Progress on Blunder

[algerbrex]

Over the long labor day weekend we had at my school, I spent a good deal of time finally sinking my teeth into understanding the meat and bones of a simple, feedforward, neural network. It wasn't as bad as I thought, although I am glad I waited to do this until after I had had plenty of exposure to linear algebra and calculus.

I used this excellent resource which many of you all probably already know about: http://neuralnetworksanddeeplearning.com/about.html

I still don't understand backpropagation as intuitively as I'd like, but I understand the formulas for computing the error vector for each layer and using it to compute the partials with respect to each weight and bias in each layer of the network, and then summing and adding the partials together to get the averages you would use to update the weights and bias during gradient descent. I plan to digest the proof section he gives when I have more time later, and look more closely into Grant Sanderson's (3blue1brown) playlist of neural networks on YouTube (

I still need to work out a couple of details though, namely the activation function I want to use, and how to map the output of the network to centi-pawn units. My initial thoughts were to shift the normal sigmoid function downward for the finally output neuron, and scale it so that it's always between -1 and 1, and then multiply the sigmoid by 10000, so that an activation of 0.01 would be equal to a centipawn score of +1, 0.1 equal to 10, and 1 equal to 100 centipawns, which of course would mean the position is overwhelmingly winning. And same logic for losing scores.

This would complicate the expressions for computing the error vectors and gradients slightly if I understand the math correctly, but it shouldn't be too difficult at all to compute by hand.

I also need to think about how I'm going to train the network. Since I want it to output a centipawn score, the first idea that comes to mind is to use labeled positions with scores. I would of course need to use a stronger engine for labeling the positions, which I don't particularly like since I don't necessarily want to train Blunder to play like another engine. But for initially experimenting, I think it'll work.

And for the number of positions to use, I'll use mini-batching and SGD to try to use as many positions as possible.

As an initial experiment, I'll start with a 768 -> 384 -> 1 structure, and write some code in Python to select about 2-10M positions to label using Stockfish's eval command functionally, and then train the network based on that. With so few positions used for tuning, I don't expect it to play very well at all, but I'm definitely curious to see how it plays plugged into Blunder's search.

The only other tedious part will be writing the structural code in Golang to allow for operations like matrix vector multiplication, or transposing a vector or what not.

[algerbrex]

After a couple of days (and nights) of programming, I've reached my first milestone in regards to implementing a neural network in Blunder by training and adding a simple network into Blunder's evaluation.

I generated data for the network by downloading games from the Lichess game database, and using some tools I've added to Blunder to parse the PGNs, and extract positions from them, labeling them using Blunder's evaluation. As a first attempt I just generated about 8M fens, and only used 100K of those for a quick and dirty tuning session.

The network structure is 768 -> 512 -> 512 -> 1, using ReLU activations of for the first two layers, and f(x)=20.00*Tanh activation on the last layer. My reasoning being that 20.00 cp would be the maximum value the NN evaluation could reach.

I trained the network using some simple driver code from PyTorch, and did about 10 epochs, which took a couple of minutes. With so little data and so few epochs, the network produced was of course quite janky, but it was cool to see even with the short tuning session, it had already "learned" material values and their relations (Q > R > B > R > P generally), and a few positional ideas like bringing pieces around the king to attack, or passed pawns near the enemy backrank are very valuable.

I then just needed to implement some matrix and vector code in Go, along with a few of their related operations, as well as some structural code for a neural network. It took a couple of hours but I go things up and running eventually, and all that was left to do was to write the weights and biases of the NN in Python to a file, and load them into the NN in Go, which wasn't a terribly difficult task. For now I just wrote the weights and biases in plain text to the file, but in the future, for actual NN I plan to use, they'll be encoded in binary.

With all of that finally done I was able to replace each instance of my HCE in the search with the NN evaluation, and watch the magic. Of course given how expensive it can be to fully do a pass through a network, the NPS and depth dropped dramatically. But nevertheless it seemed to play decent beginner-level chess. So I decided to pit it against Blunder 1.0.0 and got the resulting, very fun game:

[pgn]
[Event "?"]
[Site "?"]
[Date "2022.09.13"]
[Round "?"]
[White "Blunder NN"]
[Black "Blunder 1.0.0"]
[Result "1-0"]
[ECO "A04"]
[GameDuration "00:06:34"]
[GameEndTime "2022-09-13T06:51:26.355 Central Daylight Time"]
[GameStartTime "2022-09-13T06:44:52.249 Central Daylight Time"]
[Opening "Reti Opening"]
[PlyCount "55"]
[TimeControl "40/300+1"]

1. Nf3 {+0.29/5 8.3s} Nc6 {0.00/7 8.0s} 2. d4 {+0.20/5 8.3s} d5 {0.00/7 7.8s}
3. c4 {+0.31/5 8.3s} dxc4 {+0.15/7 7.7s} 4. d5 {+0.52/5 8.4s} Nb8 {+0.10/7 7.5s}
5. e3 {+0.35/4 8.4s} b5 {+0.45/7 7.3s} 6. Nc3 {+0.37/4 8.3s} b4 {+0.60/6 7.2s}
7. Ne4 {+0.67/4 8.3s} Ba6 {-0.05/7 7.0s} 8. Ne5 {+0.79/4 8.4s} c6 {-0.10/7 6.9s}
9. dxc6 {+0.81/3 8.3s} Qc7 {-0.10/8 3.0s} 10. Nxc4 {+0.85/3 8.4s}
Nxc6 {+0.05/7 6.7s} 11. a3 {+0.62/3 8.4s} Bb7 {+0.30/7 6.5s}
12. axb4 {+0.82/3 8.4s} Nxb4 {+0.15/7 6.4s} 13. Bd2 {+0.53/3 8.4s}
O-O-O {+0.15/7 6.3s} 14. Rxa7 {+0.59/3 8.4s} Kb8 {+0.15/6 6.1s}
15. Qa4 {+0.42/3 8.4s} Nc6 {+1.25/8 3.6s} 16. Rxb7+ {+0.56/4 8.5s}
Qxb7 {+0.95/8 5.7s} 17. Nc5 {+2.88/5 8.4s} Qc8 {-0.85/7 5.8s}
18. Nb6 {+4.36/6 8.4s} Qf5 {-2.35/7 5.7s} 19. Qxc6 {+3.38/5 8.4s}
Qb1+ {-2.60/6 5.6s} 20. Ke2 {+3.27/4 8.4s} Rxd2+ {-2.35/7 5.5s}
21. Kxd2 {+3.26/5 8.5s} Qxb2+ {-2.45/8 3.8s} 22. Kd3 {+3.26/5 8.5s}
Qb1+ {-2.35/7 5.3s} 23. Kc4 {+9.56/5 8.4s} Qc2+ {-1.60/7 5.2s}
24. Kb5 {+6.55/5 8.5s} Qb1+ {-8.05/7 5.1s} 25. Ka6 {+11.25/4 8.5s}
Qa1+ {-1999.94/7 5.0s} 26. Nca4 {+M5/5 8.5s} Qxf1+ {-1999.96/7 4.9s}
27. Rxf1 {+M3/6 8.6s} Nf6 {-1999.99/8 2.7s} 28. Qb7# {+M1/6 8.6s, White mates}
1-0
[/pgn]

Despite only searching many times 500-1000 NPS, Blunder with the NN actually managed to beat it's HCE counterpart. It was definitely cool to see the NN recognize the weak king safety of its opponent and go for an attack, and then be a couple steps ahead of Blunder 1.0.0 in realizing the attack succeded. And in the short time I trained the network, it also "learned" part of the line in the Queen's Gambit, which of course, was present in many of the Lichess games I sampled from.

