---
license: apache-2.0
tags: [chess, policy, onnx, zugwise]
---

# Zugwise move prior

A small residual policy network that reports **what fraction of club-level human
players played each legal move**. Zugwise uses it to break near-ties between
handwriting-OCR candidates when reconstructing a scoresheet — it answers "what
did the player write?", never "what should they have played?".

- Architecture: 8 blocks x 128 filters, 17 input planes, 4096 move classes
- Move index: `from*64 + to, both squares in the side-to-move-flipped frame`
- Output: **raw logits; renormalise over LEGAL moves only**
- Top-1 move match (held out): **0.4836**

## Input encoding

17 planes x 64 squares, board FLIPPED so the side to move always plays up the
board (lc0/Maia convention, so no side-to-move plane):

    0-5    side-to-move pieces   P N B R Q K
    6-11   opponent pieces       P N B R Q K
    12-13  side-to-move castling  kingside, queenside
    14-15  opponent castling      kingside, queenside
    16     en-passant target square

No history planes: measured, Maia gave the identical top move on 42/42 real
positions with and without move history.

## Training data

lichess open database (CC0). No Maia weights or GPL-covered code are used or
derived from, which is the point — this model exists so Zugwise can ship a human
move prior under a permissive licence.

## Intended use and limits

Built to rank OCR candidates for scoresheet reconstruction, not to play chess.
It is deliberately small and rating-matched to club play; a strong-play policy
would be worse for this task, not better.