Win probability

Wednesday, 9 September 2026

7 matches selected · 4 tournaments · model last ran 12:50 UTC

Umpiry rates 7 matches on Wednesday, 9 September 2026. The closest is Karen Khachanov v Alexander Blockx at 52 % — the model’s most uncertain call of the day. The most one-sided is Carlos Alcaraz v Ben Shelton at 85 %. Probabilities come from a per-tour model trained on Elo, surface Elo, recent serve and return form and layoff.

Rated matches · ordered closest first
TimeTournamentRoundMatchProbabilityVerdictH2H
21:30US Open
ATP · hard
QFKhachanov K.Blockx A.52 %48 %Toss-up
12:30Tulln
CHALLENGER · clay
R16Moeller M.Soto M.55 %45 %Toss-up1–0
20:00US Open
WTA · hard
QFGauff C.Andreeva M.55 %45 %Toss-up4–0
11:00W35 Reus
CHALLENGER · clay
R32Zeltina B.Hesse A.58 %42 %Toss-up
02:00US Open
WTA · hard
QFPegula J.Navarro E.79 %21 %Clear favourite6–0
18:30US Open
WTA · hard
QFRybakina E.Zheng Q.81 %19 %Strong favourite4–1
04:30US Open
ATP · hard
QFAlcaraz C.Shelton B.85 %15 %Strong favourite3–0

How to read this

Each row gives the model’s probability that the favourite wins, and the verdict says the same thing in words. Rows are ordered by how close the model thinks the match is, so the top of the table is where it is least sure. A 70 % favourite losing is not a broken model — it is the 30 %. Probabilities are not odds and take no account of any market.

How often the model has been right

Umpiry win-probability model accuracy by tour family, measured on the predictions the model made
TourCorrect
ATP / WTA66 %
Challenger (men)64 %
Challenger (women)68 %
ITF (men)66 %
ITF (women)64 %

Measured on the predictions the model actually made, not on a backtest — see Methodology.

Yesterday

Tuesday, 8 September 2026 · 15 matches

Favourites won

11 / 15

Model expected

8.9

The model expected 8.9 favourites to win; 11 did. See yesterday’s page.

Biggest shock, last 7 days

8 Sept
W50 Evora
ITF · hard
R32

Surprise score

91

Questions

How is the probability calculated?
A separate model for each tour, trained on Elo, surface-specific Elo, recent serve and return form and time since the player’s last match. It runs several times a day; the time of the last run is at the top of this page.
How often is the model right?
We publish it. The table above gives the hit rate for each tour family, measured on the predictions the model actually made — see Methodology for how it is computed.
Why are the closest matches at the top?
Rows are ordered by distance from 50 %, so the table opens where the model is least sure. “Most one-sided” reverses the order and groups the rows by tournament.
Is this a betting tip?
No. The page shows a model’s probability and how often that model has been right. There are no odds, no comparison with a market and no suggested stake.