As I said, this was mostly just a quick and dirty experiment for fun and to get a feel of training and implementing a NN from scratch. But seeing how powerful it can be, even with such a small amount of training, data, and NPS makes me very excited to start planning out my next steps!

[lithander]

this was mostly just a quick and dirty experiment for fun and to get a feel of training and implementing a NN from scratch. But seeing how powerful it can be, even with such a small amount of training, data, and NPS makes me very excited to start planning out my next steps!

Awesome! Absolutely inspiring! Now I want to explore NN based evaluation in my own engine immediately, too!

I generated data for the network by downloading games from the Lichess game database, and using some tools I've added to Blunder to parse the PGNs, and extract positions from them, labeling them using Blunder's evaluation. As a first attempt I just generated about 8M fens, and only used 100K of those for a quick and dirty tuning session.

What was discouraging me so far was that I thought you'd need millions or even billions of positions and quite a lot of time (or optimized code) to deal with these huge amouts of data. But you achieved a useful eval with only 100k positions and 10 epochs? That's even less data than what you'd use to "train" PSQ tables with!

Why did you start with downloading games from the Lichess db though? Couldn't you create 100k positions with Blunder quite quickly through selfplay?

[algerbrex]

Awesome! Absolutely inspiring! Now I want to explore NN based evaluation in my own engine immediately, too!

Thanks! I hope you do, I'm sure you have some good ideas to try out.

What was discouraging me so far was that I thought you'd need millions or even billions of positions and quite a lot of time (or optimized code) to deal with these huge amouts of data. But you achieved a useful eval with only 100k positions and 10 epochs? That's even less data than what you'd use to "train" PSQ tables with!

Why did you start with downloading games from the Lichess db though? Couldn't you create 100k positions with Blunder quite quickly through selfplay?

Yep. Again, re-iterating, the network is nowhere near something strong enough to publish. But also, as I said, it still worked as a very crude evaluation function.

The game I showed took the NN plugged into Blunder dev, so of course, the strength drop from the static eval is quite dramatic. But of course, I think the classic rule of thumb applies here: I spent months carefully tuning and tweaking the balance between the static HCE and the search, especially with things like pruning margins. So when I significantly change the evaluation, even if it's better, I'd expect to see an Elo drop.

I used the Lichess games because I was being lazy for the most part. I could've fairly quickly generated 100K positions, but I had seen many other engines had started with using Lichess, so I decided to go the same route. And it's seemed to work well for the most part.

I've recently found a ton of improvement on the NN scheme by actually reducing the size of the network to 768 -> 16 -> 1. Just 16 nodes in the hidden layer. Apparently the accuracy gained with a bigger net wasn't worth it with the speed drop it brought.

After a little thinking, I realized when computing the activation between the input layer and first hidden layer, the majority of the inputs were zero, so I wasted a ton of time in my matrix multiplication code by going over entries that were zero and would zero out a matrix column anyway. So I switched just the input to being a sparse array and speed up my code over 90+%. The engine went from searching to only about a depth of 5/6, to searching around 16/18, and actually the majority of the time, it matched the same depth as the HCE evaluation. So that's pretty exciting. If I can get the power of NN with only a small speed drop, that would be great.

Right now I'm going to be experimenting with how many hidden layers to use and what their sizes should be. Once I feel I have something interesting, I'm basically going to strip Blunder's search down and build it back up, at least the parts very dependent on the old eval, like static null-move pruning.

[algerbrex]

It's been a while since I posted here. I've mostly been busy with school and life, as usual. But seeing the progress other engine authors have been making in the past couple of months has motivated me to blow the dust off of Blunder's codebase and do some work to improve the engine.

I actually didn't start off by even touching Blunder's codebase. Since I'm taking a class that uses Java, and I've never been very familiar with Java, I decided to use this as an excuse to develop a new chess engine in Java. I ended up getting to the point where this engine could play fully-legal chess with a barebones material evaluation (https://github.com/algerbrex/Fork/tree/dev), at which point I decided to stop and just port what I learned over to Blunder's codebase as part of another refactoring. I may re-visit this engine in the future.

So far the refactoring is looking promising. Blunder 8.5.5's Perft speed with hashing clocks in at about 15-16 Mnps on my machine (AMD Ryzen 7 4700U). Blunder 9.0.0's (which is what this new release will be whenever it comes out) Perft speed with hashing, clocks in at about 20 Mnps. And this jumps to 22 Mnps when I enable code to compute pinned pieces, which allows the move generator to be more conservative with its calls to sqIsAttacked, since not every move is being blindly tested for legality. Additionally, this speed increase translates to shaving off ~50 seconds on Perft(7), going from ~200 seconds to ~150 seconds.

Of course, move generation speed contributes little to overall Elo in the long run, but it's still quite satisfying to speed up the move generation, and it's a nice first step

Now that the refactored move generation has been verified to be correct against my usual Perft testing suite, the next step going forward will be to implement a barebones evaluation and search routine, and build from there, testing each feature.

Addtionally, the gradient descent tuner will be one of the next things I (re)-write. For Blunder 9.0.0 I'd like to have the evaluation be as a orginal as possible, creating and using tuning data only from Blunder 9.0.0's initial barebones evaluation, which will just be default piece values and very simple PSQT's written by me. I anticpate this aspect of the re-write will be one of the most challenging and time consuming, since I'm going to have to incrementally build up the quality of the evaluation by going through several data-generation and data-tuning cycles. But I'm in no rush, since I'll be working on the re-write during my spare time between classes.

My goal would be to have Blunder 9.0.0 released around late May/early June, but it very well could be much later or earlier. It all depends on how busy I become this semester and how well I balance using my school laptop for testing while avoiding burning out its CPU.

[Chessqueen]

Awesome! Absolutely inspiring! Now I want to explore NN based evaluation in my own engine immediately, too!

Thanks! I hope you do, I'm sure you have some good ideas to try out.

What was discouraging me so far was that I thought you'd need millions or even billions of positions and quite a lot of time (or optimized code) to deal with these huge amouts of data. But you achieved a useful eval with only 100k positions and 10 epochs? That's even less data than what you'd use to "train" PSQ tables with!

Why did you start with downloading games from the Lichess db though? Couldn't you create 100k positions with Blunder quite quickly through selfplay?

Yep. Again, re-iterating, the network is nowhere near something strong enough to publish. But also, as I said, it still worked as a very crude evaluation function.

The game I showed took the NN plugged into Blunder dev, so of course, the strength drop from the static eval is quite dramatic. But of course, I think the classic rule of thumb applies here: I spent months carefully tuning and tweaking the balance between the static HCE and the search, especially with things like pruning margins. So when I significantly change the evaluation, even if it's better, I'd expect to see an Elo drop.

I used the Lichess games because I was being lazy for the most part. I could've fairly quickly generated 100K positions, but I had seen many other engines had started with using Lichess, so I decided to go the same route. And it's seemed to work well for the most part.

I've recently found a ton of improvement on the NN scheme by actually reducing the size of the network to 768 -> 16 -> 1. Just 16 nodes in the hidden layer. Apparently the accuracy gained with a bigger net wasn't worth it with the speed drop it brought.

