How ChessTing calculates things

ChessTing mixes public game data, statistics from your games, and browser Stockfish. This page explains what each number means, how we compute it, and how it relates to Chess.com.

Quick trust guide

Where analysis runs & what we store

ChessTing has four modes. This matters for privacy and for what you should expect from each feature:

Full detail: Privacy Policy and Cookie Policy.

Where the data comes from

• Chess.com & Lichess public APIs — profiles, ratings, and PGNs for the period you select (default last 3 months).
• Your browser — Stockfish WASM runs locally for game review, move-quality scans, and blunder detection.
• Sample limits — scouting loads up to 600 recent games in the browser to keep the tab responsive. Longer periods may be truncated.

Ratings on the scout dashboard

Listed rating

The number on the player's Chess.com or Lichess profile for their strongest active pool. This is not calculated by ChessTing — we display what the platform reports.

Performance rating

Tournament-style performance over games in the selected period:

avg_opponent_rating + 400 × log10((wins + 0.5) / (losses + 0.5))

Requires at least 3 rated games with opponent ratings. Heavily skewed samples (same opponent repeatedly) are flagged.

Our best estimate

Blends listed and performance when the sample is balanced. If you play the same opponent in most games, we lean on listed because performance is distorted.

Move quality rating (Stockfish)

Not a replacement for your Chess.com rating. It answers: “In this sample, did the moves look cleaner or sloppier than typical for this listed rating?”

1. Replay the last N games (you pick 4, 8, 15, or 30).
2. Evaluate every position before each player move with Stockfish at depth 12.
3. Compute centipawn loss per move from that player's perspective.
4. Skip mate scores or shallow evals that distort averages.
5. Cap each move at 500 cp in the aggregate.
6. Average cp loss across all graded moves, then anchor to listed rating.

expected_cp = benchmark(listed_rating)
adjustment = (expected_cp − avg_cp_loss) × 7.5
move_quality = listed + clamp(adjustment, −280, +350)

Expected centipawn loss by rating

Rough accuracy %

Display-only shortcut: accuracy ≈ max(0, 100 − avg_cp_loss / 6). This is not Chess.com's accuracy formula.

Phase breakdown

Opening = moves 1–12, middlegame = 13–35, endgame = 36+. Same anchor formula applied to each phase's average cp loss.

Game review (paste PGN)

Every position is evaluated once at depth 12. Centipawn loss from White's perspective is classified as:

Precision score

Weighted average by severity (best = 100, blunder = 8, etc.), then averaged per player. Useful for comparing sides in one game — not 1:1 with Chess.com accuracy.

Blunder gallery & scout engine notes

• Inaccuracy: ≥ 50 cp
• Mistake: ≥ 150 cp
• Blunder: ≥ 300 cp

Opening book (first 8 plies) is skipped for blunder mining to avoid theory noise.

Scout heuristics (non-engine)

Most of the scouting dashboard — openings, tilt patterns, time-of-day charts, archetypes, victory plans — is statistical. These do not use Stockfish unless you run an explicit engine scan. Coach phrases are hypotheses to verify over the board, not guarantees.

ChessTing vs Chess.com

Expect 10–25 percentage-point gaps on accuracy vs Chess.com for the same game — normal, not a bug.

Known limitations

• Browser analysis can freeze on huge accounts — we cap at 600 games per scout.
• Shallow depth misses deep tactics; mates are excluded from move-quality averages.
• Small samples (4 games) swing more than 15–30 game scans.
• Playing one opponent repeatedly skews performance, not listed.
• Heuristic coach text may overstate patterns on thin data — check the game list.

Questions or corrections?

Note the username, period, and which card looked wrong — we tune formulas from real reports. support@chessting.com