MQ
MQ-Chess Loss Index
Original MQ-Chess Engine v2.0Loss Index

Know why you lose.
Not just how many centipawns.

The most precise free chess profile analyzer on the Internet. Powered by the original MQ-Chess (Loss Index) algorithm weighing decision complexity ln(N_legal+1) against win-chance deltas.

PGN Analyzer
Live Demos:

Why Average Centipawn Loss (ACPL) Fails

Traditional chess analyzers compute raw average centipawn loss across all moves. MQ-Chess measures true Win Chance Delta (ΔW) weighted by Decision Complexity ln(N_legal + 1).

Traditional ACPL Metric
Flawed
Centipawn Loss:
-100 Centipawns
Penalizes player -100 cp for dropping from +8.00 to +7.00.

The Problem: ACPL treats both scenarios identically! It penalizes a player who is up a queen for making a harmless move just as harshly as a player who blunders their queen in an equal game.

MQ-Chess Loss Index
Mathematically Exact
MQ Win-Chance Loss (ΔW):
0.0% Loss
Win chance remains 100%. MQ Loss Index is 0.0%.

The MQ Solution: Converts evaluation to Win Chance via sigmoid σ(cp) = 2/(1 + e^(-0.003624 * cp)) - 1 and weights moves by legal options ln(N_legal + 1).

Engineered for Competitive Precision

Zero clutter, zero vanity metrics. Everything designed to turn your game data into actionable chess progress.

20 Original Metrics

Opening Stability, Pressure Resistance, Time Collapse, Tilt Index, Conversion Score, and 15 more objective performance indicators.

PGN Drag & Drop Analyzer

Upload any raw PGN game for instant move-by-move evaluation graphs, critical blunder maps, and MQ contribution breakdown.

Head-to-Head Compare Mode

Compare Magnus vs Hikaru or yourself vs your rivals across accuracy, openings, time scrambles, and endgame technique.

Algorithmic Recommendations

No AI hallucinated advice. Pure deterministic mathematical thresholds that deliver concrete training actions.

Time Collapse & Tilt Tracking

Identify exact time-pressure thresholds where your calculation filters break down and post-loss performance drops.

Player DNA Radar

A 6-axis visual radar measuring your Attack, Defense, Opening, Endgame, Time Management, and Tactical Vision.

Frequently Asked Questions

Everything you need to know about the MQ-Chess engine and metrics.

MQ-Chess is an original accuracy metric created in 2024 by Ivan (IvanKulkin / @vansGAMee). It replaces flawed Average Centipawn Loss (ACPL) by calculating win-probability delta (ΔW) weighted by decision complexity log(N_legal + 1).

Join the MQ Chess Lab

Be part of our open-source chess analytics community. Vote for new metrics, test early engine builds, and discuss decision complexity math directly with developers.

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