How to read a tennis win probability
A number like 70% is easy to misread as "this player will win". It means something more useful: in many matches like this one, the player would win about seven times in ten.
In short
A 70% win probability means the player would win about seven matches in ten like this one, so a single upset says nothing about the model. The honest test is calibration over hundreds of matches: did about 70% of the players rated at 70% win? Fair odds are 1 ÷ probability, and being well calibrated is not the same as beating the bookmakers' closing prices.
Figures from our archive of 77,625 matches, updated 22 Oct 2026.
A probability is a frequency
If a model gives a player 70%, the honest test is not one match but hundreds: of all the players it rated at about 70%, did about 70% win? The other 30% are not mistakes; they are the losses that a 70% chance always includes. A single upset tells you almost nothing about a model. Hundreds of matches do.
Checking a model: calibration
This is how our estimates did in the walk-forward backtest from July 2024 to October 2026 (38,207 ATP, WTA and Challenger matches, each estimate made only with data from before the match):
| Favourite's estimate | Matches | Average estimate | Favourite actually won |
|---|---|---|---|
| 50–60% | 13,015 | 54.9% | 55.7% |
| 60–70% | 11,225 | 64.8% | 64.9% |
| 70–80% | 8,234 | 74.6% | 74.2% |
| 80–90% | 4,687 | 84.4% | 82.4% |
| 90% and over | 1,046 | 92.8% | 92.7% |
When the estimate and the outcome stay this close in every band, the model is well calibrated: its percentages mean what they say. The live record of every published estimate is on the track record page.
From probability to odds
A probability turns into "fair" decimal odds as 1 ÷ probability: 70% is 1.43, 50% is 2.00, 25% is 4.00. Bookmakers build a margin into their prices, so their odds are a little shorter than fair odds. Being well calibrated is not the same as beating the market: on average, the closing prices of the sharpest bookmakers have been more accurate than our model, and we show that comparison openly.
Three habits that help
- Read a probability as "how often", never as "will".
- Judge a model on hundreds of matches and on calibration, not on last night's upset.
- Treat probabilities as information. If you bet, set a limit you can afford to lose. 18+. UK support: BeGambleAware ↗.