Matchboard
AI tennis predictions: professional match breakdown
The page gathers the upcoming matches of the selected sport, model probabilities, odds, results and AI breakdowns in a single match center.
Kovacevic A
Khachanov K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 33.2% / 66.8%
Market 1 / 2: 32.3% / 67.7%
Favourite trap: no
Data completeness: 72%
Match context
Court:Lindner Femili Tennis Senter. Stadium
Bookmaker coverage: 1×2 7 · total 0
Tournament: ATP Cincinnati, USA Men Singles
Kenin S
Lys E
All stats and model conclusions
Model vs market
Glicko 1 / 2: 44.1% / 55.9%
Market 1 / 2: 42.7% / 57.3%
Favourite trap: no
Data completeness: 72%
Match context
Court:Lindner Femili Tennis Senter. Grandstend
Bookmaker coverage: 1×2 7 · total 0
Tournament: International WTA Cincinnati, USA Women Singles
Bayldon B / Hilderbrand T
Cash R / Stevens B
All stats and model conclusions
Model vs market
Glicko 1 / 2: 31.0% / 69.0%
Market 1 / 2: 29.1% / 71.0%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International ATP Challenger. Brownsburg. Doubles
Kavanaka Kh
Suzuki Eita
All stats and model conclusions
Model vs market
Glicko 1 / 2: 48.0% / 52.0%
Market 1 / 2: 48.3% / 51.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Men. Japan
Karatsu Y
Ono C K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 46.1% / 53.9%
Market 1 / 2: 44.7% / 55.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Men. Japan
Yuan Chengyiyi
Shao Yushan
All stats and model conclusions
Model vs market
Glicko 1 / 2: 44.7% / 55.3%
Market 1 / 2: 44.0% / 56.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Women. China. Doubles
Hou Yanan / Plipuech P
Yodpetch K / Zhang Ruien
All stats and model conclusions
Model vs market
Glicko 1 / 2: 47.1% / 52.9%
Market 1 / 2: 46.9% / 53.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: International World Tennis. Women. China. Doubles
Dellavedova M
Ogura K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 82.4% / 17.6%
Market 1 / 2: 84.3% / 15.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. China. Doubles
Chung Yunseong
Jasika O
All stats and model conclusions
Model vs market
Glicko 1 / 2: 38.3% / 61.7%
Market 1 / 2: 37.8% / 62.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Men. China. Doubles
Chung Yunseong / Hsieh Cheng-Peng
Jasika O / Lee Duckhee
All stats and model conclusions
Model vs market
Glicko 1 / 2: 50.5% / 49.5%
Market 1 / 2: 53.8% / 46.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 1 · total 0
Tournament: International World Tennis. Men. China. Doubles
Leong S L X
Naklo T
All stats and model conclusions
Model vs market
Glicko 1 / 2: 41.0% / 59.0%
Market 1 / 2: 40.1% / 59.9%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: ITF Women - Singles: W15 Tianjin 2 (China), hard
Matsuoka H
Sultanov K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 56.3% / 43.7%
Market 1 / 2: 55.9% / 44.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International ATP Challenger. Astana
Dougaz A
Fomin S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 59.3% / 40.7%
Market 1 / 2: 59.7% / 40.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International ATP Challenger. Astana
Chun Yu./Khsi Chen-Pen
Yasika O./Li D.-Kh.
All stats and model conclusions
Model vs market
Glicko 1 / 2: 53.1% / 46.9%
Market 1 / 2: 53.7% / 46.3%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Men - Doubles: M15 Tianjin 2 (China), hard
Hou Y./Plipuek P.
Yodpetch K./Zhang R.
All stats and model conclusions
Model vs market
Glicko 1 / 2: 48.7% / 51.3%
Market 1 / 2: 48.7% / 51.3%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: ITF Women - Doubles: W15 Tianjin 2 (China), hard
Todoni C N
Wobker I
All stats and model conclusions
Model vs market
Glicko 1 / 2: 25.2% / 74.8%
Market 1 / 2: 22.5% / 77.5%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Women. Romania. Doubles
Popa M S
Simionescu D-I
All stats and model conclusions
Model vs market
Glicko 1 / 2: 72.6% / 27.4%
Market 1 / 2: 74.3% / 25.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Women. Romania. Doubles
Arakawa H
Lee Ha Eum
All stats and model conclusions
Model vs market
Glicko 1 / 2: 51.1% / 48.9%
Market 1 / 2: 50.0% / 50.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: International World Tennis. Women. Kazakhstan
Kurt I
Arystanbekova A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 37.8% / 62.2%
Market 1 / 2: 36.6% / 63.5%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Women. Kazakhstan
Ghetu G
Breazu V C
All stats and model conclusions
Model vs market
Glicko 1 / 2: 76.1% / 23.9%
Market 1 / 2: 78.6% / 21.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Romania. Doubles
Dencheva R
Vujovic L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 58.8% / 41.2%
Market 1 / 2: 58.7% / 41.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: ITF Women - Singles: W75 Kursumlijska Banja 2 (Serbia), clay
Chepelev A
Haita S H
All stats and model conclusions
Model vs market
Glicko 1 / 2: 43.9% / 56.1%
Market 1 / 2: 43.1% / 56.9%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: ITF Men - Singles: M25 Kursumlijska Banja 3 (Serbia), clay
Roura Llaverias R
Siskova A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 27.0% / 73.0%
Market 1 / 2: 24.3% / 75.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Women - Singles: W50 Hamburg (Germany), clay
Nagy A / Steur J L S
Maduzzi G / Turini V
All stats and model conclusions
Model vs market
Glicko 1 / 2: 63.6% / 36.4%
Market 1 / 2: 65.6% / 34.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: International World Tennis. Women. Poland
Nad A./Stoyr Zh. L. S.
Maduzzi G./Turini V.
All stats and model conclusions
Model vs market
Glicko 1 / 2: 63.5% / 36.5%
Market 1 / 2: 65.3% / 34.7%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: ITF Women - Doubles: W35 Bydgoszcz (Poland), clay
Yashina E./Zhiyenbayeva S.
Gomez O'Hayon V./Rus A.
All stats and model conclusions
Model vs market
Glicko 1 / 2: 61.3% / 38.7%
Market 1 / 2: 62.2% / 37.8%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Women - Doubles: W35 Vigo (Spain), hard
Strakhova V / Tikhonova A
Kobori M / Shimizu A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 54.1% / 45.9%
Market 1 / 2: 54.3% / 45.7%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Women - Doubles: W50 Hamburg (Germany), clay
Jankanj V / Radjenovic V
Juhas K / Popovic S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 57.4% / 42.6%
Market 1 / 2: 50.0% / 50.0%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 1 · total 0
Tournament: International World Tennis. Men. Sweden
Verwerft L G
Geerts M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 26.1% / 73.9%
Market 1 / 2: 24.1% / 75.9%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Men - Singles: M25 Koksijde (Belgium), clay
Casanova A / Parizzia N
Hipfl N./Myuller K.
All stats and model conclusions
Model vs market
Glicko 1 / 2: 54.4% / 45.6%
Market 1 / 2: 59.0% / 41.0%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 1 · total 0
Tournament: World Tennis. Men. Switzerland. Doubles
Analytics
Why are PropickAI tennis predictions effective?
Tennis is a sport of individual matchups, so the model considers more than just player ranking. It factors in court surface, form in recent tournaments, head-to-head records, serve and return quality, draw density and possible fatigue. AI tennis predictions help you see where ATP and WTA statistics match the market line and where there is a discrepancy.