Chess Analysis Statistics 2026: Insights from 100,000+ Game Reviews

The trends below come from our internal review of a large sample of anonymized amateur games analyzed on ChessDream. The figures are approximate, illustrative estimates rather than precise published research, and they will vary by rating and playing style. For openly verifiable, large-scale game data you can explore the Lichess open database.

Our analysis uses Stockfish 16+ at depth 18-22 to evaluate every position, categorizing moves as brilliant, best, excellent, good, inaccuracy, mistake, or blunder. This consistent methodology allows us to identify patterns across player ratings and playing styles.

In our sample, the large majority of game-losing blunders happen during the middlegame (roughly moves 15-35), where piece interactions and tactics are most complex. Far fewer occur in the opening, and a smaller share in the endgame. The illustrative breakdown below shows this typical pattern; exact figures vary by player and rating.

This suggests that players should focus middlegame training to reduce the most impactful errors. Specifically, positions with multiple piece interactions and tactical complications show the highest blunder rates.

Among the games we reviewed, classical king-pawn and queen-pawn openings dominate: 1.e4 and 1.d4 together account for the large majority of first moves, with the Italian Game and Sicilian Defense the most common full systems. These are illustrative preferences from our sample; for openly verifiable popularity data, explore the Lichess opening explorer.

Analysis of starting moves reveals clear preferences among users:

What separates improving players is not raw talent but consistent review habits. The players who climb fastest analyze their losses promptly, focus on understanding why a move was best rather than memorizing it, keep a compact opening repertoire, and practice tactics daily. Improvement comes from the routine, not the occasional marathon session.

Players who analyze their games regularly tend to improve noticeably faster than those who only play without review—a meaningful edge that compounds over time. Here are the key differentiators:

The single biggest takeaway is that consistent game review, focused middlegame training, and a daily tactics habit do more for your rating than any one statistic. Treat the figures here as direction, not destiny: build the review routine, then turn it into points with the free game-review workflow and the wider Game Analysis hub.

Our research demonstrates that consistent game analysis is one of the most effective methods for chess improvement. The patterns revealed—from middlegame blunder concentration to the habits of fast improvers—provide actionable insights for players at all levels.

ChessDream will continue to publish original research as we gather more data, providing the chess community with unique insights not available elsewhere.