CHESS ANALYTICS 04: Kasparov vs. Karpov matches of 1985, 1986, 1987, 1990, plus comparison from 1970s to 1990s

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  1. 1. CHESS ANALYTICS 04 part 1/2: the Kasparov-Karpov matches between 1985-90
    1. 1.1. Short verdict
    2. 1.2. Overall run table
    3. 1.3. Match-by-match comparison
    4. 1.4. 1985 match: Kasparov’s clearest technical victory
    5. 1.5. 1986 match: a near-equal match decided by conversion
    6. 1.6. 1987 match: Karpov’s statistical counterpunch
    7. 1.7. 1990 match: Kasparov reasserts the edge
    8. 1.8. Game Accuracy and Mutual Accuracy
    9. 1.9. Game-by-game metric edge
    10. 1.10. Correlations with score
    11. 1.11. Which metric families explain the overall 50–46 result?
      1. 1.11.1. Expected Score and Dominance
      2. 1.11.2. Accuracy and PQ
      3. 1.11.3. Mean ES Loss and RMS ES Loss
      4. 1.11.4. Volatility
      5. 1.11.5. Conversion
      6. 1.11.6. Error Concentration
    12. 1.12. Overall chess interpretation
    13. 1.13. Article-style thesis
  2. 2. CHESS ANALYTICS 04 part 2/2: comparisons between 1970s to 1990s player metrics
    1. 2.1. Compact chronological table
    2. 2.2. Is there a quality trend?
      1. Yes, especially from Fischer 1971–72 to Karpov 1974 and the 1980s
    3. 2.3. The strongest trend: Mutual Accuracy and PQ rise
    4. 2.4. Mean ES Loss and RMS ES Loss show the trend even better
    5. 2.5. Volatility also drops strongly
    6. 2.6. Standard deviations: later play is usually more stable, but not always
      1. WDL Accuracy SD
      2. Game Accuracy SD
      3. Mutual Accuracy SD
    7. 2.7. Error Concentration does not show a simple historical trend
    8. 2.8. The major exceptions to the trend
      1. Exception 1: Fischer–Spassky 1972 was cleaner than Fischer’s Candidates matches
      2. Exception 2: Karpov–Korchnoi 1978 was unusually rough
      3. Exception 3: Kasparov–Karpov 1990 was rougher than 1984–1987
    9. 2.9. Peak-quality matches by metric
      1. Best WDL Accuracy
      2. Best Game Accuracy
      3. Best Mutual Accuracy / PQ
      4. Lowest Mean ES Loss
      5. Lowest RMS ES Loss
      6. Lowest Volatility
    10. 2.10. Final conclusion
      1. Best formulation
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CHESS ANALYTICS 03: Karpov vs. Kasparov 1984/85 match

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  1. 1. Short verdict
  2. 2. Overall metric table
  3. 3. Accuracy, PQ, and dominance
  4. 4. Loss metrics: Karpov slightly cleaner
  5. 5. Standard deviations and stability
  6. 6. Game Accuracy and Mutual Accuracy
  7. 7. Game-by-game metric edge
  8. 8. Phase-by-phase interpretation
    1. Games 1–9: Karpov builds the match
    2. Games 1–27: Karpov’s lead phase
    3. Games 28–48: Kasparov takes over
    4. Games 47–48: the collapse/reversal endpoint
  9. 9. Correlations with game score
  10. 10. Which metric families explain the 25–23 result?
    1. 1. Conversion explains most of the final margin
    2. 2. Expected Score and Dominance explain the underlying edge
    3. 3. Volatility explains Karpov’s stable advantage
    4. 4. RMS ES Loss is more favorable than raw accuracy counts
    5. 5. Error Concentration is almost irrelevant here
  11. 11. Chess interpretation
  12. 12. Final article-style thesis
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CHESS ANALYTICS 00.0: List of Other Chess Analytics Articles

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more to come

CHESS ANALYTICS 02: Karpov vs. Korchnoi 1978 + 1981

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  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

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  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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CHESS ANALYTICS 00: Methods: Measuring World-Championship Roads with Stockfish 18 WDL

