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BEST TABLE-TENNIS PREDICTIONS FOR TODAY & TOMORROW

25-04-2025

Czech Liga Pro

Zeman L.

Zahradka M.

33%
66%

Dvorak M.

Laznicka R.

12%
87%

Tuma D.

Dousa T.

58%
41%

Bradach P.

Zahradka M.

16%
83%

Bradach P.

Zeman L.

98%
2%

Tuma D.

Trinta M.

96%
3%

Urbaniec R.

Pikous M.

16%
83%

Vavricka R.

Dvorak M.

85%
14%

Dousa T.

Fisera M.

16%
83%

Kliucuk R.

Bayer A.

85%
14%

Laznicka R.

Kabelka J.

95%
4%

Zahradka M.

Svacha O.

97%
2%

Holovatiuk Y.

Cermak V.

2%
97%

Kubat V.

Pycha M.

2%
97%

Strnad J.

Dolezal V.

42%
57%

Pikous M.

Kliucuk R.

98%
1%

Trinta M.

Dousa T.

48%
51%

Bayer A.

Urbaniec R.

11%
88%

Fisera M.

Tuma D.

12%
87%

Kabelka J.

Vavricka R.

55%
44%

Svacha O.

Bradach P.

97%
2%

Urbaniec R.

Kliucuk R.

10%
90%

Vavricka R.

Laznicka R.

97%
2%

Dvorak M.

Kabelka J.

96%
3%

Pikous M.

Bayer A.

22%
77%

Trinta M.

Fisera M.

22%
77%

Zeman L.

Svacha O.

97%
2%

Janata T.

Holovatiuk Y.

97%
2%

Berdych P.

Hruska V.

14%
85%

Varcl J.

Strnad J.

96%
3%

Volf M.

Briska J.

97%
2%

Vrabec M.

Cernik J.

96%
3%

Grohsgott J.

Vrabec M.

20%
80%

Janata T.

Volf M.

97%
2%

Varcl J.

Berdych P.

96%
3%

Grohsgott J.

Kubat V.

66%
33%
TT Elite Series

Wozniak J.

Maruszak P.

95%
4%

Marchlewski M.

Krzyzanowski M.

66%
33%

Cioch B.

Wozniak J.

80%
20%

Wiza R.

Juszczyk K.

66%
33%

Szlubowski D.

Marchlewski K.

85%
14%

Kasperski A.

Lojtek T.

83%
16%

Kwodawski B.

Wozniak J.

83%
16%

Kapik K.

Gawlas M.

97%
2%

Marchlewski K.

Lojtek T.

95%
4%

Koczyba M.

Jedrzejak P.

94%
5%

Gawlas M.

Strowski K.

75%
25%

Jedrzejak P.

Nowak J.

97%
2%

Nowak J.

Juszczyk K.

96%
3%

Niemiec K.

Kapik K.

97%
2%

Krzyzanowski M.

Niemiec K.

95%
4%

Poloszczanski D.

Makajew M.

47%
52%

Marchlewski K.

Kowalczyk M.

0%
0%

Szlubowski D.

Pawlowski K.

80%
20%

Kwodawski B.

Makajew M.

97%
2%

Lojtek T.

Kowalczyk M.

46%
53%

Maruszak P.

Gluszek W.

0%
0%

Krzyzanowski M.

Strowski K.

0%
0%

Wisniewski K.

Marchlewski M.

95%
4%

Kasperski A.

Kowalczyk M.

96%
3%

Makajew M.

Gluszek W.

96%
3%

Szlubowski D.

Kowalczyk M.

80%
20%

Marchlewski K.

Pawlowski K.

96%
3%

Fira D.

Jedrzejak P.

97%
2%

Poloszczanski D.

Maruszak P.

98%
1%

Poloszczanski D.

Cioch B.

97%
2%

Fira D.

Nowak J.

96%
3%

Marchlewski K.

Kasperski A.

47%
52%

Marchlewski M.

Niemiec K.

97%
2%

Jedrzejak P.

Juszczyk K.

98%
1%

Kapik K.

Krzyzanowski M.

95%
4%

Pawlowski K.

Wrobel D.

94%
5%

Wisniewski K.

Gawlas M.

87%
12%

Fira D.

Koczyba M.

94%
5%

Koczyba M.

Juszczyk K.

98%
1%

Wiza R.

Koczyba M.

83%
16%

Makajew M.

Cioch B.

98%
1%

Kasperski A.

Wrobel D.

46%
53%

Wiza R.

Jedrzejak P.

97%
2%

Marchlewski M.

Kapik K.

47%
52%

Maruszak P.

Makajew M.

98%
1%

Cioch B.

Maruszak P.

97%
2%

Wiza R.

Nowak J.

48%
51%

Pawlowski K.

Lojtek T.

80%
20%

Fira D.

Wiza R.

60%
40%

Koczyba M.

Nowak J.

97%
2%
WTT Contender Tunis 2022, WS

Odo S.

Wan Y.

83%
16%

Dragoman A.

Hayata Hina

47%
52%
WTT Contender Tunis 2022, MS

Lebrun F.

El-Beiali M.

98%
1%

Uda Y.

Abdel-Aziz Y.

95%
4%

26-04-2025

Czech Liga Pro

Pycha M.

Cernik J.

95%
4%

Dolezal V.

Hruska V.

96%
3%

Cermak V.

Briska J.

97%
2%

27-04-2025

ETTU Europe Cup

Post SV Mühlhausen

Cajasur Priego TM

66%
33%

Sten HB Ostrov

Dojlidy Bialystok

75%
25%

28-04-2025

ETTU Champions League, Women

Metz TT

TT Saint-Quentin

55%
44%

Predicting Table Tennis Match Outcomes: Key Factors and Insights

Here at Tabletennispredictions.com, we bring you the latest table tennis predictions from all major leagues and competitions.
Accurately predicting the outcome of a table tennis match requires an in-depth analysis of various elements that impact player performance. Below is an overview of the crucial factors and their significance in shaping predictions:

1. Critical Factors Influencing Table Tennis Predictions

Player Skill Level
  • World Rankings: Higher-ranked players generally exhibit superior skill and greater consistency.
  • Technical Proficiency: Expertise in techniques such as forehand, backhand, spins, and smashes is essential.
  • Tactical Adaptability: The ability to modify strategies based on an opponent’s strengths and weaknesses is a significant advantage.
Playing Style
  • Offensive vs. Defensive Approaches: Offensive players thrive on speed and power, while defensive players excel in long rallies and shot returns.
  • Spin Mastery: The effective use of topspin, backspin, and sidespin can determine control over the game.
  • Error Management: Players who minimize unforced errors hold a distinct edge in high-pressure scenarios.
Matchup Dynamics
  • Head-to-Head Records: Previous results against the same opponent provide valuable predictive insights.
  • Style Matchups: Certain playing styles may struggle against others, such as offensive players facing strong defenders.
Recent Performance Trends
  • Current Form: Recent successes or struggles often indicate a player’s readiness.
  • Confidence Levels: Players on winning streaks often enter matches with boosted morale.

2. Prediction Methods in Table Tennis

Statistical Analysis
  • Examining historical data, such as win-loss records, rankings, and point differentials, to uncover trends and probabilities.
  • Leveraging regression models or machine learning to identify predictive patterns.
Simulation Techniques
  • Modeling matches using player statistics like rally length, serve success rates, and error frequencies to forecast potential outcomes.
Elo Rating System
  • Adjusting player ratings dynamically after each match based on performance, offering a real-time skill evaluation.
Expert Insights
  • Drawing from the expertise of coaches, players, and analysts to account for factors that raw statistics may overlook.