After a little thinking, I realized when computing the activation between the input layer and first hidden layer, the majority of the inputs were zero, so I wasted a ton of time in my matrix multiplication code by going over entries that were zero and would zero out a matrix column anyway. So I switched just the input to being a sparse array and speed up my code over 90+%. The engine went from searching to only about a depth of 5/6, to searching around 16/18, and actually the majority of the time, it matched the same depth as the HCE evaluation. So that's pretty exciting. If I can get the power of NN with only a small speed drop, that would be great.

Right now I'm going to be experimenting with how many hidden layers to use and what their sizes should be. Once I feel I have something interesting, I'm basically going to strip Blunder's search down and build it back up, at least the parts very dependent on the old eval, like static null-move pruning.

Dragon 3.2 Sacrificed a Rook on the 2nd move and still destroyed Blunder
[pgn][Event "Blunder = Top GM"]
[Site "DESKTOP-OFQ3C0P"]
[Date "2023.02.28"]
[Round "?"]
[White "Dragon-3.2-64bit-avx2"]
[Black "Blunder-8.5.5-popcnt"]
[Result "1-0"]
[BlackElo "2750"]
[ECO "A00"]
[Opening "Ware (Meadow Hay) Opening"]
[Time "19:33:24"]
[WhiteElo "3535"]
[TimeControl "0+3"]
[Termination "normal"]
[PlyCount "110"]
[WhiteType "program"]
[BlackType "program"]

