Tennis Picks
The market’s picks for each of 4 open ATP and WTA matches, ranked from the clearest favourite to the closest call, and which way it leans on total games.
Live market pricesUpdated today at 2:25 PM ET
Where these numbers come from: Kalshi prices: KXATPMATCH and KXWTAMATCH for each match, the set-winner, total-games and game-spread series for its props, KXATP and KXWTA for tournament winners, and KXATPFINALSQUAL and KXWTAFINALSQUAL for the Finals fields. The track record prices each match at the last trade at least fifteen minutes before the earlier of its scheduled start and the moment Kalshi recorded it going live, which it has done since August 11, 2026. A scheduled time alone is not enough: it came after the first point in about one match in eleven.
ATPEvery match with a favourite, ranked by the gap between the two players’ prices. Matches priced level are left out.
ATP picks
| Pick | Opponent | Chance | Margin |
|---|---|---|---|
| Lorenzo MusettiATP Stockholm · Quarterfinal | Ugo Humbert | 65% | 28 pts |
| Alejandro TabiloATP Stockholm · Semifinal | Thiago Agustin Tirante | 57% | 13 pts |
WTAEvery match with a favourite, ranked by the gap between the two players’ prices. Matches priced level are left out.
WTA picks
| Pick | Opponent | Chance | Margin |
|---|---|---|---|
| Coco GauffWTA Finals Women Singles · Group A | Marta Kostyuk | 77% | 53 pts |
| Linda NoskovaWTA Finals Women Singles · Group A | Jessica Pegula | 55% | 10 pts |
TOTAL GAMESOver when the market prices more games than the line above 50%, Under below it.
Total-games leans
| Match | Line | Lean | Over |
|---|---|---|---|
| Musetti vs HumbertATP Stockholm | 22.5 | Over | 53% |
| Kostyuk vs GauffWTA Finals Women Singles | 19.5 | Over | 55% |
| Pegula vs NoskovaWTA Finals Women Singles | 23.5 | Under | 45% |
RESULTSThe most recently graded matches, as Kalshi’s markets settled them.
Latest ATP and WTA results
TRACK RECORDAcross the 1,332 ATP and WTA matches with a favourite that Kalshi graded from Aug 11, 2026 through Oct 13, 2026, the player priced higher before play won 906 (68%; ATP 430 of 645, WTA 476 of 687). By how sure the market was:
How the market’s tennis picks have done
| Favourite’s price | Won | Matches | Win rate |
|---|---|---|---|
| Under 60% | 175 | 339 | 52% |
| 60–69% | 262 | 422 | 62% |
| 70–79% | 220 | 285 | 77% |
| 80–89% | 164 | 195 | 84% |
| 90% and up | 85 | 91 | 93% |
BY TOURNAMENTThe 16 most recent tournaments: how many matches the favourite won, and the winner the market rated least likely.
The record, tournament by tournament
| Tournament | Favourites | Biggest upset |
|---|---|---|
| ATP ShanghaiOct 5, 2026 – Oct 13, 2026 | 70 of 110 | Several at 7% |
| WTA WuhanOct 10, 2026 – Oct 13, 2026 | 30 of 48 | Hanyu Guo · 11% |
| WTA BeijingSep 28, 2026 – Oct 11, 2026 | 87 of 125 | Alina Charaeva · 6% |
| ATP BeijingSep 28, 2026 – Oct 6, 2026 | 29 of 41 | Jie Cui · 27% |
| ATP TokyoSep 28, 2026 – Oct 6, 2026 | 26 of 42 | Adolfo Daniel Vallejo · 20% |
| ATP ChengduSep 22, 2026 – Sep 29, 2026 | 28 of 39 | Petr Bar Biryukov · 31% |
| ATP HangzhouSep 22, 2026 – Sep 29, 2026 | 30 of 39 | Several at 36% |
| WTA SeoulSep 19, 2026 – Sep 27, 2026 | 24 of 40 | Sohyun Park · 11% |
| WTA SingaporeSep 19, 2026 – Sep 27, 2026 | 29 of 37 | Tatiana Prozorova · 18% |
| WTA Sao PauloSep 12, 2026 – Sep 21, 2026 | 27 of 37 | Nadia Podoroska · 19% |
| WTA GuadalajaraSep 12, 2026 – Sep 19, 2026 | 29 of 36 | Liudmila Samsonova · 22% |
