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.

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Shown 400

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Leagues 47

Bookmakers 7

LIVE now In-play matches

Live win probability (market-implied) — how often it wins, not a profit forecast.

Tennis International World Tennis. Women. South Korea ● LIVE146'

Lin Fang An

Kawagishi N

Live pick 1 Lin Fang An 77%

Details

Tennis International World Tennis. Men. China. Doubles ● LIVE116'

Yamamoto N

Chzhou Sin

Live pick 1 Yamamoto N 53%

Details

Tennis ITF Men - Singles: M15 Bali 3 (Indonesia), Hard ● LIVE26'

Patton T

Rathi A

Live pick 1 Patton T 58%

Details

Tennis ITF Men - Singles: M15 Bali 3 (Indonesia), Hard ● LIVE26'

Ryan Ziegann S

Ahren Moonga E. (Shve)

Live pick 1 Ryan Ziegann S 90%

Details

Tennis ITF Men - Singles: M15 Nonthaburi (Thailand), Hard ● LIVE85'

O'Connell B. (Avs)

Suresh K

Live pick 1 O'Connell B. (Avs) 76%

Details

Tennis International World Tennis. Men. Japan ● LIVE66'

Oki Y

Imai S

Live pick 1 Oki Y 66%

Details

Tennis International World Tennis. Men. Japan ● LIVE47'

Ochi M

Tanaka Y

Live pick 1 Ochi M 86%

Details

Tennis ITF Men - Singles: M25 Urayasu (Japan), Hard ● LIVE80'

Ichikawa T

Roddick J

Live pick 1 Ichikawa T 87%

Details

Tennis ITF Women - Singles: W75 Tianjin (China), Hard ● LIVE47'

Kuramochi M. (Iapo)

Inoue H

Live pick 1 Kuramochi M. (Iapo) 90%

Details

Tennis International Chzhantszyagan ● LIVE

Matsuda K

Delaney Jake

Live pick 2 Delaney Jake 71%

Details

Tennis WTA - Singles: Open Championship USA (USA), Hard ● LIVE160'

Osaka N

Zakharova A

Live pick 1 Osaka N 93%

Details

Tennis International World Tennis. Men. China. Doubles ● LIVE105'

Satara H

Nakajima K

Live pick 1 Satara H 92%

Details

Tennis International World Tennis. Men. China. Doubles ● LIVE165'

Vikeri L

Lin Hao-Yu

Live pick 2 Lin Hao-Yu 78%

Details

Tennis International Chzhantszyagan ● LIVE75'

Hsu Yu Hsiou

Ymer E

Live pick 1 Hsu Yu Hsiou 79%

Details

Challenger Men - Singles: Zhangjiagang (China), Hard Tennis

Tennis

Challenger Men - Singles: Zhangjiagang (China), Hard 01.09.2026 04:30 UTC NEUTRAL · MODEL CALCULATION

Tseng C H

Zhang T. (Kit)

🎯 PropickAI prediction

model probability · no colour signal

1 Tseng C H 78%

1 78% · 2 22%

🎯 Safe pick Match winner — Tseng C H ~87% strong

1.21 4.20

✓ Prematch ready 📊 extended stats line ready 3 bookmakers 3 markets updated 01.09 04:29 UTC

line available on the match card 3 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 76.5% / 23.5%

Market 1 / 2: 77.6% / 22.4%

Favourite trap: no

Data completeness: 24%

Match context

Bookmaker coverage: 1×2 3 · total 0

Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard

Tennis

Challenger Men - Singles: Zhangjiagang (China), Hard 01.09.2026 06:00 UTC NEUTRAL · MODEL CALCULATION

Aguiard E

Matsuoka, Hayato

🎯 PropickAI prediction

model probability · no colour signal

2 Matsuoka, Hayato 66%

1 34% · 2 66%

🎯 Safe pick Match winner — Matsuoka, Hayato ~79% confident

2.80 1.42

✓ Prematch ready 📊 extended stats line ready 3 bookmakers 3 markets updated 01.09 05:51 UTC

line available on the match card 3 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 34.4% / 65.6%