1. a4 e6 {(e7-e6 e2-e3 Qd8-h4 Qd1-f3 Ng8-f6 Qf3-g3 Qh4xg3 h2xg3 Nb8-c6
Rh1-h4 d7-d5 Nb1-c3 Bf8-b4 Bf1-b5 Bb4xc3 g3-g4 Nf6-e4 g4-g5 Bc3xb2 Rh4xe4
Bb2xa1 Bb5xc6+ b7xc6) +0.05/23 1} 2. Ra3 Bxa3 {(Bf8xa3 Nb1xa3 Ng8-f6 Ng1-f3
O-O e2-e3 d7-d6 Bf1-e2 e6-e5 O-O Bc8-g4 h2-h3 Bg4-f5 d2-d3 Nb8-c6 Na3-c4)
+1.84/15 30} 3. Nxa3 {(Nb1xa3 Ng8-f6 Ng1-f3 d7-d5 b2-b3 O-O e2-e3 c7-c5
Bc1-b2 Qd8-e7 d2-d4 b7-b6 Bf1-e2 Bc8-a6 c2-c4 Rf8-d8 O-O Nb8-c6 Nf3-e5
Ba6-b7 Be2-d3 Nc6-b4 Bd3-b1 Ra8-c8 Qd1-e2 c5xd4 e3xd4 Bb7-a8 Na3-b5 d5xc4
b3xc4 a7-a6) -1.87/30 29} e5 {(e6-e5 e2-e4 Nb8-c6 Ng1-f3 Ng8-f6 Na3-c4
d7-d6 Bf1-d3 Nc6-b4 O-O Bc8-d7 Nc4-a5 Ra8-b8 Na5-c4 O-O) +1.13/15 5} 4. d4
{(d2-d4 d7-d6 d4xe5 d6xe5 Qd1xd8+ Ke8xd8 e2-e4 Bc8-e6 Ng1-e2 Ng8-f6 f2-f3
Nb8-c6 h2-h4 h7-h5 Ne2-c3 Kd8-d7 Ke1-f2 Nf6-e8 Nc3-d5 f7-f6 Bc1-e3 Ra8-d8
Bf1-b5 a7-a6 Bb5xc6+ Kd7xc6 Nd5-b4+ Kc6-d7 a4-a5 Kd7-e7) -1.67/24 5} e4
{(e5-e4 e2-e3 Ng8-f6 Ng1-e2 d7-d5 h2-h3 O-O Ne2-g3 Nb8-c6 c2-c4 Nc6-e7
c4xd5 Ne7xd5 Na3-c4 a7-a5 Nc4-d2 Rf8-e8) +1.04/17 4} 5. d5 {(d4-d5 d7-d6
e2-e3 Ng8-f6 Na3-b5 Bc8-d7 b2-b3 O-O Bc1-b2 Bd7xb5 Bf1xb5 a7-a6 Bb5-e2
c7-c6 d5xc6 Qd8-a5+ Qd1-d2 Nb8xc6 Ng1-h3 d6-d5 Qd2xa5 Nc6xa5 Ke1-d2 Rf8-d8
Rh1-d1 Na5-c6 Kd2-c1 Ra8-c8) -1.37/26 4} Nf6 {(Ng8-f6 Na3-c4 O-O d5-d6
Nb8-c6 Bc1-f4 c7xd6 Bf4xd6 Nc6-e7 e2-e3 b7-b6 Ng1-e2 Bc8-b7 h2-h3 Ra8-c8)
+1.21/15 5} 6. d6 {(d5-d6 O-O Bc1-f4) -1.19/24 5} O-O {(O-O Bc1-f4 Nf6-e8
Na3-b5 c7xd6 Nb5xd6 Ne8xd6 Bf4xd6 Rf8-e8 e2-e3 Qd8-f6 c2-c3 Nb8-c6 Ng1-e2
Re8-e6 Bd6-c5) +1.17/16 5} 7. Bf4 {(Bc1-f4 c7xd6) -1.17/25 4} c6 {(c7-c6
e2-e3 Nb8-a6 c2-c3 Na6-c5 Na3-c4 b7-b5 a4xb5 c6xb5 Nc4-e5 Qd8-b6 Bf1-e2
Bc8-b7 Ng1-h3 Bb7-d5 b2-b4 Nc5-b3) +1.12/17 5} 8. e3 {(e2-e3 Nb8-a6)
-1.30/22 4} Na6 {(Nb8-a6 Bf1xa6 Qd8-a5+ c2-c3 Qa5xa6 Ng1-e2 b7-b6 O-O
Qa6-d3 Ne2-g3 Qd3xd1 Rf1xd1 Bc8-a6 c3-c4 Rf8-e8 Ng3-f5 Nf6-g4 Nf5-e7+
Kg8-f8 h2-h3) +1.09/18 5} 9. Bxa6 {(Bf1xa6 Qd8-a5+) -1.49/21 4} Qa5+
{(Qd8-a5+ c2-c3 Qa5xa6 Ng1-e2 Rf8-e8 O-O Qa6-d3 Ne2-d4 Qd3xd1 Rf1xd1 b7-b6
Na3-c4 Nf6-h5 b2-b4 Nh5xf4 e3xf4 Bc8-a6 b4-b5 c6xb5 a4xb5 Re8-c8 Nc4-e3)
+1.12/19 5} 10. c3 {(c2-c3 b7xa6 Ng1-e2 Ra8-b8 b2-b4 Qa5-h5 Na3-c4 a6-a5
Nc4xa5 Bc8-a6 Ne2-g3 Qh5-g6 h2-h4 Nf6-d5 h4-h5 Qg6-e6 h5-h6 g7-g5 Bf4xg5
f7-f6 Bg5-f4 Nd5xc3 Qd1-d4 Nc3-d5 Na5xc6 d7xc6 Qd4xa7 Ba6-b7 O-O Nd5xf4)
-1.24/24 4} Qxa6 {(Qa5xa6 Ng1-e2 Rf8-e8 O-O Qa6-d3 Ne2-d4 Qd3xd1 Rf1xd1)
+1.17/20 4} 11. Be5 {(Bf4-e5 Nf6-d5 Ng1-e2 Rf8-e8 Be5-d4 Qa6-d3 Qd1xd3
e4xd3 Ne2-g3 Re8-e6 c3-c4 Nd5-f6 c4-c5 b7-b6 Ke1-d2 b6xc5 Bd4xc5 Ra8-b8
b2-b4 a7-a5 Rh1-b1 a5xb4 Na3-c4 b4-b3 Nc4-b6 Bc8-a6 Rb1xb3) -1.08/23 4} Nd5
{(Nf6-d5 Be5-d4 Rf8-e8 Qd1-g4 g7-g6 h2-h4 c6-c5 Bd4xc5 Qa6xa4 h4-h5)
+1.02/19 4} 12. Ne2 {(Ng1-e2 Rf8-e8 Be5-g3) -1.05/23 5} Re8 {(Rf8-e8 Be5-d4
Qa6-d3 Qd1xd3 e4xd3 Ne2-c1 Re8-e6 Nc1xd3 Re6xd6 Na3-c4 Rd6-e6 O-O b7-b5
a4xb5 c6xb5 Nc4-e5 a7-a5) +1.16/16 4} 13. Bg3 {(Be5-g3 Qa6-b6) -1.13/24 4}
b6 {(b7-b6 Qd1-b3 Bc8-b7 h2-h3 Re8-f8 Na3-c4 b6-b5 Nc4-d2 Ra8-e8 a4xb5
Qa6-a1+ Qb3-d1 Qa1xd1+ Ke1xd1 c6xb5 Kd1-c2 a7-a5 Rh1-a1 a5-a4 Ne2-d4 Bb7-a6
Nd4-f5) +1.15/18 5} 14. Nd4 {(Ne2-d4 Bc8-b7) -1.34/22 4} Qd3 {(Qa6-d3
Qd1xd3 e4xd3 Nd4-f3 Bc8-a6 c3-c4 Nd5-f6 O-O Re8-b8 Rf1-d1 b6-b5 a4xb5 c6xb5
c4xb5 Ba6xb5 Na3xb5 Rb8xb5 Nf3-e5 Rb5xb2 Ne5xd3) +1.31/18 4} 15. Qxd3