| US Open Men SinglesAug 24, 2026 – Sep 13, 2026 | 152 of 209 | Dane Sweeny · 8% |
| US Open Women SinglesAug 24, 2026 – Sep 12, 2026 | 154 of 217 | Angela Fita Boluda · 14% |
| ATP Winston SalemAug 22, 2026 – Aug 29, 2026 | 26 of 55 | Hugo Grenier · 16% |
| WTA MonterreyAug 22, 2026 – Aug 29, 2026 | 21 of 37 | En-Shuo Liang · 31% |
| ATP CincinnatiAug 11, 2026 – Aug 23, 2026 | 67 of 107 | Jaime Faria · 18% |
LEFT OUTLeft out: 6 matches priced level (no favourite); 55 voided or canceled matches; 132 matches with no recorded first start (interrupted and resumed, or first seen mid-match); 8 matches with a side that did not trade in the two days before; 2 matches whose last hour before the price time moved over 15¢. The voided and canceled matches:
Matches the record leaves out
| Match | Tournament |
|---|---|
| Norrie vs Shapovalov | ATP Shanghai |
| de Minaur vs Molcan | ATP Shanghai |
| Osorio vs Zhu | WTA Wuhan |
| Li vs Zheng | WTA Wuhan |
| Bencic vs Zhang | WTA Wuhan |
| Jovic vs Pohankova | WTA Wuhan |
| Kalinskaya vs Zhang | WTA Wuhan |
| Parry vs Kalinskaya | WTA Wuhan |
| Tjen vs Oliynykova | WTA Wuhan |
| Yastremska vs Wang | WTA Beijing |
| Golubic vs Korneeva | WTA Beijing |
| Marcinko vs Frech | WTA Beijing |
| Sherif Ahmed Abdelaziz vs Kudermetova | WTA Beijing |
| TE vs Duckworth | ATP Beijing |
| Molcan vs Rinderknech | ATP Beijing |
| Musetti vs Fery | ATP Tokyo |
| Borges vs Ugo Carabelli | ATP Chengdu |
| Zidansek vs Jeong | WTA Seoul |
| Parks vs Tjen | WTA Singapore |
| Gibson vs Anisimova | WTA Singapore |
| Mertens vs Krejcikova | WTA Singapore |
| Prozorova vs Gibson | WTA Singapore |
| Smith vs Tikhonova | WTA Sao Paulo |
| Jeanjean vs Quevedo | WTA Sao Paulo |
| Semenistaja vs Badosa | WTA Sao Paulo |
| Fernandez vs Kinoshita | WTA Sao Paulo |
| Osuigwe vs Quevedo | WTA Sao Paulo |
| Lepchenko vs Melichar-Martinez | WTA Guadalajara |
| Parks vs Sherif Ahmed Abdelaziz | WTA Guadalajara |
| Kostyuk vs Townsend | WTA Guadalajara |
| Neumayer vs Crawford | US Open Men Singles |
| Smith vs Galarneau | US Open Men Singles |
| Smith vs Pellegrino | US Open Men Singles |
| Zhang vs Sakamoto | US Open Men Singles |
| Virtanen vs Dimitrov | US Open Men Singles |
| Cerundolo vs Ruud | US Open Men Singles |
| Cilic vs Rublev | US Open Men Singles |
| Jodar vs Kokkinakis | US Open Men Singles |
| Sorribes Tormo vs Noha Akugue | US Open Women Singles |
| Potapova vs Valentova | US Open Women Singles |
| Prizmic vs Hewitt | ATP Winston Salem |
| Royer vs Giron | ATP Winston Salem |
| Safiullin vs Fucsovics | ATP Winston Salem |
| Sonego vs Kopriva | ATP Winston Salem |
| Bartunkova vs Potapova | WTA Monterrey |
| Kalinina vs Joint | WTA Monterrey |
| Timofeeva vs Li | WTA Monterrey |
| Wolf vs Samuel | ATP Cincinnati |
| Moutet vs Hurkacz | ATP Cincinnati |
| Van de Zandschulp vs Griekspoor | ATP Cincinnati |
| Fonseca vs O'Connell | ATP Cincinnati |
| Korneeva vs Charaeva | WTA Cincinnati |
| Timofeeva vs Siniakova | WTA Cincinnati |
| Wang vs Svitolina | WTA Cincinnati |
| Bencic vs Gauff | WTA Toronto |
PRICED RIGHT?From Aug 11, 2026 through Oct 13, 2026, favourites on Kalshi won less often than their prices said, by 1 point: 906 wins in 1,332 matches (68%), against prices that averaged 69%. The furthest off, level at 3 points: 52% of those priced under 60% won, against an average price of 55% (339 matches) and 77% of those priced 70–79% won, against an average price of 74% (285 matches).