Market 1 / 2: 33.7% / 66.4%

Favourite trap: no

Data completeness: 24%

Match context

Bookmaker coverage: 1×2 3 · total 0

Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard

Tennis

Challenger Men - Singles: Zhangjiagang (China), Hard 01.09.2026 06:00 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Jasika O

Santillan A

🎯 PropickAI prediction

model probability · no colour signal

1 Jasika O 59%

1 59% · 2 41%

1.60 2.35

✓ Prematch ready 📊 extended stats line ready 4 bookmakers 5 markets updated 01.09 06:20 UTC

line available on the match card 4 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 59.1% / 40.9%

Market 1 / 2: 58.9% / 41.1%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 4 · total 0

Tournament: Challenger Men - Singles: Zhangjiagang (China), Hard

ITF Men - Doubles: M25 Urayasu (Japan), Hard Tennis

Tennis

ITF Men - Doubles: M25 Urayasu (Japan), Hard 01.09.2026 04:30 UTC NEUTRAL · MODEL CALCULATION

Kusuhara Y./Nakagawa S.

Inui Y./Ogura K.

🎯 PropickAI prediction

model probability · no colour signal

1 Kusuhara Y./Nakagawa S. 72%

1 72% · 2 28%

🎯 Safe pick Match winner — Kusuhara Y./Nakagawa S. ~79% confident

1.34 3.50

✓ Prematch ready line ready 2 bookmakers 1 market updated 01.09 04:15 UTC

line available on the match card 2 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 71.0% / 29.0%

Market 1 / 2: 71.3% / 28.7%

Favourite trap: no

Data completeness: 18%

Match context

Bookmaker coverage: 1×2 2 · total 0

Tournament: ITF Men - Doubles: M25 Urayasu (Japan), Hard

Tennis

ITF Men - Doubles: M25 Urayasu (Japan), Hard 01.09.2026 04:30 UTC NEUTRAL · MODEL CALCULATION

Vans Dzh./Vans Dzh.

Saito K./Tanuma R.

🎯 PropickAI prediction

model probability · no colour signal

1 Vans Dzh./Vans Dzh. 58%

1 58% · 2 42%

1.60 2.20

✓ Prematch ready line ready 1 bookmaker 1 market updated 01.09 04:15 UTC

line available on the match card 1 bookmaker Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 45.4% / 54.6%

Market 1 / 2: 57.9% / 42.1%

Favourite trap: no

Data completeness: 18%

Match context

Bookmaker coverage: 1×2 1 · total 0

Tournament: ITF Men - Doubles: M25 Urayasu (Japan), Hard

ITF Men - Singles: M15 Nonthaburi (Thailand), Hard Tennis

Tennis

ITF Men - Singles: M15 Nonthaburi (Thailand), Hard 01.09.2026 04:30 UTC NEUTRAL · MODEL CALCULATION

Van Herzeele J

Sureshkumar M

🎯 PropickAI prediction

model probability · no colour signal

2 Sureshkumar M 58%

1 42% · 2 58%

2.25 1.60

✓ Prematch ready 📊 extended stats line ready 5 bookmakers 3 markets updated 01.09 04:29 UTC

line available on the match card 5 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 42.4% / 57.6%

Market 1 / 2: 41.8% / 58.2%

Favourite trap: no

Data completeness: 24%

Match context

Bookmaker coverage: 1×2 5 · total 0

Tournament: ITF Men - Singles: M15 Nonthaburi (Thailand), Hard

ITF Men - Doubles: M15 Nonthaburi (Thailand), Hard Tennis

Tennis

ITF Men - Doubles: M15 Nonthaburi (Thailand), Hard 01.09.2026 04:30 UTC NEUTRAL · MODEL CALCULATION

Dong Ch./Hasson J.

Blando M./Hashimoto H.

