In the two latest WTA events, we saw a mix of the expected and the unusual. Simona Halep, the heavy favorite in Prague, wound up with the title despite a couple of demanding three-setters in her first two rounds. The week’s other tournament, in Lexington, failed to follow the script. Serena Williams and Aryna Sabalenka, the big hitters at the top and bottom of the bracket, combined for three wins, with four unseeded players making up the semi-final field.
Last week I pointed out that Palermo–the tour’s initial comeback event–was so unpredictable that you would’ve been better off to treat each match as a coin flip than to use pre-layoff player strength ratings (such as Elo) to forecast outcomes. Such an upset-ridden event isn’t unheard of, even in pandemic-free times, but it is suggestive that the WTA rank-and-file haven’t quite returned to their usual form.
Prague and Lexington give us three times as much data to work with. Plus, we might theorize that Prague would be a little more predictable because so many players in that field also took part in the Palermo event, meaning that they have a little more recent match experience. While our sample of 93 main draw matches is still flimsy, it brings us a little closer to understanding how well traditional forecasts will handle this unusual time.
A thorny Brier patch
The metric I’m using to quantify predictability–or to put it another way, the validity of pre-layoff player ratings–is Brier Score, which takes into account both raw accuracy (did the forecast pick the right player to win?) and confidence level (was the forecast too strong, too weak, or just right?). Tour-level Brier Scores are usually in the range of 0.21, while a score of 0.25 means the predictions were no better than coin flips. A lower score represents more accurate predictions.
Here are the Brier Scores for Palermo, Lexington, and Prague, along with the average of the three, and the average of all WTA International events (on all surfaces) since 2017. (The scores are based on forecasts generated from my Elo ratings.) We might expect the first round to be different, since players are particularly rusty at that stage, so I’ve also broken out first round (“R32 Brier”) matches for each of the tournaments and averages in the table.
Tournament Brier R32 Brier Palermo 0.268 0.295 Lexington 0.226 0.170 Prague 0.212 0.247 Comeback Avg 0.235 0.237 Intl Avg 0.217 0.213
As we last week, the Palermo results truly defied expectations. More than half of the matches were upsets (according to my Elo ratings), with a particularly unpredictable first round.
That didn’t last. The Prague first round rated 0.247–just barely better than coin flips–but the messiness didn’t last beyond the first couple of days. The event’s overall Brier Score was 0.212, slightly better than the average WTA International. In other words, this group of 32 women, only recently returned from a months-long break, delivered results that were roughly as predictable as we would expect in the middle of a normal season.
The Lexington numbers are a bit more difficult to make sense of, but like Prague’s, they point to a post-coronavirus world that isn’t all that weird. The opening round closely followed the script, with a Brier Score of 0.170. Of the last 115 WTA International events, only 22 were more predictable. The forecast accuracy didn’t last, in large part because of Serena’s loss at the hands of Shelby Rogers. The rating for the entire tournament was 0.226, less predictable than usual, but much better than random guessing and closer to tour average than to the assumption-questioning Palermo numbers.
Revised estimates
We’re still early in the process of evaluating what to expect from players after the COVID-19 layoff. As more tournaments take place, we can identify whether players become more predictable with more matches under their belts. (Perhaps the Prague participants who skipped Palermo were more difficult to forecast, although Halep is an obvious counterexample.)
At this point, anything is possible. It could be that we will steadily drift back to business is usual. On the other hand, the new social-distancing-oriented rules–with few or no fans on site, nightlife limited to Netflix, players fetching their own towels, and new variations of on-court coaching–might work to the advantage of some women and the disadvantage of others. If that’s the case, Elo ratings will go through a novel period of adjustment as they shift to reflect which players thrive on the post-corona tour.
It’s too early to do much more than speculate about something as significant as that. But in the last week, we’ve seen forecasts go from wildly wrong (in Palermo) to not half bad (in Lexington and Prague). We’ve gained some confidence that for all the things that have obviously changed since March, our approach to player ratings may be one thing that largely remains the same.