Did the tennis favourites win as often as their prices said?
Hit rate68%906 wins in 1,332 matches
Their prices said69%The average price before play: about 918.2 wins expected
Against the price−1 ptFavourites won less often than their prices said, by 1 point
Biggest upset6%Alina Charaeva, over Elena Rybakina at WTA Beijing: the lowest-priced winner in the record
ATP and WTA favourites: how often they won, against their price
← Below their pricesAbove their prices →- Under 60%Under 60%Favourites priced under 60%: 52% won, against an average price of 55%, over 339 matches:−352%175 wins in 339 matches (52%), priced at 55% on average
- 60–69%60–69%Favourites priced 60–69%: 62% won, against an average price of 64%, over 422 matches:−262%262 wins in 422 matches (62%), priced at 64% on average
- 70–79%70–79%Favourites priced 70–79%: 77% won, against an average price of 74%, over 285 matches:+377%220 wins in 285 matches (77%), priced at 74% on average
- 80–89%80–89%Favourites priced 80–89%: 84% won, against an average price of 84%, over 195 matches:084%164 wins in 195 matches (84%), priced at 84% on average
- 90% and up90% and upFavourites priced 90% and up: 93% won, against an average price of 93%, over 91 matches:093%85 wins in 91 matches (93%), priced at 93% on average
Beat their pricesWins over the number the prices expected
- US Open Men Singles+6.3152 of 209 · 145.7 expected
- ATP Hangzhou+3.930 of 39 · 26.1 expected
- WTA Guadalajara+3.829 of 36 · 25.2 expected
- WTA Sao Paulo+1.927 of 37 · 25.1 expected
- ATP Chengdu+1.828 of 39 · 26.2 expected
Fell shortWins under the number the prices expected
- ATP Winston Salem−8.826 of 55 · 34.8 expected
- ATP Shanghai−6.670 of 110 · 76.6 expected
- WTA Beijing−4.587 of 125 · 91.5 expected
- WTA Seoul−4.124 of 40 · 28.1 expected
- ATP Tokyo−3.426 of 42 · 29.4 expected
METHOD
How to read this page
A pick is the player the market prices higher; Margin is how many percentage points separate the two prices, so the top of each list is where the market is surest. A match with only one side priced is listed last, with no margin.
A lean is the side of the total-games line the market prices above 50%. It is the market’s read, not a tip.
The track record counts each graded ATP and WTA match whose two players printed different prices before play; the price bands go by the favourite’s price then. It runs through the date it names and is extended as matches are added.
Priced right? sets the record against its own prices. A favourite priced at 70% should win about 7 times in 10, so each price band’s bar is the share that won minus the band’s average price, in percentage points: right of the centre line, those favourites won more often than their prices said; left of it, less often. One result moves a small band a long way, so read each bar with its count.
FAQ
Questions
What is the strongest tennis pick today?
By the market’s prices, Coco Gauff over Marta Kostyuk at WTA Finals Women Singles, at 77%. No pick is safe: a price is a probability, not a promise.
What is the closest tennis match today?
Pegula vs Noskova at WTA Finals Women Singles: Linda Noskova edges it at 55%.
How often does the tennis favourite win on Kalshi?
Across the 1,332 ATP and WTA matches with a favourite that Kalshi graded from Aug 11, 2026 through Oct 13, 2026, the player priced higher before play won 906 (68%; ATP 430 of 645, WTA 476 of 687).
Are Kalshi’s tennis favourites priced right?
From Aug 11, 2026 through Oct 13, 2026, favourites on Kalshi won less often than their prices said, by 1 point: 906 wins in 1,332 matches (68%), against prices that averaged 69%. The furthest off, level at 3 points: 52% of those priced under 60% won, against an average price of 55% (339 matches) and 77% of those priced 70–79% won, against an average price of 74% (285 matches).
How do I read Kalshi’s tennis odds?
Each price is what a contract paying $1 if that outcome happens costs right now, so 64¢ reads as a 64% chance. Prices move with every point once a match starts, and every one on this page links to its market.
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