🎯 PropickAI prediction

model probability · no colour signal

2 Blando M./Hashimoto H. 62%

1 38% · 2 62%

2.40 1.50

✓ Prematch ready line ready 1 bookmaker 1 market updated 01.09 04:15 UTC

line available on the match card 1 bookmaker Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 47.1% / 52.9%

Market 1 / 2: 38.5% / 61.5%

Favourite trap: no

Data completeness: 18%

Match context

Bookmaker coverage: 1×2 1 · total 0

Tournament: ITF Men - Doubles: M15 Nonthaburi (Thailand), Hard

Tennis

ITF Men - Doubles: M15 Nonthaburi (Thailand), Hard 01.09.2026 05:30 UTC NEUTRAL · MODEL CALCULATION

Arcon A./Bertran P.

Sharoenfon Iu./Srisen T.

🎯 PropickAI prediction

model probability · no colour signal

1 Arcon A./Bertran P. 79%

1 79% · 2 21%

🎯 Safe pick Match winner — Arcon A./Bertran P. ~87% strong

1.17 4.50

✓ Prematch ready line ready 2 bookmakers 1 market updated 01.09 05:15 UTC

line available on the match card 2 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 78.5% / 21.5%

Market 1 / 2: 79.3% / 20.7%

Favourite trap: no

Data completeness: 18%

Match context

Bookmaker coverage: 1×2 2 · total 0

Tournament: ITF Men - Doubles: M15 Nonthaburi (Thailand), Hard

Tennis

ITF Men - Doubles: M15 Nonthaburi (Thailand), Hard 01.09.2026 06:30 UTC NEUTRAL · MODEL CALCULATION

Masabayashi T./Sumizava D.

Congcar C./Koaykul K.

🎯 PropickAI prediction

model probability · no colour signal

1 Masabayashi T./Sumizava D. 74%

1 74% · 2 26%

🎯 Safe pick Match winner — Masabayashi T./Sumizava D. ~79% confident

1.24 3.61

✓ Prematch ready line ready 2 bookmakers 1 market updated 01.09 06:15 UTC

line available on the match card 2 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 74.0% / 26.0%

Market 1 / 2: 74.6% / 25.4%

Favourite trap: no

Data completeness: 18%

Match context

Bookmaker coverage: 1×2 2 · total 0

Tournament: ITF Men - Doubles: M15 Nonthaburi (Thailand), Hard

International Chzhantszyagan Tennis

Tennis

International Chzhantszyagan 01.09.2026 04:30 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Bar Biryukov P

Leong M W K

🎯 PropickAI prediction

model probability · no colour signal

1 Bar Biryukov P 57%

1 57% · 2 43%

1.68 2.20

✓ Prematch ready 📊 extended stats line ready 4 bookmakers 5 markets updated 01.09 06:14 UTC

line available on the match card 4 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 57.1% / 42.9%

Market 1 / 2: 57.3% / 42.7%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 4 · total 0

Tournament: International Chzhantszyagan

Tennis

International Chzhantszyagan 01.09.2026 04:30 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Samrej K

Moriya H

🎯 PropickAI prediction

2 Moriya H 52%

1 48% · 2 52%

2.02 1.88

✓ Prematch ready 📊 extended stats line ready 6 bookmakers 5 markets updated 01.09 06:18 UTC

line available on the match card 6 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 47.9% / 52.1%

Market 1 / 2: 47.4% / 52.6%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 6 · total 0

Tournament: International Chzhantszyagan

Tennis

International Chzhantszyagan 01.09.2026 06:00 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Ivashka I

Zhou Yi

🎯 PropickAI prediction

model probability · no colour signal

1 Ivashka I 55%

1 55% · 2 45%

1.67 2.07

✓ Prematch ready line ready 1 bookmaker 5 markets updated 01.09 06:14 UTC

line available on the match card 1 bookmaker Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 58.3% / 41.7%

Market 1 / 2: 55.4% / 44.7%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 1 · total 0

Tournament: International Chzhantszyagan

Tennis

International Chzhantszyagan 01.09.2026 06:00 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Sultanov K

Fomin S

🎯 PropickAI prediction

model probability · no colour signal

1 Sultanov K 58%

1 58% · 2 42%

1.61 2.20

✓ Prematch ready 📊 extended stats line ready 4 bookmakers 5 markets updated 01.09 05:45 UTC

line available on the match card 4 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 57.5% / 42.5%

Market 1 / 2: 57.8% / 42.2%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 4 · total 0

Tournament: International Chzhantszyagan

ITF Women - Doubles: W75 Tianjin (China), Hard Tennis

Tennis

ITF Women - Doubles: W75 Tianjin (China), Hard 01.09.2026 05:00 UTC NEUTRAL · MODEL CALCULATION

Li Ch./Shi H.