{(Qd1xd3 e4xd3 Ke1-d2 Bc8-b7 c3-c4 c6-c5 Nd4-f5 g7-g6 c4xd5 g6xf5 Na3-b5
Bb7xd5 Nb5-c7 Bd5-c6 Rh1-a1 Ra8-c8 Nc7xe8 Rc8xe8 f2-f3 c5-c4 Ra1-c1 Bc6-d5
Bg3-f4 Kg8-g7 Kd2-c3 Kg7-f6 Rc1-g1 a7-a5 h2-h4 Bd5-e6) -0.45/24 4} exd3
{(e4xd3 Ke1-d2 Bc8-a6 c3-c4 Nd5-b4 Nd4-f3 c6-c5 Nf3-e5 Ba6-b7 f2-f3 Nb4-c6
Ne5xd3 Nc6-a5 Nd3-e5 Bb7-c6 Ne5xc6 Na5xc6 Na3-c2 a7-a5) +0.76/18 4} 16. Kd2
{(Ke1-d2 Bc8-b7) -0.49/24 4} Ba6 {(Bc8-a6 c3-c4 Nd5-b4 Nd4-f3 Ba6-b7 Nf3-e5
h7-h5 Ne5xd3 Nb4xd3 Kd2xd3 Re8-e6 h2-h4 c6-c5 f2-f3 Re6-g6 Rh1-h3 a7-a6
Na3-b1 Ra8-e8 Nb1-c3 Bb7-c6) +0.78/20 5} 17. c4 {(c3-c4 c6-c5) -0.46/24 5}
Nb4 {(Nd5-b4 Nd4-f3 Ba6-b7 Nf3-e5 c6-c5 f2-f3 Bb7-c6 Na3-b5 Bc6xb5 a4xb5
a7-a6 b5xa6 Ra8xa6 Ne5xd3 Nb4-c6 h2-h3 Ra6-a2 Rh1-c1 h7-h6 Kd2-e2) +0.73/20
5} 18. Nf5 {(Nd4-f5 Kg8-f8 f2-f3 g7-g6 Nf5-e7 Re8xe7 d6xe7+ Kf8xe7 e3-e4
d7-d6 Bg3-f4 Ke7-d7 g2-g4 Ra8-g8 Rh1-g1 g6-g5 Bf4-g3 Rg8-g6 Rg1-f1 d6-d5
Kd2-c3 Nb4-c2 Na3xc2 d3xc2 b2-b3 d5xc4 b3xc4) -0.08/25 4} Re4 {(Re8-e4
Nf5-e7+ Kg8-f8 Kd2-c3 c6-c5 Rh1-a1 g7-g6 Na3-b5 Ba6xb5 a4xb5 Kf8-g7 Ne7-d5
Nb4xd5+ c4xd5 c5-c4 Ra1-a4 Kg7-f6 Ra4xc4 Re4xc4+ Kc3xc4) +1.63/16 5} 19. f3
{(f2-f3 Re4-e6 Bg3-f4 h7-h5 e3-e4 f7-f6 h2-h4 Kg8-f7 b2-b3 Ba6-b7 Nf5-e7
Ra8-h8 Na3-b1 a7-a5 Nb1-c3 g7-g6 Nc3-d1 Bb7-a6 Nd1-b2 b6-b5) +0.09/21 4}
Re6 {(Re4-e6 Nf5-d4 Re6-g6 Nd4-f5 Rg6-g5 Nf5-e7+ Kg8-f8 Kd2-c3 c6-c5)
+1.68/18 5} 20. h4 {(h2-h4 h7-h5 e3-e4 f7-f6 Bg3-f4 Kg8-f7 b2-b3 g7-g6
Nf5-e7 Ba6-b7 Na3-b1 Re6xe7 d6xe7 Kf7xe7 Nb1-c3 Ke7-e6 Bf4-g3 d7-d6 Nc3-d1
c6-c5 Nd1-f2 Ra8-g8 Nf2xd3 Nb4xd3 Kd2xd3 g6-g5 h4xg5) +0.12/24 4} h5
{(h7-h5 Nf5-e7+ Kg8-h7 Kd2-c3 c6-c5 e3-e4 Ra8-b8 Na3-b5 Ba6xb5 a4xb5 Rb8-d8
Rh1-a1 Rd8-a8 Kc3-d2 Re6-h6) +1.62/15 4} 21. b3 {(b2-b3 Kg8-f8) +0.10/24 4}
g6 {(g7-g6 Nf5-e7+ Kg8-g7 Rh1-c1 f7-f5 c4-c5 Ra8-b8 Bg3-f4 Rb8-d8 c5xb6
a7xb6 Na3-c4 Rd8-b8) +1.73/16 5} 22. Ne7+ {(Nf5-e7+ Kg8-f8) +0.10/26 4} Kg7
{(Kg8-g7 Na3-b1 f7-f5 Nb1-c3 Ra8-f8 Rh1-f1 Ba6-b7 Nc3-d1 Rf8-f6 Nd1-f2
Re6xd6 Bg3xd6 Rf6xd6 Kd2-c3 c6-c5 e3-e4 Rd6-e6 Ne7-d5 Bb7xd5 c4xd5)
+1.53/17 4} 23. e4 {(e3-e4 f7-f5 e4-e5 Re6xe7 d6xe7 Kg7-f7 Bg3-f4 Kf7xe7
Na3-b1 Ke7-e6 Nb1-c3 Ra8-b8 Rh1-h3 Rb8-g8 Rh3-g3 Ke6-f7 Rg3-g5 Rg8-h8
Nc3-d1 b6-b5 Nd1-b2 b5xc4 b3xc4 c6-c5 Nb2xd3 Ba6xc4 e5-e6+ Bc4xe6 Nd3-e5+
Kf7-f6 Rg5xg6+ Kf6-e7) +0.32/24 4} Bc8 {(Ba6-c8 c4-c5 Bc8-a6 Bg3-f2 Nb4-d5
Bf2-d4+ Nd5-f6 Na3-c4 Ba6xc4 b3xc4 b6xc5 Bd4xc5 Nf6-e8 Kd2xd3 Ne8xd6 Rh1-b1
Kg7-f6 Bc5xd6 Re6xd6+) +1.58/16 4} 24. Nb1 {(Na3-b1 f7-f5 e4-e5 Bc8-b7
Nb1-c3 Kg7-f7 Bg3-f4 Re6xe7 d6xe7 Kf7xe7 Nc3-d1 Ra8-e8 Nd1-f2 c6-c5 Rh1-d1
Bb7-c6 Nf2xd3 Nb4xd3 Kd2xd3 Ke7-f7 Rd1-d2 Re8-e6 Kd3-e3 Kf7-e7 Bf4-g5+
Ke7-e8 Rd2-d1) +0.50/24 4} Bb7 {(Bc8-b7 Nb1-c3 Ra8-f8 Nc3-d1 c6-c5 Nd1-b2
f7-f5 e4-e5 f5-f4 Bg3-f2 Re6xe5 Nb2xd3 Nb4xd3 Kd2xd3) +1.52/13 3} 25. Nc3
{(Nb1-c3 Kg7-f8) +0.45/23 2} Rf8 {(Ra8-f8 a4-a5 f7-f5 e4xf5 g6xf5 a5xb6
a7xb6) +1.51/16 2} 26. Bf4 {(Bg3-f4 a7-a5 Nc3-d1 f7-f6 Nd1-f2 c6-c5 Nf2xd3
Rf8-e8 Ne7-d5 f6-f5 Nd5xb4 f5xe4 Nb4-d5 e4xd3 Nd5-c7 Kg7-f7 Nc7xe8 Kf7xe8
Kd2xd3 Bb7-c6 Rh1-h3 Re6-f6 Kd3-e3 Rf6-e6+ Ke3-d2 Re6-f6) +0.58/24 2} a5
{(a7-a5 Rh1-c1 Rf8-e8 Kd2-e3 Bb7-a6 Bf4-g3 Re8-f8) +1.74/12 2} 27. Nd1
{(Nc3-d1 Rf8-e8) +0.46/24 2} c5 {(c6-c5 Nd1-f2 Nb4-c6 Nf2xd3 f7-f6 Ne7xc6
Bb7xc6) +0.45/14 2} 28. Ne3 {(Nd1-e3 Nb4-c6 Ne7-d5 f7-f5 e4xf5 g6xf5 Nd5xb6
Rf8-f7 Nb6-d5 Rf7-f8 Rh1-e1 Nc6-d4 Kd2xd3 Kg7-h7 Nd5-c7 Re6-g6 Ne3-d5
