Narrowing the gap in data analytics for women’s football A Swedish case study on the use of data analytics services

Abstract

Recently, women’s football has seen unequal financial growth between teams, with some having superior resources, and an increased use of data analytics due to investment. The impact of the financial resources of teams on the use of data analytics remains uncertain, as it is possible that such resources have contributed to a widening of the competitive disparity between the teams. The study aimed to investigate how teams in the Swedish women’s football league OBOS Damallsvenskan used data analytics services and what characteristics of data analytics services they prioritized, putting into perspective their budgets for data analytics. Data was collected through semi-structured interviews using qualitative research. Teams were grouped by budget into high, medium, and low categories. Each team’s use of data analytics services has been evaluated, putting into perspective the characteristics of each classification. Lastly, the prioritized characteristics for data analytics services from each team in each classification group were identified and examined. The study came across several main findings. Firstly, it was discovered that 50% of the teams fall into the low-budget category which is a concerning number that portrays the current prosperity of the league. Secondly, high-budget teams gain a competitive advantage by collecting and analyzing real-time data to make informed decisions during the games. Thirdly, clubs with successful teams in both women’s and men’s football benefit from synergies as they can share costs across their teams. Furthermore, the size and skills of the data analytics teams are key as information asymmetry can lead to gaining a competitive advantage. Lastly, there is no unilateral solution for data analytics services and the provision of a baseline service is contingent upon each team’s financial capabilities and preferences. The findings add to the existing research on data analytics in football by providing insights into how data analytics can be used to narrow the sportive gap in women’s football.