Lan X./Sun Y.

🎯 PropickAI prediction

model probability · no colour signal

1 Li Ch./Shi H. 84%

1 84% · 2 16%

🎯 Safe pick Match winner — Li Ch./Shi H. ~87% strong

1.12 5.90

✓ Prematch ready 📊 extended stats line ready 3 bookmakers 1 market updated 01.09 04:54 UTC

line available on the match card 3 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 82.9% / 17.1%

Market 1 / 2: 83.8% / 16.2%

Favourite trap: no

Data completeness: 18%

Match context

Bookmaker coverage: 1×2 3 · total 0

Tournament: ITF Women - Doubles: W75 Tianjin (China), Hard

Tennis

ITF Women - Doubles: W75 Tianjin (China), Hard 01.09.2026 05:00 UTC NEUTRAL · MODEL CALCULATION

Kobori M / Shimizu A

Li E./Sato Kh.

🎯 PropickAI prediction

model probability · no colour signal

1 Kobori M / Shimizu A 76%

1 76% · 2 24%

🎯 Safe pick Match winner — Kobori M / Shimizu A ~87% strong

1.23 3.90

✓ Prematch ready line ready 3 bookmakers 1 market updated 01.09 04:54 UTC

line available on the match card 3 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 75.8% / 24.2%

Market 1 / 2: 76.3% / 23.8%

Favourite trap: no

Data completeness: 18%

Match context

Bookmaker coverage: 1×2 3 · total 0

Tournament: ITF Women - Doubles: W75 Tianjin (China), Hard

Tennis

ITF Women - Doubles: W75 Tianjin (China), Hard 01.09.2026 06:30 UTC NEUTRAL · MODEL CALCULATION

Hou Y./Van M.

Plipuek P./Simidzu E.

🎯 PropickAI prediction

model probability · no colour signal

2 Plipuek P./Simidzu E. 68%

1 32% · 2 68%

🎯 Safe pick Match winner — Plipuek P./Simidzu E. ~79% confident

2.90 1.35

✓ Prematch ready line ready 2 bookmakers 1 market updated 01.09 06:15 UTC

line available on the match card 2 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 32.8% / 67.2%

Market 1 / 2: 32.2% / 67.9%

Favourite trap: no

Data completeness: 18%

Match context

Bookmaker coverage: 1×2 2 · total 0

Tournament: ITF Women - Doubles: W75 Tianjin (China), Hard

ITF Men - Singles: M15 Bali 3 (Indonesia), Hard Tennis

Tennis

ITF Men - Singles: M15 Bali 3 (Indonesia), Hard 01.09.2026 05:30 UTC NEUTRAL · MODEL CALCULATION

Ellis B

Falck R. (Nzl)

🎯 PropickAI prediction

model probability · no colour signal

1 Ellis B 78%

1 78% · 2 22%

🎯 Safe pick Match winner — Ellis B ~87% strong

1.24 4.30

✓ Prematch ready 📊 extended stats line ready 5 bookmakers 3 markets updated 01.09 05:29 UTC

line available on the match card 5 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 77.1% / 22.9%

Market 1 / 2: 77.7% / 22.3%

Favourite trap: no

Data completeness: 24%

Match context

Bookmaker coverage: 1×2 5 · total 0

Tournament: ITF Men - Singles: M15 Bali 3 (Indonesia), Hard

ITF Men - Doubles: M15 Bali 3 (Indonesia), Hard Tennis

Tennis

ITF Men - Doubles: M15 Bali 3 (Indonesia), Hard 01.09.2026 05:30 UTC NEUTRAL · MODEL CALCULATION

Lin N. H./Wang K.

Nakamura R./Susanto A.

