Statistics and Chess Improvement

  • GM Shankland
  • | Feb 21, 2012

Today I would like to share with you an exercise I did at the end of 2011 to try to prepare for the events I would play in the next year. I logged 70 FIDE rated games in 2011. This is a decent but not huge sample size, and I decided to do a thorough statistical analysis of my results to try to find spots where I was performing well and spots where I could be playing better. I’ll show some of the results and notable statistics here:

Results by Rating

My Score vs. Opposition rated under 2400 FIDE: 23 wins, 1 draw, 0 losses: 97.9%, Performance Rating 2960

My Score vs. Opposition rated 2400-2499 FIDE: 3 wins, 8 draws, 0 losses: 72.2%, Performance Rating 2540

My Score vs. Opposition rated 2500-2599 FIDE: 5 wins, 13 draws, 3 losses: 54.5%, Performance Rating 2595

My Score vs. Opposition Rated 2600-2699 FIDE: 1 win, 7 draws, 4 losses: 37.5%, Performance Rating 2546

My Score vs. Opposition Rated 2700+ FIDE: 1 win, 2 draws, 1 loss: 50%, Performance Rating 2728


From this data I could tell that the players I was having the most issue with were the players in the 2400-2700 range, and when I look back at the year, it makes sense. I was not beating 2400-2600 players as much as I should have, and I lost a couple tough games to 2600s while only striking back once. I was holding my own against the really big boys, especially considering one of my draws against 2700+ could be considered a win because I only agreed the draw to win my match in an elimination style format. However, this was only a sample of 4 games. I was quite happy that I was able to manage such an effective score against players lower than 2400.

Another thing I noticed was that while my score against 2400-2600 players left a lot to be desired, I was losing very rarely and the 3 that did occur were against 2590, 2590, and 2592- players who might be in the next category had I played them a month before or later. I decided to move those losses into the 2600-2700 category, and then I found that my score against 2500-2599 was 2656 while against 2600-2700 was only 2512. This ultimately led me to conclude that the players I needed to score better against were the 2400-2500 players and the 2600-2700 players. I decided to fix this by trying to play a bit less theoretically against the lower players to try to get them on their own earlier, and to try to be more aggressive against the stronger players because my solid play got me a bunch of draws but I got knicked for a couple of losses and did not manage to counter it with an equal number of wins. It appears this analysis and my new approach paid off so far: I present you my results against these rating ranges from my first tournament of 2012.

My Score vs. Opposition rated 2400-2499 FIDE: 3 wins, 2 draws, 0 losses: 80%, Performance Rating 2698

My Score vs. Opposition rated 2600-2699 FIDE: 1 win, 1 draw, 0 losses: 75%, Performance Rating 2830

Results by Opening

Another key part of the statistical analysis is to look at openings- this will give you a sense of what you need to study more, both in terms of opening theory and the ensuing middle games. This section was very detailed in my work, but I’ll present a more general version here:

Score with White in d4 d5 systems: 68%, 2557 Performance Rating

Score with White in Nimzo/Quid systems: 70%, 2648 Performance Rating

Score with White in KID/Grunfeld: 67%, 2591 Performance Rating

Score with White in other Systems: 88%, 2755 Performance Rating


Score with Black vs. 1. e4: 58%. 2549 Performance Rating

Score with Black vs. 1. d4: 65%, 2639 Performance Rating

Score with Black vs. Other first moves: 56%, 2542 Performance Rating


With this information I deduced that I mostly need to work on my black repertoire against non-d4 moves and my white repertoire in the Slav and QGD. There is a lot more to the statistical analysis I did, including the use of the serious but unrated games (US Chess League, tiebreak games, rapid games, training games), filtering by how many moves the games lasted (which measures fatigue and level of endgame play), breaking the year in half (In January-May I performed at a 2580 level, while June through December I was over 2630, suggesting I probably improved and the more recent games are more relevant), and much more.

I would suggest to any reader, even those few who are not professional players, that statistical analysis can be an excellent way to examine your own play, and I would suggest breaking the analysis down by rating range and opening. Then, once you have determined a weakness, look at all of your games against this rating range or opening, including the wins, to determine what you might be doing wrong and how to improve it. And always keep in mind- a small sample of games will not have the same accuracy as a large sample. Lastly, I should point out this analysis would have been extremely difficult to do without the help of Chessbase, and I highly recommend that everyone buy this software, for statistics as well as opening preparation, and engine analysis. I know that I was much happier with my training regimen after doing a thorough statistical analysis of my own results, and so far it has paid off in my only 2012 event. I look forward to seeing if it can continue to pay dividends and I hope you find it useful as well.