Bb7xd5 c4xd5 Rg6xg2 Re1-e7+ Kh7-g6 Re7xd7 Rf8-b8 Nc7-b5 Nd4xf3 Rd7-e7
Rg2-g4 Re7-e6+ Kg6-f7) +1.19/24 2} f5 {(f7-f5 e4xf5) +0.76/17 2} 29. exf5
{(e4xf5 g6xf5 Rh1-h3 Rf8-f6 Rh3-g3+ Kg7-f7 Rg3-g5 Re6xe3 Kd2xe3 Rf6-e6+
Ke3-f2 Re6-e2+ Kf2-f1 Nb4-c2 Rg5xh5 Re2-e1+ Kf1-f2 Re1-e2+ Kf2-g3 Nc2-e1
Kg3-h3 d3-d2 Rh5-h7+ Kf7-f6 Bf4xd2 Re2xd2 Ne7-g8+ Kf6-g6 Rh7xd7 Ne1xg2
Kh3-g3 Bb7-a8 Rd7-a7 f5-f4+ Kg3-g4 Ba8xf3+ Kg4xf3 Ng2xh4+ Kf3-g4) +0.76/25
2} gxf5 {(g6xf5 Ne3xf5+ Kg7-f7 Nf5-g3 Kf7-e8 Bf4-g5 Rf8-h8 Rh1-b1 Ke8-f7
Bg5-f4 Kf7-g7 Kd2-c3 Kg7-f6 Rb1-d1 Kf6-f7 Kc3-b2 Kf7-f6 Ng3-f5) +0.71/17 2}
30. Rh3 {(Rh1-h3 Kg7-f7) +1.07/25 2} Kf7 {(Kg7-f7 Ne7xf5 Bb7-c6 Kd2-c3
Bc6-a8 Rh3-g3 Re6-g6 Rg3-g5 Rg6xg5 h4xg5 Ba8-c6 Bf4-e5 Rf8-e8 Nf5-e7 h5-h4)
+0.75/15 2} 31. Rg3 {(Rh3-g3 Nb4-c2 Ne3xc2 d3xc2 Rg3-g5 Rf8-h8 Ne7xf5
Rh8-h7 Kd2xc2 Re6-e2+ Kc2-c3 Re2-e6 Kc3-d2 Re6-g6 Kd2-d3 Rg6xg5 h4xg5 h5-h4
Nf5-e7 Rh7-g7 Kd3-e2 Bb7-a8 Ke2-f2 Ba8-b7 Kf2-g1 h4-h3) +1.43/28 2} Rh8
{(Rf8-h8 Rg3-g5 Rh8-h7 Kd2-c3 Rh7-g7 Rg5xh5 Re6xe3 Bf4xe3 Rg7xg2 Be3-d2
f5-f4 Rh5-g5 Bb7xf3 Rg5xg2 Bf3xg2 Bd2xf4 Bg2-f3) +0.20/16 2} 32. N7xf5
{(Ne7xf5 Re6-g6) +1.49/25 2} Rg6 {(Re6-g6 Rg3-g5 Rh8-h7 Rg5xg6 Kf7xg6
Bf4-e5 Kg6-f7 Be5-c3 Kf7-e6 Bc3xb4 a5xb4 Kd2xd3 Rh7-f7 Nf5-g3 Rf7-f4 Ng3xh5
Rf4-d4+ Kd3-e2 Ke6xd6) +0.15/16 2} 33. Rg5 {(Rg3-g5 Nb4-c6 Ne3-d5 Rh8-e8
Bf4-e3 Rg6xg5 h4xg5 Nc6-e5 Nd5xb6 Bb7-c6 Be3xc5 Kf7-g6 Nf5-e7+ Kg6xg5
Bc5-e3+ Kg5-f6 Be3-d4 Kf6-e6 c4-c5 Bc6xf3 Bd4xe5 Bf3xg2 Be5-g3 Bg2-e4
Kd2-e3 Re8-f8 Bg3-e1 Be4-g2) +2.08/26 2} Rxg5 {(Rg6xg5 h4xg5) -0.27/16 2}
34. hxg5 {(h4xg5 Nb4-c6 Ne3-d5) +2.47/24 2} Ke6 {(Kf7-e6 Nf5-e7 Rh8-f8
g5-g6 Ke6-f6 Ne3-f5 Rf8-b8 g6-g7 Rb8-a8) -0.51/16 2} 35. Ne7 {(Nf5-e7
Nb4-c6 Ne3-d5 Nc6xe7 Nd5xe7 Rh8-h7 Kd2xd3 Rh7-g7 g5-g6 Ke6-f6 Bf4-g3 Rg7xg6
Bg3-h4+ Kf6-f7 Ne7xg6 Kf7xg6 Bh4-d8 Kg6-f5 Kd3-e3 Kf5-e6 Bd8-c7 Ke6-e5
Bc7xb6 Ke5xd6 Bb6xa5 Kd6-e5 Ba5-c7+ Ke5-e6 Bc7-b6 d7-d6 Ke3-f4 Ke6-f6 a4-a5
Bb7-a6 Bb6-c7 Kf6-e6 Kf4-g5 d6-d5 Kg5xh5 d5xc4 b3xc4 Ke6-d7 Bc7-b6 Ba6xc4
g2-g4) +3.64/28 2} h4 {(h5-h4 g5-g6) -0.82/15 2} 36. g6 {(g5-g6 Rh8-b8
Bf4-g5 h4-h3 g2xh3 Bb7xf3 g6-g7 Ke6-f7 Ne3-f5 Rb8-a8 h3-h4 Kf7-e6 Nf5-h6
Ke6xd6 g7-g8Q Ra8xg8 Nh6xg8 Nb4-c2 Ne7-d5 Nc2-d4 Kd2xd3 Kd6-e6 Ng8-f6
Ke6-f5 Nf6xd7 Bf3-h5 Nd5xb6) +3.95/24 2} Ra8 {(Rh8-a8 Ne3-g4 Nb4-c6 Ne7-d5
Ra8-b8 Ng4-h6 Nc6-e5 g6-g7 Bb7xd5 c4xd5+ Ke6xd5 g7-g8R Rb8xg8 Nh6xg8 Kd5xd6
Ng8-h6 Kd6-e6 Bf4xe5 Ke6xe5 Kd2xd3) -1.36/17 3} 37. Bg5 {(Bf4-g5 h4-h3
g2xh3 Bb7xf3 g6-g7 Ke6-f7 Ne3-f5 Nb4-c2 g7-g8Q+ Ra8xg8 Nf5-h6+ Kf7-e6
Nh6xg8 Ke6xd6 Ne7-d5 Nc2-a1 Kd2xd3 Na1xb3 Bg5-e3 b6-b5 a4xb5 a5-a4 Kd3-c3
Bf3-d1 Ng8-f6 Kd6-e6 Nf6xd7 Ke6xd7 Nd5-b6+ Kd7-c7 Nb6xa4 Nb3-d2 Na4xc5
Nd2-f3 Be3-f4+ Kc7-c8 Kc3-b4 Nf3-d4) +4.16/24 2} h3 {(h4-h3 g2xh3 Bb7xf3
g6-g7 Ke6-f7 Ne3-f5 Kf7-e6 Nf5-h4 Bf3-e2 g7-g8Q+ Ra8xg8 Ne7xg8 Ke6xd6
Nh4-f5+ Kd6-e5 Ng8-e7 Be2-f3 h3-h4 Bf3-e4 Nf5-e3 Ke5-d4) -1.01/16 2} 38.
gxh3 {(g2xh3 Bb7xf3 g6-g7 Ke6-f7 Ne3-f5 Kf7-e6 Nf5-h6 Ke6xd6 h3-h4 Ra8-e8
g7-g8Q Re8xg8 Nh6xg8 Kd6-e6 Ne7-g6 Nb4-c2 Ng6-f4+ Ke6-f7 Ng8-h6+ Kf7-g7
Nh6-f5+ Kg7-h7 Nf4xd3 Nc2-a1 Nd3-e5 Bf3-h5 Kd2-e3 Na1xb3 Ne5xd7 Kh7-g6
Ke3-f4 Nb3-d2 Nd7xb6 Kg6-f7 Nf5-g3 Bh5-d1) +4.37/25 2} Nc6 {(Nb4-c6 Ne3-d5
Nc6xe7 Nd5xe7 Bb7xf3 g6-g7 Ke6-f7 g7-g8B+ Ra8xg8 Ne7xg8 Kf7xg8 Kd2xd3