🎯 PropickAI prediction

model probability · no colour signal

1 Lin N. H./Wang K. 62%

1 62% · 2 38%

1.50 2.40

✓ Prematch ready line ready 2 bookmakers 1 market updated 01.09 05:15 UTC

line available on the match card 2 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 61.3% / 38.7%

Market 1 / 2: 61.5% / 38.5%

Favourite trap: no

Data completeness: 18%

Match context

Bookmaker coverage: 1×2 2 · total 0

Tournament: ITF Men - Doubles: M15 Bali 3 (Indonesia), Hard

ITF Men - Doubles: M15 Wuning 7 (China), Hard Tennis

Tennis

ITF Men - Doubles: M15 Wuning 7 (China), Hard 01.09.2026 06:00 UTC NEUTRAL · MODEL CALCULATION

Jones Alex / Jones Miles

Pan W./Xiao L.

🎯 PropickAI prediction

model probability · no colour signal

1 Jones Alex / Jones Miles 83%

1 83% · 2 17%

🎯 Safe pick Match winner — Jones Alex / Jones Miles ~87% strong

1.15 5.80

✓ Prematch ready line ready 3 bookmakers 1 market updated 01.09 05:45 UTC

line available on the match card 3 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 81.9% / 18.1%

Market 1 / 2: 82.5% / 17.5%

Favourite trap: no

Data completeness: 24%

Match context

Bookmaker coverage: 1×2 3 · total 0

Tournament: ITF Men - Doubles: M15 Wuning 7 (China), Hard

Tennis

ITF Men - Doubles: M15 Wuning 7 (China), Hard 01.09.2026 06:00 UTC NEUTRAL · MODEL CALCULATION

Talic Z./Vickery L.

Liu Siu/Yang X.

🎯 PropickAI prediction

model probability · no colour signal

2 Liu Siu/Yang X. 60%

1 40% · 2 60%

2.30 1.56

✓ Prematch ready line ready 3 bookmakers 1 market updated 01.09 05:45 UTC

line available on the match card 3 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 40.7% / 59.3%

Market 1 / 2: 40.7% / 59.3%

Favourite trap: no

Data completeness: 24%

Match context

Bookmaker coverage: 1×2 3 · total 0

Tournament: ITF Men - Doubles: M15 Wuning 7 (China), Hard

Tennis

ITF Men - Doubles: M15 Wuning 7 (China), Hard 01.09.2026 06:00 UTC NEUTRAL · MODEL CALCULATION

Jin Yuquan / Sun Qian

Lu C./Yang Z.

🎯 PropickAI prediction

model probability · no colour signal

1 Jin Yuquan / Sun Qian 73%

1 73% · 2 27%

🎯 Safe pick Match winner — Jin Yuquan / Sun Qian ~79% confident

1.82 4.90

✓ Prematch ready line ready 3 bookmakers 3 markets updated 01.09 05:45 UTC

line available on the match card 3 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 70.9% / 29.1%

Market 1 / 2: 71.3% / 28.7%

Favourite trap: no

Data completeness: 18%

Match context

Bookmaker coverage: 1×2 3 · total 0

Tournament: ITF Men - Doubles: M15 Wuning 7 (China), Hard

Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay Tennis

Tennis

Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay 01.09.2026 07:00 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Siniakov D

Kravchenko G

🎯 PropickAI prediction

1 Siniakov D 53%

1 53% · 2 47%

1.80 2.04

✓ Prematch ready 📊 extended stats line ready 6 bookmakers 5 markets updated 01.09 06:15 UTC

line available on the match card 6 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 52.7% / 47.3%

Market 1 / 2: 52.6% / 47.4%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 6 · total 0

Tournament: Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay

Tennis

Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay 01.09.2026 07:00 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Faurel, Thomas

Irwanto J

🎯 PropickAI prediction

model probability · no colour signal

1 Faurel, Thomas 71%

1 71% · 2 29%

🎯 Safe pick Match winner — Faurel, Thomas ~79% confident

1.30 3.20

✓ Prematch ready line ready 1 bookmaker 5 markets updated 01.09 05:59 UTC

line available on the match card 1 bookmaker Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 45.5% / 54.5%

Market 1 / 2: 71.1% / 28.9%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 1 · total 0

Tournament: Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay

Tennis

Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay 01.09.2026 07:00 UTC NEUTRAL · MODEL CALCULATION

