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BEST TABLE-TENNIS PREDICTIONS FOR TODAY & TOMORROW

15-07-2025

TT Elite Series

Pytlas W.

Tkocz M.

96%
3%

Strowski K.

Kolodziej K.

98%
1%

Ruszkiewicz A.

Pytlas W.

97%
2%

Nagel K.

Fabis A.

97%
2%

Kwodawski B.

Cioch B.

97%
2%

Kapik Krzysztof

Chmielowski J.

98%
1%

Kubiak A.

Pyrek D.

98%
1%

Chmielowski J.

Jarocki L.

97%
2%

Wnek S.

Fabis A.

97%
2%

Pyrek D.

Oracz J.

75%
25%

Kolodziej K.

Jarocki L.

98%
1%

Kubiak A.

Scigany D.

75%
25%

Olbrycht M.

Chmielowski J.

97%
2%

Strowski K.

Jarocki L.

96%
3%

Pyrek D.

Lamer M.

97%
2%

Bluszcz T.

Oracz J.

96%
3%

Ruszkiewicz A.

Panczyk A.

96%
3%

Cioch B.

Sinicki M.

96%
3%

Ruszkiewicz A.

Wrzalik T.

97%
2%

Wrzalik T.

Pytlas W.

97%
3%

Lebek M.

Nowak J.

97%
2%

Kolodziej K.

Chmielowski J.

95%
4%

Fabis A.

Strus P.

98%
1%

Kubiak A.

Bluszcz T.

96%
3%

Kubiak A.

Lamer M.

97%
2%

Nagel K.

Wnek S.

66%
33%

Sinicki M.

Lilien A.

46%
53%

Hetnar K.

Marud G.

96%
3%

Kwodawski B.

Kotwica D.

98%
2%

Marud G.

Tkocz M.

98%
1%

Strowski K.

Kapik Krzysztof

96%
3%

Scigany D.

Bluszcz T.

96%
3%

Pawlowski K.

Nagel K.

97%
2%

Ruszkiewicz A.

Tkocz M.

97%
2%

Rudomina K.

Lilien A.

96%
3%

Kotwica D.

Sinicki M.

94%
5%

Scigany D.

Oracz J.

97%
2%

Bluszcz T.

Lamer M.

98%
1%

Rudomina K.

Kotwica D.

71%
28%

Rudomina K.

Sinicki M.

97%
2%

Misiak M.

Cioch B.

98%
1%

Wnek S.

Pawlowski K.

97%
2%

Pyrek D.

Bluszcz T.

96%
3%

Wrzalik T.

Juszczyk K.

96%
3%

Strus P.

Pawlowski K.

71%
28%

Sinicki M.

Misiak M.

97%
2%

Pawlowski K.

Rolak J.

97%
3%

Juszczyk K.

Tkocz M.

97%
2%

Kapik Krzysztof

Kolodziej K.

97%
2%

Marud G.

Panczyk A.

97%
2%

Wnek S.

Strus P.

98%
1%

Wisniewski K.

Kolodziej K.

96%
3%

Kubiak A.

Oracz J.

27%
72%

Scigany D.

Lamer M.

95%
4%

Rolak J.

Nagel K.

98%
1%

Lamer M.

Oracz J.

93%
6%

Wrzalik T.

Tkocz M.

46%
53%

Fabis A.

Rolak J.

97%
2%

Olbrycht M.

Kapik Krzysztof

98%
1%

Wisniewski K.

Olbrycht M.

96%
3%

Pyrek D.

Scigany D.

57%
42%

Kotwica D.

Lilien A.

26%
73%

Juszczyk K.

Pytlas W.

95%
4%

Nagel K.

Strus P.

97%
2%

Strus P.

Rolak J.

96%
3%

Marud G.

Juszczyk K.

96%
3%

Kwodawski B.

Sinicki M.

96%
3%

Rudomina K.

Cioch B.

97%
2%

Pawlowski K.

Fabis A.

97%
2%

Kolodziej K.

Olbrycht M.

95%
4%

Marud G.

Ruszkiewicz A.

95%
4%

Wisniewski K.

Kapik Krzysztof

83%
16%

Rudomina K.

Misiak M.

97%
2%

Hetnar K.

Tkocz M.

97%
2%
TT Cup

Szewczyk H.

Chlopek B.

97%
2%

Sadowski W.

Michta M.

97%
2%

Kos K.

Szewczyk H.

87%
12%

Kucharski M.

Sikon M.

96%
3%

Campoy P.

Alonso O.

97%
2%

Medina J.

Garcia P.

96%
3%

Campoy P.

Medina J.

55%
44%

Kucharski M.

Bracha M.

97%
2%

Garcia P.

Vega S.

96%
3%

Sadowski W.

Chlopek B.

55%
44%

Duch Adam

Kos P.

97%
2%

Kos K.

Michta M.

62%
37%

Kucharski M.

Ucinski R.

96%
3%

Sadowski W.

Szewczyk H.

97%
2%

Moroz A.

Chlopek B.

95%
4%

Kos K.

Sadowski W.

97%
2%

Ucinski R.

Kos P.

94%
5%

Michta M.

Chlopek B.

97%
2%

Sikon M.

Duch Adam

71%
28%

Ucinski R.

Sikon M.

97%
2%

Bracha M.

Kos P.

97%
2%

Bracha M.

Duch Adam

95%
4%

Szewczyk H.

Moroz A.

95%
4%

Michta M.

Moroz A.

96%
3%
Czech Liga Pro

Golis R.

Berdych P.

97%
2%

Kliucuk R.

Jiri Louda

57%
42%

Pavelka R.

Fisera M.

97%
2%

Turek T.

Petracek V.

71%
28%

Kolar M.

Briza F.

96%
3%

Tuma M.

Sprynar P.

95%
4%

Volhejn D.

Rose R.

96%
3%

Zahradnik T.

Brozhik K.

46%
53%

Berdych P.

Tuma M.

95%
4%

Jiri Louda

Zahradnik T.

60%
40%

Briza F.

Pavelka R.

46%
53%

Brozhik K.

Kliucuk R.

66%
33%

Rose R.

Turek T.

66%
33%

Sprynar P.

Golis R.

66%
33%

Golis R.

Tuma M.

98%
1%

Kliucuk R.

Zahradnik T.

66%
33%

Petracek V.

Volhejn D.

98%
1%

Pavelka R.

Kolar M.

95%
4%

Turek T.

Volhejn D.

83%
16%

Berdych P.

Sprynar P.

96%
3%

Fisera M.

Briza F.

22%
77%

Jiri Louda

Brozhik K.

81%
18%

Petracek V.

Rose R.

97%
2%

Kostal M.

Fojt P.

47%
52%

Mazanek S.

Pycha M.

95%
4%

Kolisnyk O.

Ruzicka J.

97%
2%

Krejci R.

Tuma D.

97%
2%

Syroha M.

Potensky J.

28%
71%

Kasnik S.

Huk M.

42%
57%

Pycha M.

Pinc S.

40%
60%

Kostal M.

Krejci R.

97%
2%

Mazanek S.

Syroha M.

98%
1%

Prazdny P.

Kolisnyk O.

97%
2%

Fojt P.

Janata T.

33%
66%

Prazdny P.

Kasnik S.

95%
4%

Fisera M.

Kolar M.

95%
4%

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.