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.
Li A
Ruzic A
Joint M
Samsonova L
Stephens S
Tauson C
Berrettini M
Wawrinka S
Blockx, Alexander
Barrios Vera M T
Darderi L
Wendelken H
Shang Juncheng
Trungelliti M
Grabher J
Cirstea S
Shang Juncheng
Trungelliti M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 64.6% / 35.4%
Market 1 / 2: 64.9% / 35.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International US Open. Men. Qualifying Wild Card Challenge
Auger-Aliassime F
Hijikata R
All stats and model conclusions
Model vs market
Glicko 1 / 2: 85.3% / 14.7%
Market 1 / 2: 86.2% / 13.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: International US Open. Men. Qualifying Wild Card Challenge
Halys Q
Diaz Acosta F
All stats and model conclusions
Model vs market
Glicko 1 / 2: 72.1% / 27.9%
Market 1 / 2: 72.6% / 27.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: International US Open. Men. Qualifying Wild Card Challenge
Mensik J
Mochizuki S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 85.8% / 14.2%
Market 1 / 2: 86.8% / 13.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: ATP - Singles: Open Championship USA (USA), Hard
Borges N
Tien L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 36.3% / 63.7%
Market 1 / 2: 35.8% / 64.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: ATP - Singles: Open Championship USA (USA), Hard
Burruchaga R A
Khachanov K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 25.0% / 75.0%
Market 1 / 2: 24.2% / 75.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 7 · total 0
Tournament: ATP - Singles: Open Championship USA (USA), Hard
Shelton B
Griekspoor T
All stats and model conclusions
Model vs market
Glicko 1 / 2: 83.1% / 16.9%
Market 1 / 2: 83.8% / 16.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: ATP - Singles: Open Championship USA (USA), Hard
Dimitrov G
Popyrin A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 63.7% / 36.3%
Market 1 / 2: 63.9% / 36.1%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 7 · total 0
Tournament: ATP - Singles: Open Championship USA (USA), Hard
Cocciaretto E
Siniakova K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 38.8% / 61.2%
Market 1 / 2: 38.2% / 61.9%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: WTA - Singles: Open Championship USA (USA), Hard
Swiatek I
Wang Xiyu
All stats and model conclusions
Model vs market
Glicko 1 / 2: 88.2% / 11.8%
Market 1 / 2: 89.0% / 11.0%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: International US Open. Women
Damm M
Tiafo F. (Ssha)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 25.3% / 74.7%
Market 1 / 2: 24.8% / 75.2%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: ATP - Singles: Open Championship USA (USA), Hard
Damm M
Tiafoe F
All stats and model conclusions
Model vs market
Glicko 1 / 2: 24.1% / 75.9%
Market 1 / 2: 23.3% / 76.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International US Open. Men. Qualifying Wild Card Challenge
Osaka N
Zakharova A
All stats and model conclusions
Model vs market
Glicko 1 / 2: 85.4% / 14.6%
Market 1 / 2: 86.4% / 13.6%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: WTA - Singles: Open Championship USA (USA), Hard
Takahata R
Koizumi N
All stats and model conclusions
Model vs market
Glicko 1 / 2: 37.9% / 62.1%
Market 1 / 2: 37.7% / 62.3%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: ITF Men - Singles: M25 Urayasu (Japan), Hard
Mitsui S
Nakagawa S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 81.4% / 18.6%
Market 1 / 2: 82.2% / 17.9%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: ITF Men - Singles: M25 Urayasu (Japan), Hard
Saitoh K
Okabe S. (Iapo)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 90.5% / 9.5%
Market 1 / 2: 91.5% / 8.5%
Favourite trap: no
Data completeness: 18%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: ITF Men - Singles: M25 Urayasu (Japan), Hard
Tanuma R
Kavakhasi Iu. (Iapo)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 58.4% / 41.6%
Market 1 / 2: 59.3% / 40.7%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 1 · total 0
Tournament: ITF Men - Singles: M25 Urayasu (Japan), Hard
Oki Y
Imai S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 27.6% / 72.4%
Market 1 / 2: 27.2% / 72.8%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: ITF Men - Singles: M25 Urayasu (Japan), Hard
Ichikawa T
Roddick J
All stats and model conclusions
Model vs market
Glicko 1 / 2: 43.1% / 56.9%
Market 1 / 2: 42.6% / 57.4%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Men - Singles: M25 Urayasu (Japan), Hard
Ochi M
Tanaka Y
All stats and model conclusions
Model vs market
Glicko 1 / 2: 62.0% / 38.0%
Market 1 / 2: 62.0% / 38.0%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Men - Singles: M25 Urayasu (Japan), Hard
Wang JiaYi
Bai Ch. (Kit)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 24.9% / 75.1%
Market 1 / 2: 23.7% / 76.3%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Women - Singles: W75 Tianjin (China), Hard
Kulikova A
Yao Xinxin
All stats and model conclusions
Model vs market
Glicko 1 / 2: 49.6% / 50.4%
Market 1 / 2: 49.5% / 50.5%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: ITF Women - Singles: W75 Tianjin (China), Hard
Naito Y
Astakhova D
All stats and model conclusions
Model vs market
Glicko 1 / 2: 35.2% / 64.8%
Market 1 / 2: 34.7% / 65.3%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Women - Singles: W75 Tianjin (China), Hard
Yamaguchi Mei
Back Dayeon
All stats and model conclusions
Model vs market
Glicko 1 / 2: 36.6% / 63.4%
Market 1 / 2: 36.4% / 63.6%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: ITF Women - Singles: W75 Tianjin (China), Hard
Hsu Yu Hsiou
Ymer E
All stats and model conclusions
Model vs market
Glicko 1 / 2: 62.5% / 37.5%
Market 1 / 2: 59.7% / 40.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 1 · total 0
Tournament: International Chzhantszyagan
Castelnuovo L
Dellavedova M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 37.2% / 62.8%
Market 1 / 2: 37.1% / 62.9%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard
Simakin I
Yevseyev D
All stats and model conclusions
Model vs market
Glicko 1 / 2: 74.7% / 25.3%
Market 1 / 2: 75.3% / 24.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard
Tomic B
Imamura M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 64.2% / 35.8%
Market 1 / 2: 64.3% / 35.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard
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.