I have continued to look at the data from the 2019 FIFA Women’s World Cup.
I have been using the data to help me look at the potential of ggplot 2 as a visualisation tool. It has helped me look at generalised linear models fit too using glm in R.
At the moment, I am using the glm function as a descriptive tool. I am going to follow David Little’s posts (link) as I move towards developing models of performance.
I have a GitHub respository for my FIFA data (link).
My most recent visualisations are:
Ball in Play and Ball Not In Play (in Minutes). I am interested in the dwell time in games, namely when the ball is not in ply.
Total Game Time in Minutes. I am keen to see how games last. In this tournament, three games went to extra time (link). The median total game time for this tournament was 97 minutes.
Ambient weather: temperature and fouls awarded. The FIFA Match Facts contain weather information. This gives an opportunity to explore some ambient data. The median temperature for this tournament was 22 degrees centigrade. The median number of fouls awarded was 20.
Ambient weather: humidity and fouls awarded. The FIFA data include a recording of humidity levels at the start of each game. The median humidity was 60%. The median number of fouls awarded was 20.
I have a particular interest in referee behaviour. In this visualisation I include two outliers: the longest and shortest ball in play time. For this tournament the median ball in play time was 55 minutes.