Kg8-f7 Bg5-d8 Kf7-e6 Bd8xb6 Ke6xd6 Bb6xa5 Kd6-e5) -1.68/17 3} 39. f4
{(f3-f4 Nc6-d4 Ne7-d5 Ra8-g8 h3-h4 Rg8xg6 f4-f5+ Nd4xf5 Nd5-f4+ Ke6xd6
Ne3xf5+ Kd6-e5 Nf4xg6+ Ke5xf5 Ng6-e7+ Kf5-g4 Ne7-d5 d7-d6 Nd5xb6 Bb7-c6
Bg5-d8 Kg4-h5 Nb6-d5 Bc6-a8 Kd2xd3 Ba8-b7 Kd3-e3 Bb7-c8 Ke3-f4 Bc8-e6)
+5.61/21 2} Nxe7 {(Nc6xe7 d6xe7 Bb7-e4 Ne3-d5 Be4xd5 c4xd5+ Ke6-f5 g6-g7
Kf5-g6 h3-h4 Kg6xg7 f4-f5 Kg7-f7 Kd2xd3 Ra8-e8 d5-d6 Re8-c8 h4-h5 Rc8-g8
Bg5-e3 Rg8-g2) -2.05/19 2} 40. dxe7 {(d6xe7 Bb7-e4 f4-f5+ Be4xf5 Ne3-d5
Ke6-d6 Bg5-f4+ Kd6-e6 Nd5-c7+ Ke6xe7 Bf4-g5+ Ke7-f8 Nc7xa8 d7-d6 Bg5-h6+
Kf8-g8 Na8xb6 Bf5xg6 Nb6-d5 Kg8-h7 Bh6-g5 Bg6-f5 h3-h4 Bf5-h3 Bg5-d8 Bh3-c8
Bd8xa5 Kh7-h6 Ba5-c7 Kh6-h5 Kd2xd3 Bc8-f5+ Kd3-d2 Bf5-c8 Kd2-e3 Bc8-a6
Bc7-d8 Kh5-h6 Ke3-e4 Kh6-g6 h4-h5+ Kg6xh5 Bd8-c7 Ba6-c8) +6.33/25 2} Be4
{(Bb7-e4 Ne3-d5 Be4xd5 c4xd5+ Ke6-f5 g6-g7 Kf5-g6 h3-h4 Kg6xg7 f4-f5 Kg7-f7
Kd2xd3 Ra8-e8 d5-d6 Re8-h8 Kd3-c4 Rh8-c8 Kc4-b5 Rc8-b8 f5-f6 Kf7-e6 h4-h5
c5-c4 Kb5xc4 Ke6xd6) -2.28/22 3} 41. f5+ {(f4-f5+ Be4xf5 Ne3-d5 Ke6-d6
Bg5-f4+ Kd6-e6 Nd5-c7+ Ke6xe7 Bf4-g5+ Ke7-f8 Nc7xa8 Kf8-g7 h3-h4 Bf5-e4
Na8xb6 Be4-b7 h4-h5 Bb7-f3 h5-h6+ Kg7xg6 Nb6xd7 Bf3-e4 Nd7-f6 Be4-f5 h6-h7
Kg6-g7 Bg5-h6+ Kg7-h8 Bh6-f8 Bf5-h3 Bf8xc5 Bh3-f5 Bc5-d4 Kh8-g7 Bd4-c3
Bf5-g6 Bc3xa5) +6.97/23 2} Bxf5 {(Be4xf5 Ne3-d5 Ra8-g8 Nd5-c7+ Ke6-e5
e7-e8Q+ Rg8xe8 Nc7xe8 Bf5xg6 Ne8-f6 Bg6-f5 Nf6-d5 Ke5-e4 Bg5-d8 Bf5xh3
Bd8xb6 Bh3-e6 Nd5-c3+ Ke4-f3 Kd2xd3 Be6-f5+) -2.24/16 2} 42. Nd5 {(Ne3-d5
Ra8-g8 e7-e8R+ Rg8xe8 Nd5-c7+ Ke6-e5 Nc7xe8 Bf5xg6 Ne8-c7 Bg6-f5 h3-h4
d7-d6 Nc7-d5 Bf5-e4 Bg5-d8 Ke5-e6 Bd8xb6 Be4-f3 Bb6-c7 Ke6-d7 Bc7xa5 Bf3-e2
Ba5-b6 Kd7-c6 Nd5-f6 Kc6-b7 h4-h5 Be2xh5 Nf6xh5 Kb7-c6 Bb6-a5 d6-d5 Kd2xd3)
+7.11/26 2} Bxg6 {(Bf5xg6 Nd5-c7+ Ke6-f5 Nc7xa8 Kf5xg5 Na8xb6 Kg5-f6
Nb6xd7+ Kf6xe7 Nd7xc5 Bg6-f5 h3-h4 Ke7-f6 Nc5xd3 Bf5-e4) -2.94/18 3} 43.
Nc7+ {(Nd5-c7+ Ke6-d6 Nc7xa8 Kd6-c6 e7-e8Q Bg6xe8 Bg5-d8 d7-d5 c4xd5+
Kc6-d6 Na8xb6 c5-c4 b3xc4 Kd6-c5 Kd2xd3 Kc5-b4 Bd8-e7+ Kb4-b3 Nb6-a8 Be8xa4
h3-h4 Ba4-e8 Na8-c7 Be8-g6+ Kd3-d4 a5-a4 Be7-c5 a4-a3 Bc5xa3 Bg6-h5 d5-d6
Bh5-g4 c4-c5 Kb3-c2 Nc7-a8 Kc2-d2 Kd4-d5 Kd2-c2) +7.32/24 2} Kf5 {(Ke6-f5
Nc7xa8 Kf5xg5 Na8xb6 Kg5-f6 Nb6xd7+ Kf6xe7 Nd7xc5 Bg6-f5 h3-h4 Bf5-g4
Nc5xd3 Ke7-d6 c4-c5+ Kd6-d5 c5-c6 Kd5-d6 b3-b4 a5xb4 Nd3xb4 Bg4-f3 a4-a5
Bf3xc6 a5-a6 Bc6-d5 a6-a7 Bd5-e4) -3.03/22 3} 44. Nxa8 {(Nc7xa8 Kf5xg5
Na8-c7 Kg5-f6 e7-e8Q Bg6xe8 Nc7xe8+ Kf6-e5 Kd2xd3 d7-d5 c4xd5 Ke5xd5 h3-h4
Kd5-e6 Ne8-c7+ Ke6-f6 Nc7-a8 Kf6-g6 Na8xb6 Kg6-f6 Nb6-c4 Kf6-e6 h4-h5
Ke6-f7 Nc4xa5) +9.26/22 2} Kxg5 {(Kf5xg5 Na8xb6 Bg6-e8 Kd2xd3 Kg5-f6
Nb6-d5+ Kf6-f7 h3-h4 Kf7-e6 Kd3-e3 Be8-f7 h4-h5 Bf7xh5 Nd5-f4+ Ke6xe7
Nf4xh5 Ke7-e6 Ke3-e4 d7-d6 Nh5-f4+ Ke6-d7 Ke4-f5 Kd7-e7 Nf4-d5+ Ke7-f7
Kf5-f4 Kf7-e6) -3.16/25 3} 45. Nc7 {(Na8-c7 Bg6-f5 e7-e8Q Bf5xh3 Nc7-d5
Bh3-e6 Nd5xb6 Kg5-f4 Nb6xd7 Be6xc4 b3xc4 Kf4-g4 Nd7xc5 Kg4-h4 Nc5xd3 Kh4-g4
Qe8-e4+ Kg4-h3 Qe4-h7+ Kh3-g2) +10.69/20 2} Kf4 {(Kg5-f4 e7-e8R Bg6xe8
Nc7xe8 Kf4-g3 Ne8-f6 d7-d6 Kd2xd3 Kg3xh3 Nf6-e4 Kh3-g4 Ne4xd6 Kg4-f4 Nd6-c8
Kf4-e5 Nc8xb6 Ke5-e6 Kd3-e4 Ke6-d6 Nb6-d5 Kd6-e6) -3.95/22 3} 46. e8=Q
{(e7-e8Q Bg6xe8 Nc7xe8 Kf4-f5 Kd2xd3 Kf5-e5 h3-h4 d7-d5 h4-h5 d5xc4+ Kd3xc4
b6-b5+ Kc4xb5 Ke5-d4 Kb5-b6 c5-c4 b3xc4 Kd4xc4 Kb6xa5 Kc4-c5 h5-h6 Kc5-d4
Ne8-c7 Kd4-e5) +10.89/20 2} Bxe8 {(Bg6xe8 Nc7xe8 Kf4-g3 Ne8-f6 d7-d6