Ovcharenko, Oleksandr

Strombachs R

🎯 PropickAI prediction

model probability · no colour signal

1 Ovcharenko, Oleksandr 69%

1 69% · 2 31%

🎯 Safe pick Match winner — Ovcharenko, Oleksandr ~79% confident

1.37 3.10

✓ Prematch ready 📊 extended stats line ready 3 bookmakers 3 markets updated 01.09 06:15 UTC

line available on the match card 3 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 69.3% / 30.7%

Market 1 / 2: 69.8% / 30.2%

Favourite trap: no

Data completeness: 24%

Match context

Bookmaker coverage: 1×2 3 · total 0

Tournament: Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay

Tennis

Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay 01.09.2026 08:00 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Nesterov, Pyotr

Milev, Yanaki

🎯 PropickAI prediction

model probability · no colour signal

1 Nesterov, Pyotr 82%

1 82% · 2 18%

🎯 Safe pick Match winner — Nesterov, Pyotr ~87% strong

1.22 5.60

✓ Prematch ready 📊 extended stats line ready 6 bookmakers 3 markets updated 01.09 06:15 UTC

line available on the match card 6 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 76.2% / 23.8%

Market 1 / 2: 76.6% / 23.4%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 6 · total 0

Tournament: Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay

Tennis

Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay 01.09.2026 08:00 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Brunclik P

Sorger S

🎯 PropickAI prediction

2 Sorger S 53%

1 47% · 2 53%

2.06 1.85

✓ Prematch ready 📊 extended stats line ready 4 bookmakers 5 markets updated 01.09 06:15 UTC

line available on the match card 4 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 45.7% / 54.3%

Market 1 / 2: 45.7% / 54.4%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 4 · total 0

Tournament: Challenger Men - Singles: Plovdiv 3 (Bulgaria), Clay

Challenger Men - Singles: Komo (Italy), Clay Tennis

Tennis

Challenger Men - Singles: Komo (Italy), Clay 01.09.2026 08:00 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Soto M. (Chil)

Feldbausch K

🎯 PropickAI prediction

model probability · no colour signal

2 Feldbausch K 80%

1 20% · 2 80%

🎯 Safe pick Match winner — Feldbausch K ~87% strong

4.70 1.21

✓ Prematch ready 📊 extended stats line ready 5 bookmakers 5 markets updated 01.09 06:20 UTC

line available on the match card 5 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 23.5% / 76.5%

Market 1 / 2: 22.6% / 77.4%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 5 · total 0

Tournament: Challenger Men - Singles: Komo (Italy), Clay

Tennis

Challenger Men - Singles: Komo (Italy), Clay 01.09.2026 08:00 UTC NEUTRAL · MODEL CALCULATION

Uaild T. (Bra)

Krumich M

🎯 PropickAI prediction

model probability · no colour signal

1 Uaild T. (Bra) 57%

1 57% · 2 43%

1.62 2.18

✓ Prematch ready line ready 2 bookmakers 3 markets updated 01.09 06:15 UTC

line available on the match card 2 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 57.5% / 42.5%

Market 1 / 2: 57.3% / 42.7%

Favourite trap: no

Data completeness: 24%

Match context

Bookmaker coverage: 1×2 2 · total 0

Tournament: Challenger Men - Singles: Komo (Italy), Clay

International Komo Tennis

Tennis

International Komo 01.09.2026 08:00 UTC NEUTRAL · MODEL CALCULATION 📊 Rich data

Jianu F C

Squire H

🎯 PropickAI prediction

model probability · no colour signal

2 Squire H 59%

1 41% · 2 59%

2.30 1.63

✓ Prematch ready 📊 extended stats line ready 4 bookmakers 5 markets updated 01.09 06:11 UTC

line available on the match card 4 bookmakers Details

All stats and model conclusions

Model vs market

Glicko 1 / 2: 42.5% / 57.5%

Market 1 / 2: 42.2% / 57.8%

Favourite trap: no

Data completeness: 39%

Match context

Bookmaker coverage: 1×2 4 · total 0

Tournament: International Komo

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.