Some readers may groan upon seeing the title of this post, and that’s okay. I get it.
Who, when taking their first steps in chess, dreams of winning wars of attrition? Probably no one. On the contrary, I often fantasized about winning a brilliant game in a tournament hall or chess club with a crowd of people watching in awe. Okay, I admit it … I still do!
Alas, I rarely win beautiful games. Most of my wins border on the tedious side — regularly 50+ moves. When I get away from this — whether because of fatigue, laziness, or delusions of grandeur — the results are usually disastrous. I’m just a grinder, and I’ve finally accepted that.
Fortunately, grinding works.
Easier to Play with Black?
With the White pieces, I feel a burden to “prove something” with my advantage of the first move. This often leads to going for too much, and bad things happen.
Grinders subscribe to the “equalize first” philosophy of playing the Black pieces. There isn’t any pressure to “do” anything. Even draws with peers are acceptable, though we want to win just as much as anyone else!
In the right position types, there will often be chances as Black to turn the tables on your opponent, especially if you’re willing to face a mildly unpleasant initiative. For a great example of this, play through Anatoly Karpov’s win against Gata Kamsky from the 1996 FIDE World Championshp Match.
Now I want to share another classic in a similar vein, also one of my favorite examples:
Born in Odesa, Ukraine, Efim Geller (1925-1998) was one of the world’s best from the 1950s through the 1970s. He was a six-time Candidate (1953, 1956, 1962, 1965, 1968, 1971) and twice USSR Champion (1955, 1979).
He defeated eight world champions in all, achieving plus-scores against Mikhail Botvinnik, Bobby Fischer, Tigran Petrosian, and Vasily Smyslov.
I highly recommend his autobiographical Application of Chess Theory. It is an underrated game collection! Geller shares incisive comments on openings and strategy, and a rich selection of his games. Quality Chess issued a new edition of this work under a fitting title: The Nemesis.
35 years after the historic AVRO 1938 tournament, another AVRO event was organized in the Dutch city of Hilversum in June 1973. This win helped Geller tie for first with Laszlo Szabo.
Black to play. How did Geller initiate a surprising king-hunt?
Chess computer software is extremely popular, and has been for a long time. A chess engine can analyze your games and give you an idea of how well or poorly you played. With ratings topping the 3400 mark, these monsters are several hundred points stronger than any human chess player, dead or alive.
…that is abused by less experienced players
Beware blindly following the output of a chess computer! An engine does not “understand” chess the same way a human does, and we cannot achieve the near-perfection in play that a computer can. When analyzing tactics the computer sees nearly everything, but what if you want to understand a position where pieces aren’t flying everywhere?
Here’s an example. You enter a game into ChessBase (or open one from a database). Then you open your favorite chess engine to analyze it, such as Fritz or Stockfish. How helpful might this be?
Let’s take the classic game Evans—Opsahl from the 1950 Dubrovnik Olympiad.
Evans-Opsahl, 1950, after 17 moves. I have opened Stockfish 11. How helpful is the engine, really?
The screenshot is not easy to see, so I’ll fill you in on some details. I turned on Stockfish 11 after black’s 17th move and let it analyze for awhile.
At 36 ply (half moves) or 18 full moves, it considers white’s best move to be 18.Rb2 for some strange reason, giving an evaluation of +/=0.68. This suggests white is slightly better. In a real game between humans, I totally disagree!
Situations like this usually arise from the Exchange Variation of the Queen’s Gambit Declined (1.d4 d5 2.c4 e6 3.Nc3 Nf6 4.cxd5 exd5; other sequences of moves can reach this same position). After both players support their d-pawns, and castle, we get a Karlsbad pawn structure, like this:
Both sides hope to start a minority attack on the flank where they have less pawns! White plays on the queenside, and black on the kingside. The idea is to create weaknesses to attack later. White’s play is quicker and easier, but if black succeeds the reward is a dangerous assault on white’s king.
What the engine can’t tell you
Let’s take another look at the game position:
White is ready to play 18.b5! to break apart black’s queenside. Notice that white’s pieces are in position to pounce. Of course, the future five-time U.S. Champion did just that.
Black has not played in the most accurate manner, and his attack is nowhere near threatening enough to disturb white seriously. Things would look better for him if his knight was on a more threatening post.
But wait, there’s more…
I’d like to mention that if black had the move here, an interesting possibility would be to play 18…b5!? himself. That makes is much harder for white to break through, and black has only one weakness to defend, on c6, though it’s a very serious one. Slowing white’s queenside play would also give black time to organize counterplay against white’s kingside. Either that, or try to land the black knight on c4 where it shields the weak c6-pawn from white’s pieces:
After the computer suggestion 18.Rb2 the move 18…b5 gains even more punch, because if white now follows with 19.axb5 axb5:
You can’t go wrong with this classic by Ludek Pachman.
White’s heavy pieces trip over each other and struggle to fight for the newly-opened a-file!
A chess engine can’t explain all of that to you. You have to either read a middle game textbook (such as Pachman’s Modern Chess Strategy), study well-annotated games from a database, or hire a coach. You can also read this blog regularly!
I could have left the engine on even longer, and maybe it would have chosen 18.b5 after all. It was the second-choice move with an evaluation of +/= 0.63. The point is, the computer couldn’t tell an inexperienced player the ideas behind any moves it suggests!
Evans was more than “slightly better” after 18.b5
The second player had to passively defend a weak structure for the rest of the game. In a practical game, this is a nightmare scenario. Opsahl finally succumbed after 81 moves.