Matchup effects are a common idea in tennis commentary. It is the thing at the heart of comments like ‘her game matches up well’ against her opponent. One way to think of a matchup effect is as a surprising head-to-head, when results go against what the overall ability of both players would have us expect. Do such effects exist? And are they substantial enough that they matter when it comes to making better predictions about tennis results?
Novak Djokovic looked unstoppable at the Australian Open and he heads into Indian Wells as the hands down favourite for the title. With GIG predictions giving him a 1 and 2 chance to win the whole thing, the question of the event will be whether anyone can stop Djokovic?
The women’s draw for the first of the Sunshine Double is out. In this post, I break down the prospects for the 10 women most likely to impress at Indian Wells this year.
With the close of the second month of the 2019 season, we look back at the biggest pressure performances of the men’s tour. Reilley Opelka takes top honours for having faced the most service pressure in a match in February, racking up 15.5 break point equivalents (BPEs) against John Isner in New York. Opelka also saved the most of the BPEs faces winning a whopping 92% of high-pressure service points.
A model that could predict a player’s performance on serve would have a number of interesting uses like forecasting the outcome of matches or identifying surprising performances. But for any of these uses the model would need to be accurate and reliable. How should we evaluate a model’s performance? And how do we know when a model is good enough?
Every player has days when everything seems to work and other days when nothing seems to go right. Saying when a player has truly over (or under) performed is tricky in tennis because there is always an opponent on the other side of the net that is also influencing the outcome of points. In this post, I look at a basic strategy to try to isolate the ability of the server and receiver, and discuss how this might be used to identify surprising performances on serve.
Pressure is one of those concepts in tennis that we all know exists but we struggle to calculate. I’ve made multiple attempts at quantifying scoreboard pressure and have yet to come around to one that is both statistically useful and easy to interpret. But some recent experimenting has uncovered what I think could be as close to a ‘best’ statistic for pressure as I am likely to find.
In his win over Roger Federer, 20 year-old Stefanos Tsitsipas not only earned the biggest upset of the 2019 Australian Open so far, he caused many to wonder whether tennis was seeing the start of a new era. Tsitsipas’s journey at the 2019 AO is the biggest of multiple success stories for a young crop of talents on the men’s tour, stories that have already made this year one of the most unique in AO history.
The introduction of a super tiebreak in the deciding set of singles matches was one of a number of changes at the 2019 Australian Open. After two rounds, 3 men’s and 2 women’s matches have already put that rule to the test. What do the outcomes of those matches tell us about the possible impact of the new format?
Ahead of the first round of the Australian Open, I take a look at some of the likely winners on the men’s side. The forecast bodes well for the Big 3, with Novak Djokovic leading the race toward the first slam title of the 2019 season.
