ThomasCM
Joined 5 years ago
Joined 5 years ago
That said, there are also some unique features like "Openings" which allows you to quickly identify your best/worst openings.
Like the author, I also use regression, but extended to non-title players. More information: https://www.chessmonitor.com/blog/2023-elo-calculation
If anyone wants more info on how this works, check out this post with more details: https://www.chessmonitor.com/blog/2023-elo-calculation
Another key feature Lichess does not have, is the Openings page. It is very powerful when used correctly. You can look at your openings and immediately see for which openings you might need to consume more theory (or which you should not play at all).
Here is an example: https://www.chessmonitor.com/u/cdPiOkUArRJ7shVNJcT3/openings...
My code for that is rather simple. I'm using Next.js and the code looks something like this (a little simplified):
const router = useRouter(); // get the router/location object
const information = useFetch({ position: router.query.position }); // fetch information from the server
function changeChessPosition(newPosition) { // called when position changes
router.replace({ query: { postition: newPosition } }); // replaces the state in the URL
}
In addition, I have some caching in place so that each position is only downloaded once and the change function looks a little more complicated in my case as there are multiple values that can be change for each page.That said, there are some optimizations you can apply that will compress moves even further (for example the order of the moves as explained in the Lichess blog post is important). In the end it's a tradeoff between (de)serializing the game fast and reducing the size (even more).
All data comes from my project ChessMonitor, which maintains one of the largest chess databases in the world. Feel free to check it out! :)