Win probability

Wednesday, 1 July 2026

20 matches selected · 2 tournaments · model last ran 17:50 UTC

Umpiry rates 20 matches on Wednesday, 1 July 2026. The closest is Arthur Rinderknech v Martin Damm at 51 % — the model’s most uncertain call of the day. The most one-sided is Jessica Pegula v Sara Sorribes Tormo at 96 %. Probabilities come from a per-tour model trained on Elo, surface Elo, recent serve and return form and layoff.

Rated matches · ordered closest first
Time	Tournament	Round	Match	Probability	Verdict	H2H
13:15	Wimbledon ATP · grass	R64	Rinderknech A.Damm M.	51 %49 %	Toss-up	1–1
13:00	Wimbledon ATP · grass	R64	Safiullin R.Van De Zandschulp B.	55 %45 %	Toss-up	2–0
11:35	Wimbledon ATP · grass	R128	Molcan A.Altmaier D.	58 %42 %	Slight edge	3–0
15:00	Wimbledon WTA · grass	R64	Siniakova K.Bartunkova N.	62 %38 %	Slight edge	0–1
12:25	Wimbledon WTA · grass	R64	Yastremska D.Bouzas Maneiro J.	65 %35 %	Slight edge	1–3
10:10	Wimbledon WTA · grass	R64	Sawangkaew M.Parks A.	67 %33 %	Clear favourite	2–0
16:55	Wimbledon WTA · grass	R64	Alexandrova E.Tararudee L.	69 %31 %	Clear favourite	1–0
10:10	Wimbledon ATP · grass	R64	Tien L.Fucsovics M.	74 %26 %	Clear favourite	0–1
13:40	Wimbledon WTA · grass	R64	Kalinskaya A.Parry D.	74 %26 %	Clear favourite	2–0
10:10	Wimbledon WTA · grass	R64	Kasatkina D.Tjen J.	75 %25 %	Clear favourite	1–0
11:45	Wimbledon ATP · grass	R128	Cobolli F.Navone M.	76 %24 %	Clear favourite	2–0
15:40	Wimbledon WTA · grass	R64	Andreeva M.Krejcikova B.	80 %20 %	Clear favourite	3–2
16:50	Wimbledon ATP · grass	R64	Auger Aliassime F.Prizmic D.	84 %16 %	Strong favourite	1–0
18:50	Wimbledon ATP · grass	R64	Djokovic N.Tsitsipas S.	86 %14 %	Strong favourite	13–2
12:35	Wimbledon WTA · grass	R64	Muchova K.Zhang S.	87 %13 %	Strong favourite	4–0
14:15	Wimbledon WTA · grass	R64	Gauff C.Sierra S.	91 %9 %	Strong favourite	3–0
13:15	Wimbledon ATP · grass	R64	Medvedev D.Merida Aguilar D.	92 %8 %	Strong favourite	1–0
12:10	Wimbledon WTA · grass	R64	Sabalenka A.Kessler M.	93 %7 %	Strong favourite	2–0
12:40	Wimbledon ATP · grass	R64	Sinner J.Borges N.	96 %4 %	Strong favourite	2–0
15:45	Wimbledon WTA · grass	R64	Pegula J.Sorribes Tormo S.	96 %4 %	Strong favourite	2–3

Rated matches · ordered most one-sided first
Time	Tournament	Round	Match	Probability	Verdict	H2H
15:45	Wimbledon WTA · grass	R64	Pegula J.Sorribes Tormo S.	96 %4 %	Strong favourite	2–3
12:40	Wimbledon ATP · grass	R64	Sinner J.Borges N.	96 %4 %	Strong favourite	2–0
12:10	Wimbledon WTA · grass	R64	Sabalenka A.Kessler M.	93 %7 %	Strong favourite	2–0
13:15	Wimbledon ATP · grass	R64	Medvedev D.Merida Aguilar D.	92 %8 %	Strong favourite	1–0
14:15	Wimbledon WTA · grass	R64	Gauff C.Sierra S.	91 %9 %	Strong favourite	3–0
12:35	Wimbledon WTA · grass	R64	Muchova K.Zhang S.	87 %13 %	Strong favourite	4–0
18:50	Wimbledon ATP · grass	R64	Djokovic N.Tsitsipas S.	86 %14 %	Strong favourite	13–2
16:50	Wimbledon ATP · grass	R64	Auger Aliassime F.Prizmic D.	84 %16 %	Strong favourite	1–0
15:40	Wimbledon WTA · grass	R64	Andreeva M.Krejcikova B.	80 %20 %	Clear favourite	3–2
11:45	Wimbledon ATP · grass	R128	Cobolli F.Navone M.	76 %24 %	Clear favourite	2–0
10:10	Wimbledon WTA · grass	R64	Kasatkina D.Tjen J.	75 %25 %	Clear favourite	1–0
13:40	Wimbledon WTA · grass	R64	Kalinskaya A.Parry D.	74 %26 %	Clear favourite	2–0
10:10	Wimbledon ATP · grass	R64	Tien L.Fucsovics M.	74 %26 %	Clear favourite	0–1

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
Tour	Correct
ATP / WTA	66 %
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, 30 June 2026 · 20 matches

Favourites won

10 / 20

Model expected

13.9

The model expected 13.9 favourites to win; 10 did. See yesterday’s page.

Biggest shock, last 7 days

28 Jun

Milan

CHALLENGER · clay

Alejo Sanchez Quilez beat Mili Poljicak

Surprise score

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.