Let’s Check Engine Correlation: How to use it

That Let’s check Funktion started as a means to distribute computer analysis of games or positions to other users and get feedback from not just one engine, but up to three. This was a “scratch my back and I’ll scratch you” process as you spent credits to get this and earned credits by leaving your computer open for others to request the same from your computer.

A more recent addition to its functionality has been the provision of a report at the end of the analysis, shown at the beginning of the notation, letting you know about the engine correlation Score of white and black. This engine correlation is a summary of the number of moves that matched an engine’s best decisions. If all moves agree with the first choice of an engine, then the engine correlation The score is 100%.

Why Use Let’s Check Engine Correlation?

Imagine you’re just analyzing with Stockfish and it says 5 moves out of 10 disagree. This might overlook the fact that two of the moves that don’t match his selection are being picked by another top engine like Komodo Dragon 3. In other words, only five match Stockfish, but a total of seven match the top engine choices. That’s the underlying point Let’s check the engine correlation. Using it to analyze a game not only tells you what a variety of engines thought about each move, but also gives you a summary to call up engine correlation above, shows the percentage of times a player’s moves matched an engine’s top pick.

However, unlike a simple engine comparison, it is not only compared to a top engine movement, but to severaland if the move matches one of those engines, then it’s a match for engine correlation.

Engine correlation in ChessBase 16

If you have ChessBase 16 or higher, you can access the pure report with a full averaged summary of multiple games. To access this, highlight one or more games in a database and right click, select Edit and then select from the list below Let’s check the engine correlation.

Regardless of the number of games, you get a total performance of all players. For example, after being asked to provide a report on all matches and players of the 2022 Candidates Tournament. Nepomniachtchi had stamped his way through the field very impressively and that engine correlation agrees by showing how much better his movement standard matched that of the best engines.

Be warned: Not only does it ignore any annotations already present in the game, it deletes them and replaces them with the Let’s Check annotations.

You will notice two things in the image above. The first is that Nepomniachtchi’s result was 12% higher than his rivals, which is a big difference. The second is that although each player played 14 games, many only reported 12 or 13 games.

The reason is Let’s check will ignore general theory movements, and the engine correlation is not reported if the game analyzed too few moves. Suppose a game was 28 moves long, but 20 of those moves were classified as theory, meaning that they only had to actually evaluate 8 moves, which is too few to issue a report.

When we open a sample game, we see a report at the beginning.

Motor correlation in Fritz

If you are using one of the chess engines that use an updated version of the Fritz interface, such as B. Fritz 18, Fat Fritz 2 or Komodo Dragon 3, you have some advanced options open to you.

To access it you just have to have a game in front of you and then to go analysis Select menu and left Let’s review the analysis.

Unlike ChessBase 16, this opens a new window with options.

The first choice is Errors, combinations, training, which it analyzes by looking for missed moves so you can compete with them. The second is Retrieval only and shall only consult the cloud for in-game positions already analyzed by other users. This already gives one engine correlation report whether enough moves have been analyzed previously.

Then we have the more interesting choice: standard analysis. The word standard isn’t usually associated with “interesting,” but you’ll see why.

Let’s click Progressive.

Now we have a bunch of options to play around with. The key to understanding here is this: Now when you access the Let’s check moved, you will also use your engine to contribute further analysis. For example if you select Just different moves, then every time a move in the game is not selected by other engines, it is analyzed with your engine and the results are added to the database. This happens even if the result matches the other engines.

reading the results

As mentioned in a previous article, the top players are perfectly capable of getting 100% matches or multiple scores with 90% scores or better. And even a much weaker player can occasionally get a high match, so don’t overinterpret it into a few isolated highs. I’m submitting one of my own games that I played a few years ago:

As you can see, I got an 86% match rate, and yet that doesn’t mean much other than that I was having a very good day back then.

There are those who say that this type of result doesn’t mean the player played better, it simply means they played more engine moves. However, I contend that if the engines are all 1000 Elo or better than us, the same moves almost certainly indicate that you’ve also made moves that are far closer to perfection than not.

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