Review method · 01

How to review a Go game with AI

A four-step routine that does not chase every number: reconstruct your thinking, use KataGo to find turning points, and keep lessons you can use next game.

  1. Replay once before opening the AI

    Move quickly through the game and mark where you thought for a long time, felt unsure, or were surprised by the result. Write down what worried you then, so you can compare thought processes rather than merely copy an answer.

    On the first replay, do not recalculate every variation. Mark only three kinds of moment: where you slowed down, where you regretted the move immediately, and where the post-game result surprised you. Beside each mark, write the question you had before AI changed your memory, such as “Can this group live?” or “Must I keep sente here?” Those untouched questions later reveal whether the real training need is reading, direction, or risk judgment.

    Mark your own questions before opening AI; moves 42, 67, and 87 are the three positions selected for review.
  2. Find turning points with both graphs

    Import the SGF and start analysis. Scan the overall trend, then choose two or three positions with a meaningful change in win rate or score lead and enough context to understand it. Late fluctuations in an already decided game are rarely the best place to begin.

    The two graphs answer different questions. Win rate estimates the chance of winning if both sides continue strongly; score lead estimates the board margin. A sharp win-rate swing with a small score change often means the game was already extremely close. When both graphs move together, the position usually deserves attention. Place your marker on the move before the swing so you study the position in which the decision was actually made.

    The example aligns win rate and score lead around move 87. A turning point is an entry into study, not a verdict on your strength.
  3. Compare the game and candidate moves

    Play your move first, then explore several KataGo candidate moves and their variations on the board. Ask what threat each move answers, what sente it preserves, and which group becomes lighter or heavier.

    The candidate list is not an answer sheet. Play the game move and state its purpose, then play candidate A and identify whether it changes move order, group safety, or sente. Next, deliberately try a natural reply outside the main AI variation and see whether the idea survives. “A is better” is hard to reuse; “A forces a reply while the right-side group is still thin” is a reason you can recognize in another game.

    Side-by-side comparison: played move 87 attacks immediately, while candidate A first addresses the thin right-side group.
  4. Rewrite the result as a future cue

    Do not copy a long variation. Give each key position one action you can recall, such as “check my weakest group before attacking” or “when ahead, compare score lead instead of watching win rate alone.”

    Keep only one to three notes from a game. A useful format is “position signal → old habit → next action,” for example: “They have a weak group but mine is unsettled → attack immediately → first locate my weakest group.” Avoid saving coordinates and twenty-move lines unless you are studying a joseki that truly requires recall. Reopen only the position a few days later; if you can still name the check to perform, the note is useful.

    Compress a long variation into a review card that tells you what to check when the same signal appears again.

Before you finish

  • I can state what I was thinking
  • I kept only a few key positions
  • I understand the problem each candidate solves
  • I wrote a cue I can use next game
Open the review sample