Matthias Wuellenweber - The Complete Guide to the ChessBase 26 Monte-Carlo-Analysis
Monte Carlo analysis in ChessBase offers a completely new way to understand sharp or unclear positions by simulating thousands of fast engine games and revealing their practical outcomes. In this walkthrough, Matthias Wüllenweber demonstrates how the feature works, how to interpret its statistics, and how the piece-path arrows uncover typical winning and losing manoeuvres. ChessBase '26 and Mega Database 2026 are now available on our shop. Order now if you have not yet. Photo: ChessBase
Matthias Wuellenweber - The Complete Guide to the ChessBase 26 Monte-Carlo-Analysis
0:00 – What Monte Carlo Analysis Is Introduction to Monte Carlo analysis, the dice icon, and why it gives practical, contrasting insights compared to normal engine evaluations.
1:48 – Why the Results Differ from Stockfish After several hundred games, the Monte Carlo score remains equal despite Stockfish showing a winning evaluation, illustrating the difficulty and pitfalls of the position.
3:02 – CPU Allocation & Remote Engine Advantage Explanation of parallel processing, 20-CPU usage, remote engine benefits, and how to adjust Monte Carlo parameters.
8:21 – Piece-Path Arrows & Success Colours Demonstration of the new hover-over arrows showing typical engine-match manoeuvres, with green/red success indicators, and how to disable them if needed.

