There is one game remaining in this year’s Women’s T20 World Cup. Australia will play England in the final at North Sound on 24 November.
I have been looking at some naive probabilities about the partnerships of winning and losing teams.
Before the tournament I had recorded data from ICC T20 games in 2017-2018 (n=58). These enabled me to estimate some prior probabilities before the World Cup started. I have used the tournament website to collect data from the World Cup in the West Indies (n=20 completed games) to give me a set of posterior outcomes.
At this World Cup, winning teams have established their dominance with first wicket partnerships (9 of the 20 games have partnerships > 50 runs). Losing teams have had just two 50 run + opening partnerships. Losing teams have fourth wicket partnerships as an important contribution to their run totals.
At present, the median profiles for runs scored per wicket in the tournament is:
The median winning run total is 137 (range 81 to 194) and median losing total is 99 (range 71 to 160).
North Sound (CricketHer, Twitter)
In the lull between the Group Games and the semi-finals of the Women’s T20 Cricket World Cup, I have been looking at the data I have collected and trying out some ggplot visualisation.
My attempts with the ggridges package failed and I am going to re-try. But in the meantime, here are two comparisons that use the ggrepel package. My data are for the total runs scored in each wicket partnerships. The data do not include the games decided by Duckworth-Lewis methods (England v Bangladesh).
I used Baptiste Auguie’s suggestions for laying out multiple plots (two in my case) and installed the grid and gridExtra packages to help me.
The Group Games have concluded at the 2018 Women’s Cricket T20 competition in the West Indies.
I have been looking at the runs scored in partnerships in the Group Games and comparing them with some priors calculated from 58 T20 games in 2017-2018. I have not included rain affected games or games decided by Duckworth-Lewis calculations.
My graphs of these data:
Winning Team Comparisons
Losing Team Comparisons
Winning and Losing Posteriors from Group Games