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.
Tenti F. (Arg)
Monzon I
Janicijevic S
Nilsson L
Zolotareva A
Falkowska W
Burillo I
Hietaranta L
Mayo A
Willwerth B
Saraiva dos Santos P A
Martin Andres
Gonzalez Fernandez M
Pacheco Mendez R
Pareja, Julieta
Shymanovich I
Papamichail D
Gorgodze E
Basing M
Deckers A
Virtanen O
Pinnington Jones J
Salkova D
Knutson G A
Skatov T
Dimitrov G
Gaubas V
Cecchinato M
Jacquet K
Dougaz A
Wong C
Neumayer L
Fearnley J
Pavlovic L
Dominguez Alonso J
Milev Y
Fenty A
Chopra K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 66.6% / 33.4%
Market 1 / 2: 68.9% / 31.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP Challenger. Kingston 2. Qualification
Ficovich J P
Tobon M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 49.9% / 50.1%
Market 1 / 2: 49.4% / 50.6%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP Challenger. Kingston 2. Qualification
Marrero Curbelo I
Andrade, Andres
All stats and model conclusions
Model vs market
Glicko 1 / 2: 27.9% / 72.1%
Market 1 / 2: 25.4% / 74.6%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP Challenger. Kingston 2. Qualification
Echeverria J / Montes-de la Torre I
Gray A / Rybakov A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 50.2% / 49.8%
Market 1 / 2: 50.0% / 50.0%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International Rokhempton 2. Pary
Frantzen C / Haase R
Halys Q / Herbert P-H
All stats and model conclusions
Model vs market
Glicko 1 / 2: 47.8% / 52.2%
Market 1 / 2: 46.6% / 53.4%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: International ATP. Uinston-Seylem. Pary
Mayot H
Forbs M. (Ssha)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 78.4% / 21.6%
Market 1 / 2: 80.4% / 19.6%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: Challenger Men - Singles: Kingston 2 (Jamaica), Hard
Passaro F
Gentzsch T
All stats and model conclusions
Model vs market
Glicko 1 / 2: 46.2% / 53.8%
Market 1 / 2: 46.9% / 53.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International US Open. Men. Qualifying Wild Card Challenge
Seyboth Wild T
McDonald M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 42.5% / 57.5%
Market 1 / 2: 40.4% / 59.6%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International US Open. Men. Qualifying Wild Card Challenge
Mikrut L. (Khor)
Basavareddi N
All stats and model conclusions
Model vs market
Glicko 1 / 2: 36.0% / 64.0%
Market 1 / 2: 33.7% / 66.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International US Open. Men. Qualifying Wild Card Challenge
Mochizuki S
Shick B
All stats and model conclusions
Model vs market
Glicko 1 / 2: 58.7% / 41.3%
Market 1 / 2: 59.5% / 40.5%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International US Open. Men. Qualifying Wild Card Challenge
Gea A
Chidekh C
All stats and model conclusions
Model vs market
Glicko 1 / 2: 64.6% / 35.4%
Market 1 / 2: 65.5% / 34.5%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International US Open. Men. Qualifying Wild Card Challenge
Andreescu B
Podrez, Veronika
All stats and model conclusions
Model vs market
Glicko 1 / 2: 69.4% / 30.6%
Market 1 / 2: 72.3% / 27.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International US Open. Women
Penickova K
Dart H
All stats and model conclusions
Model vs market
Glicko 1 / 2: 24.8% / 75.2%
Market 1 / 2: 22.3% / 77.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International US Open. Women
Rus A
Lamens S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 36.3% / 63.7%
Market 1 / 2: 34.9% / 65.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International US Open. Women
Bandecchi S
Hruncakova V
All stats and model conclusions
Model vs market
Glicko 1 / 2: 61.4% / 38.6%
Market 1 / 2: 61.7% / 38.3%
Favourite trap: no
Data completeness: 44%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International US Open. Women
Uchijima M
Havlickova L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 61.4% / 38.6%
Market 1 / 2: 63.0% / 37.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International US Open. Women
Hibino N
Siskova A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 43.5% / 56.5%
Market 1 / 2: 42.9% / 57.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: International US Open. Women
Zidansek T
Maristany Zuleta de Reales G
All stats and model conclusions
Model vs market
Glicko 1 / 2: 57.8% / 42.2%
Market 1 / 2: 59.1% / 40.9%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International US Open. Women
Crawley F
Ovcharenko E
All stats and model conclusions
Model vs market
Glicko 1 / 2: 80.2% / 19.8%
Market 1 / 2: 82.8% / 17.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International WTA 125K. Filadelfiya
Altmaier D
Buse I
All stats and model conclusions
Model vs market
Glicko 1 / 2: 47.3% / 52.7%
Market 1 / 2: 46.3% / 53.7%
Favourite trap: no
Data completeness: 61%
Match context
Court:Veyk Forest Tennis Senter, Vtoroy court
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP. Uinston-Seylem
Van de Zandschulp B
Darderi L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 58.6% / 41.4%
Market 1 / 2: 59.0% / 41.1%
Favourite trap: no
Data completeness: 61%
Match context
Court:Veyk Forest Tennis Senter, Center court
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP. Uinston-Seylem
Hijikata R
Bonzi B
All stats and model conclusions
Model vs market
Glicko 1 / 2: 52.1% / 47.9%
Market 1 / 2: 52.4% / 47.6%
Favourite trap: no
Data completeness: 61%
Match context
Court:Veyk Forest Tennis Senter, Tretiy court
Bookmaker coverage: 1×2 4 · total 0
Tournament: International ATP. Uinston-Seylem
Detiuc A / Khromacheva I
Khodzumi E / Martins I
All stats and model conclusions
Model vs market
Glicko 1 / 2: 66.4% / 33.6%
Market 1 / 2: 69.0% / 31.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International WTA 125K. Filadelfiya. Pary
Monferrer E
Vaskes F. (Uru)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 74.2% / 25.8%
Market 1 / 2: 76.3% / 23.7%
Favourite trap: no
Data completeness: 18%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Men - Singles: M15 Mar Del Plata (Argentina), Clay
Svrcina D
Galarneau A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 62.0% / 38.0%
Market 1 / 2: 62.8% / 37.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: ATP - Singles: Open Championship USA (USA) - Qualification, Hard
Souza M. (Bra)
Ansari K. (Ssha)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 25.3% / 74.7%
Market 1 / 2: 22.3% / 77.7%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: ITF Women - Singles: W35 Barueri (Brazil), Hard
Wells C
Korvin F. (Ssha)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 25.5% / 74.5%
Market 1 / 2: 22.1% / 77.9%
Favourite trap: no
Data completeness: 18%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Men - Singles: M15 Champaign, IL (USA), Hard
Bakonyi D / Jilly A
Peck J. (Kan)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 58.4% / 41.6%
Market 1 / 2: 58.9% / 41.1%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Men - Singles: M15 Champaign, IL (USA), Hard
Pounvit N. (Ssha)
Bakonyi D
All stats and model conclusions
Model vs market
Glicko 1 / 2: 65.7% / 34.3%
Market 1 / 2: 67.0% / 33.0%
Favourite trap: no
Data completeness: 18%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: ITF Men - Singles: M15 Champaign, IL (USA), Hard
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.