Understanding Women's Soccer using Machine Learning Techniques

Women’s soccer is on the rise, with both increased interest and professionalization in the past decade. This is evident in the interest and publicity surrounding the recent World Cups, European Championships and the LIGA MX Femenil. There has also been increased availability about data collected from professional women’s matches. This talk will explore the question: How can this data help support teams? In this talk, I will discuss three areas where data can provide insights that can help in squad building and in-game decision making. First, I will discuss how we can value actions and identify a player’s key qualities. Next, I will explain how we can measure a player’s pace of play and how we can use this metric for player recruitment. Lastly, I will explain how we can use data to predict player chemistry.