This post is aimed at walking through one method of comparing players upon specific metrics within a league setting. For this example I will use a couple of different metrics from the free StatsBomb FA WSL dataset.
What a month of Women’s football we had, culminating in a final where the USA were made to earn their fourth World Cup title. The Netherlands however, can be proud of their achievements, making their first final in their second world cup appearance. Let’s summarise the match quickly.
Team Name Goals Shots Shots On Target xG Passes Successful Pass % Netherlands 0 6 4 0.
The Fifa Women’s World Cup is coming to a close and the race for the golden boot is tight, with the top 3 all still involved in the tournament (Table 1).
Player Name Team Name Goals Shots xG Alex Morgan United States 6 20 2.19 Ellen White England 6 18 3.
The knockout round of the Women’s World Cup has arrived. After two weeks of group phase matches, the last 16 has been decided. All of the top nations made it through which has set up a couple tough looking matches. So let’s breakdown a couple of these matches and look how these teams progressed through to this stage of the tournament.
Canada made it through to the knockout phase after finishing second in Group E, after winning 2 matches and losing to the Netherlands.
It’s been a few days since I last posted about the Women’s World Cup, and with the end of the second round of games I thought now would be a good time as any to put together a summary of where each group is at, looking ahead to the final round of games. So let’s get right in to it.
This group has so far been all about the host nation, who with one game to go have already qualified for the knockout rounds.
An analysis of passing in the Fifa Women's World Cup
An analysis of day 3 of the womens world cup in France
An analysis of the first game of the Women's world cup using R
An anaysis of shots using FA WSL data from StatsBomb and the ggplot package in R