Body: <p>If you want to know what moves humans play in a certain positions, any database with enough games in it can give you the answer.</p>
  <p>This obviously only works for <em>opening positions</em>, as the chance of any human games having reached the exact position you are looking at exponentially decreases as the game progresses.</p>
  <p>But upon reaching the endgame, games start converging again, in many cases ending up in positions that have occurred millions of times when the number of pieces gets very low.</p>
  <p>I'm interested in what moves humans make in those common endgame positions.</p>
  <p><strong>Why this is different than endgame tablebases:</strong></p>
  <p>Tablebases reflect perfect play. In a losing position, all moves lose, so they are all equivalent as far as the tablebase is concerned, except for metrics like distance to mate and such.</p>
  <p>Humans do not play perfectly. By having access to move frequency data, one can deliberately prepare &quot;tricky&quot; moves that maximize the chance of the opponent blundering a win or draw.</p>
  <p><strong>But where can such frequency data be found?</strong></p>
  <p>For instance, Lichess, which has an opening book for <a href="https://lichess.org/analysis/rnbqkbnr/pppppppp/8/8/4P3/8/PPPP1PPP/RNBQKBNR_b_KQkq_-_0_1" rel="nofollow noreferrer">opening positions</a> replaces this book with an <a href="https://lichess.org/analysis/8/8/8/8/1k6/1p6/pK6/8_w_-_-_0_1" rel="nofollow noreferrer">endgame tablebase view</a> when the number of pieces gets within range for those.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-06-11T17:22:29.847Z
Comments.Text: Run a script over the megabase? Obvious problem: "Common" possible endgame positions exceed "common" opening positions by a few orders of magnitude. Maybe you should start small: How good are humans in mating with B+N compared to the tablebase?
Comments.UserDisplayName: Hauke Reddmann
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-06-19T14:05:56.260Z
Comments.Text: "But upon reaching the endgame, games start converging again, in many cases ending up in positions that have occurred millions of times when the number of pieces gets very low." - This isn't necessarily the case. E.g., even if we suppose all chess games ended in King vs King (which definitely isn't the case), there would still be thousands of legal arrangements for those two pieces on the board.
Comments.UserDisplayName: Inertial Ignorance
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-06-19T14:09:19.813Z
Comments.Text: You could loop over games in a database and collect those that have certain combinations of pieces. But the problem is that these pieces won't be in the exact same squares in almost all the cases. So to understand the types of moves people play, you'd have to somehow recognize overarching patterns. I suppose this could be possible with some advanced program or machine learning project, but I'm just guessing here.
Comments.UserDisplayName: Inertial Ignorance
Tags: <endgame><database><preparation><reference-request>
Title: Endgame move frequency data?
ThreadText: # Endgame move frequency data?
  
  (Asked by: username_0 on 2022-06-11)
  
  If you want to know what moves humans play in a certain positions, any database with enough games in it can give you the answer.
  
  This obviously only works for *opening positions*, as the chance of any human games having reached the exact position you are looking at exponentially decreases as the game progresses.
  
  But upon reaching the endgame, games start converging again, in many cases ending up in positions that have occurred millions of times when the number of pieces gets very low.
  
  I'm interested in what moves humans make in those common endgame positions.
  
  **Why this is different than endgame tablebases:**
  
  Tablebases reflect perfect play. In a losing position, all moves lose, so they are all equivalent as far as the tablebase is concerned, except for metrics like distance to mate and such.
  
  Humans do not play perfectly. By having access to move frequency data, one can deliberately prepare "tricky" moves that maximize the chance of the opponent blundering a win or draw.
  
  **But where can such frequency data be found?**
  
  For instance, Lichess, which has an opening book for [opening positions](https://lichess.org/analysis/rnbqkbnr/pppppppp/8/8/4P3/8/PPPP1PPP/RNBQKBNR_b_KQkq_-_0_1) replaces this book with an [endgame tablebase view](https://lichess.org/analysis/8/8/8/8/1k6/1p6/pK6/8_w_-_-_0_1) when the number of pieces gets within range for those.
  
  **Tags:** endgame, database, preparation, reference-request
  
  > **Comments:**
  > **username_1**: Run a script over the megabase? Obvious problem: "Common" possible endgame positions exceed "common" opening positions by a few orders of magnitude. Maybe you should start small: How good are humans in mating with B+N compared to the tablebase?  
  > **username_2**: "But upon reaching the endgame, games start converging again, in many cases ending up in positions that have occurred millions of times when the number of pieces gets very low." - This isn't necessarily the case. E.g., even if we suppose all chess games ended in King vs King (which definitely isn't the case), there would still be thousands of legal arrangements for those two pieces on the board.  
  > **username_2**: You could loop over games in a database and collect those that have certain combinations of pieces. But the problem is that these pieces won't be in the exact same squares in almost all the cases. So to understand the types of moves people play, you'd have to somehow recognize overarching patterns. I suppose this could be possible with some advanced program or machine learning project, but I'm just guessing here.  
  
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  ## 0 answers
  
  