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.
Rapagnetta D
Mazza M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 48.0% / 52.0%
Market 1 / 2: 46.7% / 53.3%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Men. Italy. Doubles
Hipfl N./Oradini Dzh.
Beraldo L / Comino L
Katini N / Matta A
Baragiola Mordini T C / Penasa L
Candiotto A
Barrera Aguirre I
All stats and model conclusions
Model vs market
Glicko 1 / 2: 62.4% / 37.6%
Market 1 / 2: 63.4% / 36.6%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Women. Brazil
Sanchez Uribe M J
Bohrer Martins C
All stats and model conclusions
Model vs market
Glicko 1 / 2: 23.1% / 76.9%
Market 1 / 2: 20.1% / 79.9%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Women. Brazil
Laron M
Barros V L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 25.5% / 74.5%
Market 1 / 2: 23.2% / 76.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: International World Tennis. Women. Brazil
Fullana L./Souza M.
Ccuno R / Pereira R
Ait el Bachir W / Van Zonneveld C
De Koning R / Longvil R
Spurling N
Wells C
All stats and model conclusions
Model vs market
Glicko 1 / 2: 55.2% / 44.8%
Market 1 / 2: 54.4% / 45.6%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Men. East Lansing
Gordon E
Lamchinniah H
All stats and model conclusions
Model vs market
Glicko 1 / 2: 32.6% / 67.4%
Market 1 / 2: 30.8% / 69.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Men. East Lansing
Fullerton M
Solheim F K
Baltazor N
Mahjoob C
Maunupau O
Chulak Z
All stats and model conclusions
Model vs market
Glicko 1 / 2: 40.7% / 59.3%
Market 1 / 2: 39.5% / 60.5%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Women. Ist-Lansing
Poling L
Runstrom F
Bluestein C
Lesterhuis A
Akuginova A
Baules A
Barretto I
Syrtveit N
All stats and model conclusions
Model vs market
Glicko 1 / 2: 49.4% / 50.6%
Market 1 / 2: 50.0% / 50.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Women. Ist-Lansing
Klemens Tia
Loureiro M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 32.3% / 67.7%
Market 1 / 2: 29.5% / 70.5%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International UTR Pro. Women. Ist-Lansing
Barbic A / Hopfe F
Gavrielides L / Loosen T
Bolelli S / Vavassori A
Luz O / Matos R
All stats and model conclusions
Model vs market
Glicko 1 / 2: 44.4% / 55.6%
Market 1 / 2: 56.8% / 43.2%
Favourite trap: no
Data completeness: 44%
Match context
Bookmaker coverage: 1×2 1 · total 0
Tournament: ATP Cincinnati, USA Men Doubles
Nys H / Roger-Vasselin E
Doumbia S / Reboul F
All stats and model conclusions
Model vs market
Glicko 1 / 2: 52.9% / 47.1%
Market 1 / 2: 53.4% / 46.6%
Favourite trap: no
Data completeness: 61%
Match context
Court:Lindner Femili Tennis Senter, Tretiy court
Bookmaker coverage: 1×2 4 · total 0
Tournament: International ATP. Doubles. Cincinnati. Hard
De Jong J
Gaston H
All stats and model conclusions
Model vs market
Glicko 1 / 2: 59.3% / 40.7%
Market 1 / 2: 60.8% / 39.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP Challenger Quebec City, Canada Men Singles
Vales V
Photiades P
Zapp L
Saleh A
Bejlek S
Keys M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 36.1% / 63.9%
Market 1 / 2: 34.5% / 65.5%
Favourite trap: no
Data completeness: 61%
Match context
Court:Lindner Femili Tennis Senter, Stadium
Bookmaker coverage: 1×2 5 · total 0
Tournament: WTA Cincinnati, USA Women Singles
Exsted M
Aguilar Cardozo J
All stats and model conclusions
Model vs market
Glicko 1 / 2: 24.9% / 75.1%
Market 1 / 2: 23.1% / 77.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: International World Tennis. Men. Paraguay. Doubles
Villanueva G
Bobo D
All stats and model conclusions
Model vs market
Glicko 1 / 2: 83.7% / 16.3%
Market 1 / 2: 86.8% / 13.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Paraguay. Doubles
Giamichelle S / Vergara del Puerto M A
Frutos Alonso A. A./Nunez Vera A. S.
Jovic I / McNally C
Bouzkova M / Noskova L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 50.6% / 49.4%
Market 1 / 2: 50.3% / 49.7%
Favourite trap: no
Data completeness: 61%
Match context
Court:Lindner Femili Tennis Senter, Grandstend
Bookmaker coverage: 1×2 4 · total 0
Tournament: International WTA. Doubles. Cincinnati. Hard
Wessels L
Marterer M. (Ger)
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.