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.
Hipfl N
Reitano S. (Ita)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 70.8% / 29.2%
Market 1 / 2: 72.3% / 27.7%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International World Tennis. Men. Italy. Doubles
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
Darderi L / Etcheverry T M
Granollers M / Zeballos H
All stats and model conclusions
Model vs market
Glicko 1 / 2: 28.0% / 72.0%
Market 1 / 2: 24.7% / 75.3%
Favourite trap: no
Data completeness: 61%
Match context
Court:Lindner Femili Tennis Senter, Grandstend
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP. Doubles. Cincinnati. Hard
Frantzen C / Haase R
Arribage T / Olivetti A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 39.5% / 60.5%
Market 1 / 2: 38.6% / 61.4%
Favourite trap: no
Data completeness: 61%
Match context
Court:Lindner Femili Tennis Senter, Tretiy court
Bookmaker coverage: 1×2 6 · total 0
Tournament: International ATP. Doubles. Cincinnati. Hard
Nys H / Roger-Vasselin E
Doumbia S / Reboul F
All stats and model conclusions
Model vs market
Glicko 1 / 2: 48.6% / 51.4%
Market 1 / 2: - / -
Favourite trap: no
Data completeness: 12%
Match context
Bookmaker coverage: 1×2 0 · total 0
Tournament: ATP Cincinnati, USA Men Doubles
Fullana L
Souza M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 74.6% / 25.4%
Market 1 / 2: 76.3% / 23.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: International World Tennis. Women. Brazil
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
Defalco J / Garcia J
Bensobas-Fernandes O / Koskel A-A
Magimai K
Kandhai N
Battle L
Corwin O
All stats and model conclusions
Model vs market
Glicko 1 / 2: 66.7% / 33.3%
Market 1 / 2: 67.9% / 32.1%
Favourite trap: no
Data completeness: 33%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International UTR Pro. Men. East Lansing
Spurling N
Wells C
All stats and model conclusions
Model vs market
Glicko 1 / 2: 55.7% / 44.3%
Market 1 / 2: 55.0% / 45.0%
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
Weir L
Nishino N
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
Giustino L
Hassan B
All stats and model conclusions
Model vs market
Glicko 1 / 2: 55.9% / 44.1%
Market 1 / 2: 56.7% / 43.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International ATP Challenger Sion, Switzerland Men Singles
Valdes-Guson Kh-P
Pinzon F
All stats and model conclusions
Model vs market
Glicko 1 / 2: 31.3% / 68.7%
Market 1 / 2: 29.1% / 71.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International UTR Pro. Men. Neshvill
Jacques H
Maioral A
Teramo D-K
Vasilescu L
Grubor A. (Kan)
Bonelli E
All stats and model conclusions
Model vs market
Glicko 1 / 2: 49.1% / 50.9%
Market 1 / 2: 48.7% / 51.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: World Tennis. Women. Switzerland
Sroka M / Zgolia B
Grzegorzewski O / Sadzik J
Sziedat F
Lim J
All stats and model conclusions
Model vs market
Glicko 1 / 2: 23.4% / 76.6%
Market 1 / 2: 19.9% / 80.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Women. Switzerland. Qualification
Stricker D
Compagnucci T
All stats and model conclusions
Model vs market
Glicko 1 / 2: 71.4% / 28.6%
Market 1 / 2: 73.1% / 26.9%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ATP Challenger Sion, Switzerland Men Singles
Steur J L S
Brockmann T J
All stats and model conclusions
Model vs market
Glicko 1 / 2: 56.9% / 43.1%
Market 1 / 2: 56.7% / 43.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Women. Germany. Doubles
Bonzi B
Van Assche L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 46.0% / 54.0%
Market 1 / 2: 45.7% / 54.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: International ATP Challenger Quebec City, Canada Men Singles
Hsieh Su-Wei / Ostapenko J
Kempen M / Panova A
Senn N
Bieldiugin T
All stats and model conclusions
Model vs market
Glicko 1 / 2: 39.0% / 61.0%
Market 1 / 2: 38.1% / 62.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International World Tennis. Men. Germany. Doubles
Barbic A / Hopfe F
Gavrielides L / Loosen T
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.