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.
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
Jones F
Barthel M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 63.3% / 36.7%
Market 1 / 2: 63.6% / 36.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International US Open. Women
Yuan Yue
Avdeeva J
All stats and model conclusions
Model vs market
Glicko 1 / 2: 67.9% / 32.1%
Market 1 / 2: 69.8% / 30.2%
Favourite trap: no
Data completeness: 61%
Match context
Court:Billi Dzhin King Neshional Tennis Senter, Kort "13"
Bookmaker coverage: 1×2 6 · total 0
Tournament: International US Open. Women
Swan K
Stoiana M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 36.7% / 63.3%
Market 1 / 2: 33.9% / 66.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International US Open. Women
Liutova K
Radivojevic L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 72.7% / 27.3%
Market 1 / 2: 73.6% / 26.4%
Favourite trap: no
Data completeness: 61%
Match context
Court:Billi Dzhin King Neshional Tennis Senter, Kort "16"
Bookmaker coverage: 1×2 4 · total 0
Tournament: International US Open. Women
Ku Yeon Woo
Hunter S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 42.5% / 57.5%
Market 1 / 2: 42.3% / 57.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: International US Open. Women
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.