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.
Live win probability (market-implied) — how often it wins, not a profit forecast.
Royer V
Martinez P
Pascual Ferra R
Suresh D. (Ind)
Liang En Shuo
Kraus S
Lamchinniah H
Spurling N
Pegula J
Swiatek I
Nakashima B
Tiafoe F
All stats and model conclusions
Model vs market
Glicko 1 / 2: 52.5% / 47.5%
Market 1 / 2: 51.9% / 48.1%
Favourite trap: no
Data completeness: 72%
Match context
Court:Lindner Femili Tennis Senter, Stadium
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP Cincinnati, USA Men Singles
Bondar A
Jacquemot E
All stats and model conclusions
Model vs market
Glicko 1 / 2: 65.3% / 34.7%
Market 1 / 2: 66.0% / 34.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: WTA - Singles: Monterrey (Mexico) - Qualification, Hard
Hurkacz H
Echargui M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 82.8% / 17.2%
Market 1 / 2: 86.0% / 14.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP Challenger Cancun, Mexico Men Singles
Balaji N S / Chandrasekar A
Gonsales S./Kho R.
Joint M
Hinojosa Gomez J
Braund A
Wensley S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 49.8% / 50.2%
Market 1 / 2: 49.9% / 50.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International UTR Pro. Men. Australia
Aguiard E
Jones Scott
All stats and model conclusions
Model vs market
Glicko 1 / 2: 49.7% / 50.3%
Market 1 / 2: 49.8% / 50.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International UTR Pro. Men. Australia
Katz A
Yu Ramey
Santitto J
Dodaj C
All stats and model conclusions
Model vs market
Glicko 1 / 2: 48.5% / 51.5%
Market 1 / 2: 48.2% / 51.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International UTR Pro. Women. Australia
Bejlek S
Gauff C
All stats and model conclusions
Model vs market
Glicko 1 / 2: 25.0% / 75.0%
Market 1 / 2: 22.5% / 77.5%
Favourite trap: no
Data completeness: 72%
Match context
Court:Lindner Femili Tennis Senter, Stadium
Bookmaker coverage: 1×2 7 · total 0
Tournament: International WTA Cincinnati, USA Women Singles
Hoole C
Cham E
All stats and model conclusions
Model vs market
Glicko 1 / 2: - / -
Market 1 / 2: - / -
Favourite trap: no
Data completeness: -
Match context
Bookmaker coverage: 1×2 0 · total 0
Tournament: International UTR Pro. Men. Australia
Mihulka B
Zylberman A
All stats and model conclusions
Model vs market
Glicko 1 / 2: - / -
Market 1 / 2: - / -
Favourite trap: no
Data completeness: -
Match context
Bookmaker coverage: 1×2 0 · total 0
Tournament: International UTR Pro. Women. Australia
Wan I Wen
McPhee K
Liutarevich I / Reyes-Varela M A
Alvarez Valdes L C / Magadan A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 43.1% / 56.9%
Market 1 / 2: - / -
Favourite trap: no
Data completeness: 12%
Match context
Bookmaker coverage: 1×2 0 · total 0
Tournament: ATP Challenger Cancun, Mexico Men Doubles
Baez S
Harris L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 56.7% / 43.3%
Market 1 / 2: 57.8% / 42.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP Challenger Cancun, Mexico Men Singles
Hsu Yu Hsiou
Dellavedova M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 67.1% / 32.9%
Market 1 / 2: 69.7% / 30.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Taiwan
Lomakin G / Tamm K
Ichikawa T / Imamura M
Matsuda R
Chen Meng Yi
All stats and model conclusions
Model vs market
Glicko 1 / 2: 77.4% / 22.6%
Market 1 / 2: 79.8% / 20.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Women. China. Doubles
Isomura K
Fitriadi M R
All stats and model conclusions
Model vs market
Glicko 1 / 2: 46.2% / 53.8%
Market 1 / 2: 46.3% / 53.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. China. Doubles
Lokoli L. (Fra)
Seghetti S. (Ita)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 58.4% / 41.6%
Market 1 / 2: - / -
Favourite trap: no
Data completeness: 12%
Match context
Bookmaker coverage: 1×2 0 · total 0
Tournament: World Tennis. Men. Italy
Sciahbasi M. (Ita)
Miletich I
All stats and model conclusions
Model vs market
Glicko 1 / 2: 40.5% / 59.5%
Market 1 / 2: 38.5% / 61.5%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: ITF Men - Singles: M15 Arad (Romania), Clay
Sorger S
Gundacker J
All stats and model conclusions
Model vs market
Glicko 1 / 2: 60.4% / 39.6%
Market 1 / 2: 83.5% / 16.5%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 1 · total 0
Tournament: ITF Men - Singles: M25 Slovenj Gradec (Slovenia), Clay
Nagy A
Miron T
All stats and model conclusions
Model vs market
Glicko 1 / 2: 50.6% / 49.4%
Market 1 / 2: - / -
Favourite trap: no
Data completeness: 12%
Match context
Bookmaker coverage: 1×2 0 · total 0
Tournament: World Tennis. Women. Romania
Kisimov D
Juhas K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 44.8% / 55.2%
Market 1 / 2: 43.8% / 56.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Sweden
Behrmann T
Mashtakov N
All stats and model conclusions
Model vs market
Glicko 1 / 2: 55.2% / 44.8%
Market 1 / 2: 56.0% / 44.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Austria
Zolotareva R
Encheva L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 64.0% / 36.0%
Market 1 / 2: 65.1% / 34.9%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: ITF Women - Singles: W75 Kursumlijska Banja 3 (Serbia), Clay
Grzegorzewski O / Sadzik J
Januchowski J / Romer K
Borg L
Guttau N
All stats and model conclusions
Model vs market
Glicko 1 / 2: 51.6% / 48.4%
Market 1 / 2: 50.8% / 49.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Sweden. Doubles
Sanchez Jover C
Ritschard A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 39.3% / 60.7%
Market 1 / 2: 37.0% / 63.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: International World Tennis. Men. Spain. 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.