The WBBL season starts in 72 hours from the time this post is published, with three games on the opening day: Hobart Hurricanes v Perth Scorchers, Adelaide Stikers v Melbourne Renegades, and Sydney Thunder v Melbourne Stars.
I’ve spent the last few weeks working on Elo ratings stuff, and I’ve completed what could be my statistical magnum opus.
To show you how this can be worked out, with a note that it is all very approximate, here’s an example for the Thunder-Stars game.
On the first spreadsheet, there’s my Elo rating formula calculator, which gives an estimated win chance.
This formula is worked out as that team’s transformed rating (using the awesome post here for calculations) divided by the sum transformed rating. It’s an important part of the calculation, as the new rating is calculated by some tricky maths involving that.1
This winning percentage is what I’ve used for these calculations.
In the other spreadsheet, we get a few bits of information.
There’s also a chart that has the chance of each team having x wins at the end of the season, but I’ll tell you the most common values now:
- 8: Sydney Sixers, Sydney Thunder
- 7: Adelaide Strikers, Brisbane Heat, Hobart Hurricanes, Melbourne Stars, Perth Scorchers
- 6: Melbourne Renegades
Go fiddle with the spreadsheets, all in this folder. I’ll be updating it from Saturday.
1For you hardcore number buffs, the new rating is the old rating, plus ((your win percentage minus your predicted win percentage) multiplied by K). K is used to change the ratings, and as my spreadsheet says, I set K to 20. Since the expected winning percentages add to 1, you get whatever your opponent’s winning percentage is of 20 if you win, and lose your percentage of 20 if you lose. Assuming the Thunder win, they will have 43.98% of 20 added to their 1538 rating, making a total of 1546.796997. (I’ll round it to 1547 for simplicity’s sake.) If they lost, meanwhile, then 56.02% of 20 would be subtracted from it.