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  1. CHESS ANALYTICS 00.0: List of Other Chess Analytics Articles
  1. 1. The Basic Units of the Analysis
  2. 2. Expected Score
  3. 3. Expected-Score Loss
  4. 4. WDL Accuracy
  5. 5. Game Accuracy
  6. 6. Mutual Accuracy
  7. 7. Performance Quality
  8. 8. Dominance
  9. 9. Volatility
  10. 10. RMS Expected-Score Loss
  11. 11. Error Concentration
  12. 12. Score, Expected Score, and Conversion
  13. 13. HardRAP and SoftRAP
  14. 14. How the Metrics Form One Whole
  15. 15. Why WDL Is Preferable Here to Pawn Evaluation
  16. 16. Why This Series Is Worth Doing

This article series studies World-Championship matches and World-Championship qualification runs with a modern engine-based method.

The basic idea is simple:

Put every move of great historical matches under Stockfish 18, translate each position into win/draw/loss chances, and then ask: who preserved winning chances better, who lost chances more often, who created volatility, who converted chances into points, and who stayed more consistent?

Stockfish 18 is far stronger than any human player. Its strength is so far above human World Champions that comparing it to humans by normal Elo becomes difficult. This makes it useful as a reference point: not because it “understands chess like a human,” but because it gives a very strong, consistent measuring stick.

The purpose is not to reduce chess greatness to one number. The purpose is to create a performance profile:

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IMAGINATION ENGINEERING: 21 Foundational Thought Operations

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Based on the author’s discussion with ChatGPT o1, below is a concise list of some foundational thought/imagination operations we’ve identified so far, each with a short description.

This list is one possible ordering of these operations, arranged from most foundational (simple transformations on what’s already present) to more complex (involving abstraction, context shifts, and temporal or evidential reasoning). Of course, any such ordering is subjective; different thinkers might sequence them differently based on how they conceptualize “foundational.” Still, this list gives a helpful progression from basic acts to more advanced cognitive maneuvers.


1. Addition or Subtraction

  • Definition: Including or removing elements or phases from a mental construct.
  • Example: Expanding a story by adding a new character, or simplifying a recipe by cutting out ingredients.

2. Partitioning or Unifying

  • Definition: Splitting elements or phases into distinct parts, or merging multiple elements or phases into a whole.
  • Example: Breaking a problem into smaller subproblems, or consolidating scattered notes into a single outline.

3. Enumerating

  • Definition: Systematically listing or mapping out all possible combinations or permutations to ensure none are missed.
  • Example: Pairing {red, blue, green} with {circle, square, triangle} to generate nine distinct design ideas.
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PHILOSOPHY: Methods of Thinking in Plato’s Dialogues

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The following are a series of brilliant AI-generated Step-by-Step Guides for Thinking in the same way as Plato, the brilliant philosopher. The AI used was Google’s Gemini 1.5 Pro with NotebookLM, as presented with the five volumes of Benjamin Jowett’s public domain 1871-1875 translations of Plato into English.

CONTENTS LIST:

  1. Methods of Thinking in Plato’s Dialogues
    1.1. Dialectic
    1.1.1. Dialectic: Definitions
    1.1.2. Dialectic: Division and Generalisation
    1.1.3. Dialectic: Elenchus (Socratic Method)
    1.2. Hypothetical Reasoning
    1.3. Anamnesis (Recollection)
    1.4. Analogy and Illustration
    1.5. Myth and Allegory
    1.6. Irony
  2. Main Subject Matters in Plato’s Dialogues, a List
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CHESS: Branchy, Decisive, Free: A Framework for Understanding High-Class Moves

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The Game Tree is a fundamental concept for explaining high-class moves.

I presume you already know about Game Trees.

The moves in a Game Tree create the structure of the Game Tree.

The excellence of a move is shaped by the future structure of the Game Tree.

The moves and the (future) structure of a Game Tree can be measured with the following concept pairs:

  • Decisive <–> Harmless (a.k.a. Sharp <–> Calm),
  • Branchy <–> Straight (a.k.a. Complicated <–> Simple),
  • Free <–> Deadendy,
  • Winning <–> Losing.

These concept pairs are measured as follows:

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