of how climate change can be affecting, or not, on the FIFA World Cup performance statistics.
Allmers, S., & Maennig, W. (2009). Economic impacts of the FIFA Soccer World Cups in France 1998, Germany 2006, and outlook for South Africa 2010. Eastern Economic Journal, 35(4), 500-519.
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(1), 137-147.
Jayal, A., McRobert, A., Oatley, G., & O’Donoghue, P. (2018). Sports Analytics: Analysis, Visualisation and Decision Making in Sports Performance. Routledge.
Kakamu, T.; Wada, K.; Smith, D. R.; Endo, S., & Fukushima T. (2017). Preventing heat illness in the anticipated hot climate of the Tokyo 2020 Summer Olympic Games. Environmental Health and Preventive Medicine 22(68), 1-6.
Matzarakis, A., & Fröhlich, D. (2015). Sport events and climate for visitors-the case of FIFA World Cup in Qatar 2022. International Journal of Biometeorology, 59(4), 481-586.
Mohr, M.; Nybo, L.; Grantham, J., & Racinais, S. (2012). Physiological Responses and Physical Performance during Football in the Heat. PLoS ONE, 7(6), e39202.
NASA (2018). Global Climate Change, Vital Signs of the Planet. [Internet] http://climate.nasa.gov/ (last accessed, Jul. 18)
Nassis, G. P.; Brito, J.; Dvorak, J.; Chalabi, H.; & Racinais, S. (2015). The association of environmental heat stress with performance: analysis of the 2014 FIFA World Cup Brazil. British Journal of Sports Medicine, 49(9), 609-613.
Nicolau, J. L., & Sharma, A. (2018). A generalization of the FIFA World Cup effect. Tourism Management, 66(June), 315-317.
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.
O’Donoghue, P., & Holmes, L. (2014). Data analysis in sport. Routledge.
Pachuari R. K.; Allen, M. R.; Barros, V. R.; Broome, J.; Cramer, W.; Christ, R., et al. (2014). Climate change 2014: synthesis report. Contribution of working groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Intergovernmental Panel on Climate Change, Geneva. Retrieved from:
Ramdas, B.; van Gaalen, R., & Bolton, J. (2015). The Announcement Impact of Hosting the FIFA World Cup on Host Country Stock Markets. Procedia Economics Finance, 30, 226-238.
Robinson, W. S. (1950). Ecological correlations and the behaviour of individuals. American Sociological Review, 15(3), 351-357.
Rumpf, M. C.; Silva, J. R.; Hertzog, M.; Farooq, A., & Nassis, G. (2017). Technical and physical analysis of the 2014 FIFA World Cup Brazil: winners vs. losers. The Journal of sports medicine and physical fitness, 57(10), 1338-1343.
Vandenbroucke, J. P.; Broadbent, A., & Pearce, N. (2016). Causality and causal inference in epidemiology: the need for a pluralistic approach. International Journal of Epidemiology, 45(6), 1776-1786.
Vigen, T. (2015). Spurious Correlations. Hachette Books.
Wikipedia (2018). FIFA World Cup-related lists. [Internet] (last accessed, Jul. 18). Retrieved from:
Palabras clave/key words
------------------------ 0 -------------------------