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.
Giotis R./Thurner N.
Paardekooper S./Van Sambeek F.
All stats and model conclusions
Model vs market
Glicko 1 / 2: 22.4% / 77.6%
Market 1 / 2: 19.5% / 80.5%
Favourite trap: no
Data completeness: 18%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: ITF Men - Doubles: M15 Lambermont (Belgium), clay
Krutykh O
Tseng C H
All stats and model conclusions
Model vs market
Glicko 1 / 2: 39.4% / 60.6%
Market 1 / 2: 37.7% / 62.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International ATP Challenger Prague, Czech Republic Men Singles
Jianu F C
Rehberg M H
All stats and model conclusions
Model vs market
Glicko 1 / 2: 34.6% / 65.4%
Market 1 / 2: 33.3% / 66.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International ATP Challenger Prague, Czech Republic Men Singles
Mrva M
Kumstat J
All stats and model conclusions
Model vs market
Glicko 1 / 2: 47.2% / 52.8%
Market 1 / 2: 47.3% / 52.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP Challenger Prague, Czech Republic Men Singles
Gombos N
Papoe R M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 41.7% / 58.3%
Market 1 / 2: 41.4% / 58.6%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International ATP Challenger Prague, Czech Republic Men Singles
Raschdorf C. (Ger)
Iamalapalli (Ind)
Pieri D./Radzhi A.
Breaz A./Todoni C. N.
Marques G
Andaloro F
All stats and model conclusions
Model vs market
Glicko 1 / 2: 51.6% / 48.4%
Market 1 / 2: 50.2% / 49.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Men. Portugal
Barroso Campos A
Tsitsipas Pavlos
All stats and model conclusions
Model vs market
Glicko 1 / 2: 71.3% / 28.7%
Market 1 / 2: 73.5% / 26.5%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Portugal
Sadzik J
Wazny A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 25.8% / 74.2%
Market 1 / 2: 23.0% / 77.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Men. Poland
Marek W
Filar K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 47.2% / 52.8%
Market 1 / 2: 46.2% / 53.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Poland
Torcq B
Wassermann D
All stats and model conclusions
Model vs market
Glicko 1 / 2: 33.4% / 66.6%
Market 1 / 2: 29.9% / 70.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: International World Tennis. Men. Germany. Doubles
De Stefano S
Bulgaru M B
All stats and model conclusions
Model vs market
Glicko 1 / 2: 57.0% / 43.0%
Market 1 / 2: 57.0% / 43.0%
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
Comino L
Basile P
All stats and model conclusions
Model vs market
Glicko 1 / 2: 25.5% / 74.5%
Market 1 / 2: 22.2% / 77.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: World Tennis. Men. Italy
Petkovic M
Giraldi C. (Isp)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 86.1% / 13.9%
Market 1 / 2: 89.1% / 10.9%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: ITF Men - Singles: M25 Ueberlingen (Germany), clay
Beiker B. (Vel)
De Marchi A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 32.6% / 67.4%
Market 1 / 2: 31.6% / 68.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Men. Italy. Doubles
Spiridon D C
Lokoli L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 18.6% / 81.4%
Market 1 / 2: 14.8% / 85.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Men. Italy. Doubles
Rapagnetta D
Mazza M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 47.7% / 52.3%
Market 1 / 2: 46.4% / 53.6%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Men. Italy. Doubles
Planinsek F J
Mokhar V
Bass F / Duncan S
Hands T / Summers M
Planinsek F J
Mohar V. (Sln)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 86.7% / 13.3%
Market 1 / 2: 89.7% / 10.3%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: ITF Men - Singles: M25 Slovenj Gradec (Slovenia), clay
Hatouka Y
Vargas V. (Ekv)
Gomez O'Hayon V
Kardava Z
All stats and model conclusions
Model vs market
Glicko 1 / 2: 36.1% / 63.9%
Market 1 / 2: 34.1% / 66.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Women. Spain. Doubles
Mrva, Maxim
Kumstat, Jan
All stats and model conclusions
Model vs market
Glicko 1 / 2: 43.3% / 56.7%
Market 1 / 2: 43.6% / 56.4%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: ATP Challenger Prague, Czech Republic Men Singles
Arribage T / Olivetti A
Arevalo M / Pavic M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 29.8% / 70.2%
Market 1 / 2: 28.6% / 71.4%
Favourite trap: no
Data completeness: 29%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ATP Cincinnati, USA Men Doubles
Heliovaara H / Patten H
Nys H / Roger-Vasselin E
All stats and model conclusions
Model vs market
Glicko 1 / 2: 58.6% / 41.4%
Market 1 / 2: 64.1% / 35.9%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 1 · total 0
Tournament: ATP Cincinnati, USA Men Doubles
Ram R / Salisbury J
Frantzen C / Haase R
All stats and model conclusions
Model vs market
Glicko 1 / 2: 58.3% / 41.7%
Market 1 / 2: 59.2% / 40.8%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ATP Cincinnati, USA Men Doubles
Sanchez Jover C
Lopes Morilo I. (Isp)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 68.7% / 31.3%
Market 1 / 2: 70.1% / 29.9%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Men - Singles: M25 Santander (Spain), clay
Fita Juan S
Juan Mano A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 38.9% / 61.1%
Market 1 / 2: 38.5% / 61.5%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Spain. Doubles
Lopez Montagud C
Perez Contri S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 53.2% / 46.8%
Market 1 / 2: 52.2% / 47.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · 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.