  • 5 years ago

    CM psantann

    I think this is an effective method of focusing your effort where you need to improve. It can even said that it can be more important for amateurs (who have more time restrictions) than to professionals. Thank you for sharing this!

  • 5 years ago


    I have used this type of analysis in my openings.  In one line of one of the openings I play, Ifound out I did not fair very well.  I then studied that line for a few weeks and at my last tourney won both games in that variation.  I think this analysis can be very useful.

  • 5 years ago


    Nice analysis, and all that... However this information will not help you at all, and here is why. These games are already over. That information can not be changed and is in the past. Ratings are just imaginary. Play each game for the game that it is. Your opponents rating is not important b/c ratings are not accurate. A 2500 player can play like a 2300 one day and a 2700 on a different day. So when the score card says you are playing against a 2500 the game they play can be that of a 2300 or a 2700 making your analysis of vs a 2500 not accurate making your overall analysis not accurate.

    You are over thinking things... just play the game

  • 5 years ago


    Nice article. Thanqu. 

  • 5 years ago


    @idealogical thanks

  • 5 years ago


    Best article that i have ever read

  • 5 years ago


    Nice stuff

  • 5 years ago


    This is interesting information for highlighting problem areas that you might not be aware of. Another breakdown I have seen in a book (yermo or maybe wells?) was to also look at opening, middlegame and endgame losses/wins/draws and relate it to positions such as open and closed to even narrow down even further the areas that need some work. 

    I think Hammer should show us his breakdowns as well!!

  • 5 years ago

    FM VPA

    Don't bother so much on statistics just improve your standard & play well regardless whom you playYell

  • 5 years ago


    @Shams Thanks   

  • 5 years ago


    Certainly this makes a great deal of sense and this scientific approach or mathematical approach will prove it's worth!  Great idea!  And tracking progress like this ... is so critical for improvement be it in body building (weights / reps) or whatever ... it's needed because you can see where you need to improve, isolate that area and then focus on that weakness ...

  • 5 years ago


    Thank you, GM Shankland. That was a very nice idea!

  • 5 years ago


    Shredder runs natively on the Mac.

  • 5 years ago


    Nice results.
  • 5 years ago


    First of all, congratulations on your excellent results. But the opening alone makes itcertainly is not the point. If you have your self-analysis but certainly also the middlegame and endgame with the include?

  • 5 years ago


    A chessmaster discussion here really? Please at least make the effort to post it at a relevant place.

    There are ways to do that (even in the forums here).

    Be assured people there will gladly help out.

  • 5 years ago


    Pardon my ignorance, but why is chessmaster the only decent program available for Mac users??  Are there others?  Why would Fritz not be available?

    Thank you!

  • 5 years ago


    Rijac, essentially, you would need to code each game along the relevant dimensions (or categories); for example, [a] win (1) and loss (0), [b] rated games (1) and unrated games (2), [c] bullet games (1), blitz games (2), and standard games (3), [d] online (1) and live (2) games, [e] e4 opening playing as white (1), d4 opening playing as white (2), c4 opening playing as white (3), and any other opening moves you use (4-k, where k = the number of opening moves you use), [f] any other dimension you want to compare your performance on (e.g., specific openinings, responses to e4/d4/c4 when playing black, specific defences, time of the day, day of the week, and so on).  If you enter your codings into MS Excel (or another spreadsheet program), you could very easily do some basic analyses (search online for data analysis using Excel for information).  There are plenty of other ways to go about creating variables to work with, and analyzing your data, but this would allow you to do analyses similar to those in the above post. 

    Hope this helps!

  • 5 years ago


    Nice job.  Thanks for sharing!

    Two thoughts. 

    1. A larger sample size would definitely be good. But I imagine you also coded all or most of your unrated games.  Perhaps you can compare your performance rating by game type; i.e., rated games, unrated but serious games, other unrated games.  Perhaps the context influences your performance along specific dimensions (e.g., specific openings), which may suggest a social facilitation or social inhibition effect (look into the psychological research for a description of these effects, reasons they occur, etc.). 

    2. I wonder if significance tests (e.g., t, chi-square) would indicating the your preformance along certain dimensions (again, e.g., specific openings) would be useful.  If the differences are not statistically significant, perhaps giving more attention to something that appears to be a weakness would not be the best use of your time.  Again, though, the sample size might be an issue here.  If you are familiar with more advanced statistical techniques, perhaps some bootstrap analyses would come in handy for this.

    There are several other ways to think about and anlyze your data, some of which I'm sure you have done.  I'd be happy to brainstorm a little with you to identify others.

  • 5 years ago

    GM SultanOfKings

    Na, don't worry - I started out, but then lost interest fairly quick :)

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