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CHESS ANALYTICS 02: Karpov vs. Korchnoi 1978 + 1981

27 Wednesday May 2026

Posted by Ripsu-sama in chess, chess analytics

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Tags

chess, chess analytics, chess history, engine analysis, Fischer, Karpov, Korchnoi, performance analysis, Stockfish, world championship

  • CHESS ANALYTICS 00: Methods: Measuring World-Championship Roads with Stockfish 18 WDL
  • CHESS ANALYTICS 00.0: List of Other Chess Analytics Articles
  1. 1. CHESS ANALYTICS 02 part 1/2: Karpov 1978 + 1981 vs. Korchnoi
    1. 1.1. Overall verdict
    2. 1.2. The two matches are very different
    3. 1.3. Karpov–Korchnoi 1978: nearly level
    4. 1.4. Karpov–Korchnoi 1981: clear Karpov superiority
    5. 1.5. Game Accuracy and Mutual Accuracy
    6. 1.6. Overall game-by-game edge
    7. 1.7. Which metrics best explain the scores?
    8. 1.8. Metric-family interpretation
    9. 1.9. Chess-style interpretation
    10. 1.10. Final conclusion
  2. 2. CHESS ANALYTICS 02 part 2/2: Karpov 1981 vs. Fischer 1971-72
    1. 2.1. Why Karpov 1981 improves the forecast
    2. 2.2. Why Fischer still retains a small statistical edge
    3. 2.3. The key change: Karpov becomes a much better anti-Fischer candidate
    4. 2.4. Revised estimate
    5. 2.5. Final answer
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CHESS ANALYTICS 01: Fischer 1971-72 compared with Karpov 1974

26 Tuesday May 2026

Posted by Ripsu-sama in chess, chess analytics

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Tags

championship runs, chess, chess analytics, chess history, chess metrics, engine analysis, Fischer, Karpov, Stockfish, world championship

  1. 0. CHESS ANALYTICS 00: Methods: Measuring World-Championship Roads with Stockfish 18 WDL
  2. CHESS ANALYTICS 00.0: List of Other Chess Analytics Articles
  1. 1. CHESS ANALYTICS 01 part 1/3: the 11th World-Champion, Robert Fischer
    1. 1.1. Overall verdict
    2. 1.2. Match-by-match headline
    3. 1.3. Fischer–Taimanov, 6–0
    4. 1.4. Fischer–Larsen, 6–0
    5. 1.5. Fischer–Petrosian, 6.5–2.5
    6. 1.6. Fischer–Spassky, 12.5–7.5 in played games
    7. 1.7. Game-level findings
    8. 1.8. What most strongly explains the scores?
      1. 1.8.A. Expected-score advantage explains the base result
      2. 1.8.B. Conversion explains why the result became historically crushing
      3. 1.8.C. Loss and volatility metrics explain the engine edge
      4. 1.8.D. Error Concentration is not a primary explanation
      5. 1.8.E. RAP metrics mostly encode score + quality dominance
    9. 1.9. Overall chess interpretation
  2. 2. CHESS ANALYTICS 01 part 2/3: the 12th World-Champion, Anatoly Karpov
    1. 2.1. Overall verdict
    2. 2.2. Overall stability and SD reading
    3. 2.3. Match-by-match summary
    4. 2.4. Karpov–Polugaevsky, 5.5–2.5
    5. 2.5. Karpov–Spassky, 7–4
    6. 2.6. Karpov–Korchnoi, 12.5–11.5
    7. 2.7. Game Accuracy and Mutual Accuracy
    8. 2.8. Game-by-game relative edge
    9. 2.9. Which metric families best explain the run?
      1. 2.9.1. Expected Score and Dominance
      2. 2.9.2. Conversion
      3. 2.9.3. Mean ES Loss, RMS ES Loss, and Volatility
      4. 2.9.4. Error Concentration
      5. 2.9.5. RAP metrics
    10. 2.10. Chess interpretation
  3. 3. CHESS ANALYTICS 01 part 3/3: 11th vs. 12th World-Championship run
    1. Fischer 1971–72 compared with Karpov 1974
    2. Fischer
    3. Karpov
    4. Fischer’s volatility profile
    5. Karpov’s volatility profile
    6. WDL Accuracy SD
    7. PQ SD
    8. Volatility SD
    9. Fischer’s route
    10. Karpov’s route
    11. Fischer–Spassky 1972
    12. Karpov–Spassky 1974
    13. What changed in Spassky?
    14. Fischer vs Karpov through Spassky
    15. Metric-based favorite: Fischer, narrowly to moderately
    16. Rough match estimate
    17. Fischer’s statistical weapons
    18. Karpov’s statistical weapons
    19. 3.12.1. Fischer’s result dominance is far larger
    20. 3.12.2. Karpov’s technical cleanliness is higher
    21. 3.12.3. Fischer’s relative separation is higher
    22. 3.12.4. Karpov’s run is lower-volatility
    23. 3.12.5. Fischer’s conversion is historically extreme
    24. 3.13.1. Both were more accurate than their opponents
    25. 3.13.2. Both had lower expected-score loss
    26. 3.13.3. Both had lower volatility than their opponents
    27. 3.13.4. Both scored above expectation
    28. 3.13.5. Both beat Spassky by similar relative WDL margins
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