Jan Gustafsson’s latest video series, “A repertoire against 1.Nf3, 1.c4 and 1.g3,” has just been released. Although a standalone series, it could also be thought of as Part 5 of Jan’s popular 4-part repertoire against 1.d4, since it covers all White’s attempts to dodge the lines in that series. Not sure what series to try next? Our new state-of-the-art proprietary search algorithm shows you recommendations immediately after you finish a game in the Playzone. We look at how it works.
Jan’s latest video series is out! In 9 videos, and just over 3 hours, it gives you all you need to play Black against opponents who play 1.Nf3, 1.c4 and 1.g3, including how to face such dangerous weapons as the King’s Indian Attack.
As Jan explains in the introduction:
Even though it is a standalone series it is based quite heavily on our 4-part black repertoire series against 1.d4, because many people had the problem, “I’m happy with the repertoire against 1.d4, I’m happy with the Nimzo, the Catalan, the Vienna or the Queen’s Gambit Declined, but what do I do if people go 1.Nf3 d5 and then they don’t play 2.d4, but they play e.g. the King’s Indian Attack, or they play the Reti, or they start with 1.c4 and they try to move-order me out of my Nimzo-Indian.
It’s becoming more relevant than ever, because many 1.d4 players, me included, have started branching out quite heavily, and started playing a lot more 1.c4, a lot more 1.Nf3, trying to rely on move-order trickery to move guys off their favourite openings, so hopefully after watching this series you will no longer be vulnerable to such and will be very able to deal with these closed game artists.
Check out Jan's new series now!
In English alone there are now around 80 video series featuring almost 1000 individual videos, while there are also eBooks covering some options not yet available in video form. How should you decide what to study next?
Well, there are lots of approaches, but one fun one is now simply to play a blitz or bullet game in our Playzone. As soon as the game is over you’ll see a recommendation appear for what to try next. You might expect it just to show a random series, or a suggestion based on a basic list of openings, but in fact it uses a sophisticated algorithm developed by chess24 developer, and Women’s International Master, Lyubka Genova, who submitted her work as part of her PhD.Big data, and information retrieval of that data (search), is the backbone of the modern web, and what Lyubka managed to do was adapt existing approaches not to handle words, but chess positions (represented by FENs – a text representation of a chess position that you can also find in the Analysis tab under any game).
To determine how important particular positions are the system uses the TF-IDF weighting – i.e. the product of the Term Frequency (how often, in this case, a chess position occurs) and the Inverse Document Frequency (how unique the position is – e.g. the starting position of a game will give lots of hits, but won’t be useful for the search). The actual algorithm used is of course proprietary, with some adaptations, for instance, to give more weight to main lines.
Games are indexed in a Vector Space Model, with Cosine Similarity used to give a measure of how closely the game matches the different series. As you may have noticed, it’s all very mathematical, but the point is that the calculations can be completed at lightning speed and allow results to be provided almost in real time. And that’s when the recommendation appears. Give it a go!
We respect your privacy and data protection guidelines. Some components of our site require cookies or local storage that handles personal information.