Does 6.5 Komi points genuinely matter on 19x19 board?

shinuito · July 10, 2025, 12:00am

Not sure it helps, but I think some of the python code has been changed since the rating calculator conversion.

The win probably wasn’t shown anyway, but I remember that being one thing that changed.

It looks also like the handicap adjustment is different in the python code to the javascript one:

python:

analysis/util/RatingMath.py

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              # Convert the head start from "points" to "ranks", defining 1 rank as
              # the territorial value of a free move on a 19x19 board.  For small
              # boards, the head start needs to be scaled up to a 19x19 board.
              if size == 9:
                  return black_head_start * 6 / stone_value_territory
              if size == 13:
                  return black_head_start * 3 / stone_value_territory
              return black_head_start / stone_value_territory
          
          
          def get_handicap_adjustment(player: str, rating: float, handicap: int, size: int, komi: float, rules: str) -> float:
              rank_difference = get_handicap_rank_difference(handicap, size, komi, rules)
          
              # Apply the +/- for white/black in the "rank" domain where it's symmetric.
              # Note that the "rating" domain is log-scale, where +/- is asymmetric.
              assert player == "white" or player == "black"
              if player == "black":
                  effective_rank = rating_to_rank(rating) + rank_difference
              else:
                  effective_rank = rating_to_rank(rating) - rank_difference

doing some funny thing based on komi? Something like trying to unify 19x19 with smaller boards.

Compared to the js stuff that doesn’t do that I don’t think.

github.com/online-go/online-go.com

src/lib/rank_utils.ts

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          }
          
          /** Calculates OGS rank deviation from the Glicko2 rating and deviation */
          export function rank_deviation(rating: number, deviation: number): number {
              // Suggestion: use the uncertainty propagation formula for log transforms:
              // https://en.wikipedia.org/wiki/Propagation_of_uncertainty#Example_formulae
              //     - bpj
              return rating_to_rank(rating + deviation) - rating_to_rank(rating);
          }
          
          export function get_handicap_adjustment(rating: number, handicap: number): number {
              return rank_to_rating(rating_to_rank(rating) + handicap) - rating;
          }
          function overall_rank(user_or_rank: UserOrRank | rest_api.FullPlayerDetail["user"]): number {
              let rank: number;
              if (typeof user_or_rank === "number") {
                  rank = user_or_rank;
              } else {
                  rank = getUserRating(user_or_rank, "overall", 0).rank;
              }
              return rank;