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.
Birrell K
Marcinko P
Navone M
Djokovic N
Gorzny, Sebastian
Collignon R
Michelsen A
Cina, Federico
Lee Carol Young Suh
Boulter K
Bublik A
Volf Dzh. (Ssha)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 67.5% / 32.5%
Market 1 / 2: 68.2% / 31.8%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: ATP - Singles: Open Championship USA (USA), Hard
Bublik A
Wolf J J
All stats and model conclusions
Model vs market
Glicko 1 / 2: 66.9% / 33.1%
Market 1 / 2: 67.4% / 32.6%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: International US Open. Men. Qualifying Wild Card Challenge
Williams V
Kenin S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 16.4% / 83.6%
Market 1 / 2: 15.6% / 84.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: WTA - Singles: Open Championship USA (USA), Hard
Castelnuovo L
Dellavedova M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 31.5% / 68.5%
Market 1 / 2: 31.2% / 68.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard
Simakin I
Yevseyev D
All stats and model conclusions
Model vs market
Glicko 1 / 2: 75.8% / 24.2%
Market 1 / 2: 76.3% / 23.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard
Tomic B
Imamura M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 66.1% / 33.9%
Market 1 / 2: 66.4% / 33.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard
Liu H. (Kit)
Utida K. (Iapo)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 66.2% / 33.8%
Market 1 / 2: 41.7% / 58.3%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 1 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard
Sun F
Vu Tun-Lin (Tvn)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 42.3% / 57.7%
Market 1 / 2: 42.1% / 57.9%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard
Watanuki Y
Pankin, Semen
All stats and model conclusions
Model vs market
Glicko 1 / 2: 68.4% / 31.6%
Market 1 / 2: 68.8% / 31.2%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard
Cui Jie
Trotter J. K. (Iapo)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 54.2% / 45.8%
Market 1 / 2: 54.1% / 45.9%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard
Liu Khani
Utida K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 44.2% / 55.8%
Market 1 / 2: 43.8% / 56.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: International Chzhantszyagan
Palan D
Leong M W K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 47.4% / 52.6%
Market 1 / 2: 47.4% / 52.6%
Favourite trap: no
Data completeness: 29%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China) - Qualification, Hard
Matsuda, Koki
Meng Fanming
All stats and model conclusions
Model vs market
Glicko 1 / 2: 68.4% / 31.6%
Market 1 / 2: 68.8% / 31.2%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China) - Qualification, Hard
Moriya H
Dev S D P
All stats and model conclusions
Model vs market
Glicko 1 / 2: 70.3% / 29.7%
Market 1 / 2: 70.6% / 29.4%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 5 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China) - Qualification, Hard
Sultanov K
Charlton J
All stats and model conclusions
Model vs market
Glicko 1 / 2: 77.5% / 22.5%
Market 1 / 2: 77.9% / 22.1%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China) - Qualification, Hard
Jasika O
Peliwo F
All stats and model conclusions
Model vs market
Glicko 1 / 2: 79.4% / 20.6%
Market 1 / 2: 79.9% / 20.1%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: Challenger Men - Singles: Zhangjiagang (China) - Qualification, Hard
Vales, Amit
Parisca I
All stats and model conclusions
Model vs market
Glicko 1 / 2: 37.0% / 63.0%
Market 1 / 2: 36.6% / 63.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 6 · total 0
Tournament: Challenger Men - Singles: Plovdiv 3 (Bulgaria) - Qualification, Clay
Iannakkone F. (Ita)
Fajta P
All stats and model conclusions
Model vs market
Glicko 1 / 2: 63.6% / 36.4%
Market 1 / 2: 63.8% / 36.3%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: Challenger Men - Singles: Plovdiv 3 (Bulgaria) - Qualification, Clay
Iannaccone F
Fajta P
All stats and model conclusions
Model vs market
Glicko 1 / 2: 62.6% / 37.4%
Market 1 / 2: 62.6% / 37.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: International Plovdiv 3
Bernet, Henry
Napolitano S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 56.9% / 43.1%
Market 1 / 2: 56.6% / 43.4%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: Challenger Men - Singles: Komo (Italy), Clay
Dodig, Matej
Poljicak M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 59.9% / 40.1%
Market 1 / 2: 60.1% / 39.9%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: Challenger Men - Singles: Komo (Italy), Clay
Arnaboldi F
Bondioli, Federico
All stats and model conclusions
Model vs market
Glicko 1 / 2: 33.0% / 67.0%
Market 1 / 2: 32.7% / 67.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: Challenger Men - Singles: Komo (Italy), Clay
Brancaccio R
Ajdukovic D
All stats and model conclusions
Model vs market
Glicko 1 / 2: 62.1% / 37.9%
Market 1 / 2: 62.2% / 37.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: Challenger Men - Singles: Komo (Italy), Clay
Bueno G
Reis da Silva J L
All stats and model conclusions
Model vs market
Glicko 1 / 2: 61.8% / 38.2%
Market 1 / 2: 61.8% / 38.2%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: Challenger Men - Singles: Komo (Italy), Clay
Varillas J P
Kumstat, Jan
All stats and model conclusions
Model vs market
Glicko 1 / 2: 26.7% / 73.3%
Market 1 / 2: 26.3% / 73.7%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 4 · total 0
Tournament: Challenger Men - Singles: Komo (Italy), Clay
Soto M. (Chil)
Feldbausch K
All stats and model conclusions
Model vs market
Glicko 1 / 2: 24.1% / 76.0%
Market 1 / 2: 23.2% / 76.8%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: Challenger Men - Singles: Komo (Italy), Clay
Jianu F C
Squire H
All stats and model conclusions
Model vs market
Glicko 1 / 2: 40.9% / 59.1%
Market 1 / 2: 40.5% / 59.5%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 2 · total 0
Tournament: International Komo
Seyboth Wild T
Krumich M
All stats and model conclusions
Model vs market
Glicko 1 / 2: 55.5% / 44.5%
Market 1 / 2: 55.7% / 44.3%
Favourite trap: no
Data completeness: 39%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: International Komo
Nedic A
Lokoli L. (Fra)
All stats and model conclusions
Model vs market
Glicko 1 / 2: 58.0% / 42.0%
Market 1 / 2: 58.5% / 41.5%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: Challenger Men - Singles: Komo (Italy) - Qualification, Clay
Gombos N
Gulin S
All stats and model conclusions
Model vs market
Glicko 1 / 2: 55.6% / 44.4%
Market 1 / 2: 55.4% / 44.7%
Favourite trap: no
Data completeness: 24%
Match context
Bookmaker coverage: 1×2 3 · total 0
Tournament: Challenger Men - Singles: Komo (Italy) - Qualification, Clay
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.