Earlier this week, I posted my first attempt at a
tennis win probability graph, using Victoria Duval's come from behind upset over Samantha Stosur as an example. I am going to try to make this a daily feature for the remainder of the US Open. Each day, I will pick a particularly noteworthy match and publish its win probability graph. As I don't follow tennis too closely, I am open to suggestions as to which match to feature.
For today's post, I am using
Leyton Hewitt's upset victory over
Juan Martin Del Potro. As with my Duval graph, I am calibrating the inputs to the model such that the initial probability matches the betting consensus (Hewitt with a 12.8% win probability). See the table at the bottom of the graph for the assumed serve and return point probabilities.
| Leyton Hewitt | 6 | 5 | 3 | 7 | 6 | | Excitement | 6.5 |
| Juan Martin Del Potro | 4 | 7 | 6 | 6 | 1 | | Comeback | 13 |
| Point Probabilities (Model Inputs) |
| Player | Serve | Return |
| Hewitt | 0.587 | 0.338 |
| Del Potro | 0.662 | 0.413 |
Leave a Comment