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.
Spenser O
Weir L
Chulak Z
Syrtveit N
Nagel A
Mazur D. (Ger)
Gaston H
Van Assche L
Oradini G
Weis A
Gorzny S
Polmans M. (Avs)
Heck H
Rottgering M
Nys H / Roger-Vasselin E
Luz O / Matos R
Jacques H
Ushizima H H
All stats and model conclusions
Model vs market
Glicko 1 / 2: 38.9% / 61.1%
Market 1 / 2: 38.2% / 61.8%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International UTR Pro. Men. Neshvill
Vassar A
Vasilescu L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 60.6% / 39.4%
Market 1 / 2: 60.8% / 39.2%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Men. Neshvill
Pascual Ferra R
Suresh D. (Ind)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 36.4% / 63.6%
Market 1 / 2: 35.5% / 64.5%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: ATP - Singles: Uinston-Salem (USA) - Qualification, Hard
Shelbayh A
Seggerman R
All stats and model conclusions
Model vs market
Glicko 1 / 2: 68.4% / 31.6%
Market 1 / 2: 69.3% / 30.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: International ATP. Uinston-Seylem
Blackford E
Ivanova E
All stats and model conclusions
Model vs market
Glicko 1 / 2: 35.0% / 65.0%
Market 1 / 2: 34.2% / 65.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International UTR Pro. Women. Ist-Lansing
Shaya P
Baltazor N
All stats and model conclusions
Model vs market
Glicko 1 / 2: 50.9% / 49.1%
Market 1 / 2: 50.0% / 50.0%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Men. East Lansing
Corwin F
Corwin O
Nelson T
Gordon E
All stats and model conclusions
Model vs market
Glicko 1 / 2: 56.4% / 43.6%
Market 1 / 2: 57.5% / 42.5%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Men. East Lansing
Lamchinniah H
Spurling N
All stats and model conclusions
Model vs market
Glicko 1 / 2: 44.3% / 55.7%
Market 1 / 2: 43.0% / 57.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Men. East Lansing
Hipfl N./Oradini Dzh.
Bosio G / Martin Manzano J C
All stats and model conclusions
Model vs market
Glicko 1 / 2: 51.2% / 48.8%
Market 1 / 2: 50.0% / 50.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Men. Italy. Doubles
Pegula J
Swiatek I
All stats and model conclusions
Model vs market
Glicko 1 / 2: 33.5% / 66.5%
Market 1 / 2: 32.0% / 68.0%
Favourite trap: no
Data completeness: 72%
Match context
Court:Lindner Femili Tennis Senter. Stadium
Bookmaker coverage: 1×2 5 · total 0
Tournament: International WTA Cincinnati, USA Women Singles
Bejlek S
Gauff C
All stats and model conclusions
Model vs market
Glicko 1 / 2: 26.2% / 73.8%
Market 1 / 2: 23.8% / 76.2%
Favourite trap: no
Data completeness: 61%
Match context
Court:Lindner Femili Tennis Senter, Stadium
Bookmaker coverage: 1×2 6 · total 0
Tournament: International WTA Cincinnati, USA Women Singles
Villanueva G
Aguilar Cardozo J
All stats and model conclusions
Model vs market
Glicko 1 / 2: 43.6% / 56.4%
Market 1 / 2: 43.2% / 56.8%
Favourite trap: no
Data completeness: 44%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Paraguay. Doubles
Sakellaridis S
Daniel T
All stats and model conclusions
Model vs market
Glicko 1 / 2: 47.6% / 52.4%
Market 1 / 2: 47.8% / 52.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP Challenger Quebec City, Canada Men Singles
Werner C
Vidmanova D
All stats and model conclusions
Model vs market
Glicko 1 / 2: 19.4% / 80.6%
Market 1 / 2: 17.0% / 83.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: WTA - Singles: Monterrey (Mexico) - Qualification, Hard
Jeanjean L
Rakhimova K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 38.2% / 61.8%
Market 1 / 2: 36.6% / 63.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: WTA - Singles: Monterrey (Mexico) - Qualification, Hard
Udvardy P
Arango E
All stats and model conclusions
Model vs market
Glicko 1 / 2: 45.2% / 54.8%
Market 1 / 2: 43.6% / 56.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: WTA - Singles: Monterrey (Mexico) - Qualification, Hard
Liang En Shuo
Kraus S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 33.6% / 66.4%
Market 1 / 2: 32.6% / 67.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: WTA - Singles: Monterrey (Mexico) - Qualification, Hard
Tararudee L
Timofeeva M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 66.1% / 33.9%
Market 1 / 2: 66.2% / 33.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: WTA - Singles: Monterrey (Mexico) - Qualification, Hard
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
Rodriguez V
Putintseva Y
All stats and model conclusions
Model vs market
Glicko 1 / 2: 11.4% / 88.6%
Market 1 / 2: 7.3% / 92.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: International WTA. Monterrey
Joint M
Hinojosa Gomez J
Royer V
Martinez P
All stats and model conclusions
Model vs market
Glicko 1 / 2: 66.7% / 33.3%
Market 1 / 2: 68.3% / 31.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP Challenger. Kingston. Qualification
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
Hurkacz H
Echargui M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 82.3% / 17.7%
Market 1 / 2: 85.3% / 14.7%
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.
Braund A
Wensley S
Aguiard E
Jones Scott
Katz A
Yu Ramey
Santitto J
Dodaj C
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.