Nf6-e4+ Kg3xh3 Kd2xd3 Kh3-g4 Ne4xd6 Kg4-f4 Nd6-c8 Kf4-e5 Nc8xb6 Ke5-e6
Kd3-e4 Ke6-d6 Nb6-d5 Kd6-e6 Nd5-c3 Ke6-d6 Ke4-f5 Kd6-c6 Kf5-f6 Kc6-d6
Nc3-e4+ Kd6-c6 Kf6-g6 Kc6-b6 Kg6-f6) -4.12/26 2} 47. Nxe8 {(Nc7xe8 Kf4-g5
Kd2xd3 Kg5-g6 h3-h4 Kg6-f5 Ne8-c7 Kf5-f4 Nc7-d5+ Kf4-e5 Nd5xb6 d7-d6 Nb6-c8
Ke5-f5 Nc8xd6+ Kf5-f4 Nd6-b7 Kf4-g4 h4-h5 Kg4xh5 Nb7xc5 Kh5-g4 Kd3-e4
Kg4-g5 Ke4-e5 Kg5-g4 Ke5-d6 Kg4-f3 Nc5-e6 Kf3-g4 c4-c5 Kg4-g3) +11.90/21 2}
Kg3 {(Kf4-g3) -4.13/27 3} 48. Kxd3 {(Kd2xd3 Kg3xh3 Ne8-f6 Kh3-g3 Kd3-e4
d7-d6 Ke4-d5 Kg3-f3 Kd5xd6 Kf3-e2 Nf6-d7 Ke2-d3 Nd7xb6 Kd3-d4 Nb6-d7 Kd4-c3
Nd7xc5 Kc3-b4 Nc5-d7 Kb4xb3 Nd7-b6 Kb3-c3 c4-c5 Kc3-b3 Kd6-c7) +11.25/21 2}
Kxh3 {(Kg3xh3 Ne8-f6 d7-d6 Nf6-e4 Kh3-g4 Ne4xd6 Kg4-f4 Nd6-c8 Kf4-e5 Nc8xb6
Ke5-e6 Kd3-e4 Ke6-d6 Nb6-d5 Kd6-e6 Ke4-f4 Ke6-d6 Kf4-f5 Kd6-d7 Kf5-e5
Kd7-c6 Nd5-c3 Kc6-b7 Ke5-d5 Kb7-b6 Nc3-e4 Kb6-b7 Ne4xc5+ Kb7-c7 Nc5-e6+
Kc7-d7 c4-c5) -4.95/28 3} 49. Nf6 {(Ne8-f6 d7-d6 Kd3-e4 Kh3-h4 Ke4-d5
Kh4-g5 Nf6-e4+ Kg5-g4 Kd5xd6 Kg4-f5 Kd6-d5 Kf5-f4 Ne4-f6 b6-b5 a4xb5 Kf4-f3
Kd5-c6 Kf3-e2 b5-b6 Ke2-d3 Nf6-d7 Kd3-c3 Nd7xc5 Kc3-b4 b6-b7 Kb4-a3)
+13.69/21 1} d6 {(d7-d6 Nf6-e4 Kh3-g4 Ne4xd6 Kg4-f4 Nd6-c8 Kf4-e5 Nc8xb6
Ke5-e6 Kd3-e4 Ke6-d6 Nb6-d5 Kd6-e6 Ke4-f4 Ke6-d6 Kf4-f5 Kd6-c6 Kf5-e5
Kc6-d7 Nd5-f6+ Kd7-e7 Nf6-e4) -5.68/33 2} 50. Ke4 {(Kd3-e4 Kh3-g2 Ke4-d5
Kg2-g3 Kd5xd6 Kg3-f4 Kd6-c6 Kf4-e5 Kc6xb6 Ke5-d6 Nf6-d7 Kd6-e7 Nd7xc5
Ke7-d8 Kb6-c6 Kd8-e7 Nc5-d7 Ke7-f7 Kc6-d6 Kf7-g6 Nd7-b6) +13.88/21 1} Kg2
{(Kh3-g2 Ke4-d5 Kg2-f3 Kd5xd6 Kf3-e3 Nf6-d5+ Ke3-d3 Nd5xb6 Kd3-d4 Nb6-d7
Kd4-d3 Nd7xc5+ Kd3-c3 Kd6-d7 Kc3-c2 Kd7-c6 Kc2-c3 Kc6-b5 Kc3-d4 Nc5-b7
Kd4-d3 Nb7xa5 Kd3-e4 b3-b4 Ke4-f3 c4-c5 Kf3-g3 c5-c6 Kg3-f3) -6.55/26 1}
51. Kd5 {(Ke4-d5 b6-b5 a4xb5 Kg2-f3 Kd5xd6 Kf3-f4 Kd6-c6 Kf4-f5 b5-b6
Kf5xf6 Kc6xc5 Kf6-e6 Kc5-c6 Ke6-e5 c4-c5 Ke5-e6 b6-b7 Ke6-e7 Kc6-b6 Ke7-f7
c5-c6 Kf7-f6 c6-c7 Kf6-g6 Kb6-b5 Kg6-f6 Kb5-c6 Kf6-g5 Kc6-c5 Kg5-f6 Kc5-b5
Kf6-g5) +16.38/22 1} Kf3 {(Kg2-f3) -10.85/25 1} 52. Kxd6 {(Kd5xd6 Kf3-e3
Kd6-c6 Ke3-d4 Kc6xb6 Kd4-c3 Kb6xa5 Kc3-b2 Nf6-e4 Kb2-c1 Ne4xc5 Kc1-c2
Ka5-a6 Kc2-c3 Ka6-b6 Kc3-d2 a4-a5 Kd2-e2 Nc5-e4 Ke2-e3 a5-a6 Ke3-e2 c4-c5
Ke2-e3 c5-c6 Ke3-d4 a6-a7) +16.96/23 1} Ke3 {(Kf3-e3 Nf6-d5+ Ke3-d3 Nd5xb6
Kd3-d4 Nb6-d7 Kd4-e3 Nd7xc5 Ke3-f3 Nc5-e6 Kf3-g2 c4-c5 Kg2-f2 Ne6-f4 Kf2-e3
c5-c6 Ke3-d4 Nf4-h3 Kd4-c3 c6-c7 Kc3xb3 c7-c8Q Kb3xa4) -11.07/16 1} 53. Kc6
{(Kd6-c6 Ke3-d4 Kc6xb6 Kd4-c3 Kb6xa5 Kc3-d4 Nf6-e4 Kd4-e5 Ka5-b6 Ke5-f5
a4-a5 Kf5-e5 Kb6xc5 Ke5-f5 Kc5-b6 Kf5-g6 a5-a6 Kg6-g7 c4-c5 Kg7-g6 c5-c6
Kg6-f5 c6-c7 Kf5-f4 a6-a7 Kf4-e3 a7-a8Q Ke3-d3 Qa8-e8 Kd3-e3 Kb6-c6 Ke3-f3
b3-b4 Kf3-g2 b4-b5) +19.55/23 1} Kf4 {(Ke3-f4 Kc6xb6 Kf4-f5 Nf6-d7 Kf5-e6
Nd7xc5+ Ke6-d6 Kb6-b5 Kd6-e5 Nc5-d7+ Ke5-d6 Nd7-b6 Kd6-e7 c4-c5 Ke7-d8
c5-c6 Kd8-c7 Nb6-d5+ Kc7-d6 c6-c7 Kd6xd5 Kb5xa5 Kd5-e5 c7-c8Q Ke5-d4)
-11.80/23 1} 54. Kxb6 {(Kc6xb6 Kf4-e3 Kb6xa5 Ke3-d4 Nf6-e4 Kd4-e3 Ka5-b6
Ke3-f3 Ne4xc5 Kf3-e3 a4-a5 Ke3-d4 a5-a6 Kd4-e3 Nc5-e4 Ke3xe4 a6-a7 Ke4-e5
c4-c5 Ke5-d4 c5-c6 Kd4-e5 c6-c7 Ke5-d6 b3-b4 Kd6-d7 Kb6-b7 Kd7-d6 b4-b5
Kd6-c5 b5-b6) +21.44/20 1} Kf5 {(Kf4-f5 Nf6-d7 Kf5-e6 Nd7xc5+ Ke6-d6 Kb6-b5
Kd6-e5 Kb5xa5 Ke5-d6 Ka5-b5 Kd6-c7 b3-b4 Kc7-d6 a4-a5 Kd6-e5 a5-a6 Ke5-d4
a6-a7 Kd4-e5 a7-a8Q Ke5-f4 Qa8-f8+ Kf4-e3 Qf8-f5 Ke3-e2 Qf5-d3+ Ke2-e1
Qd3-e4+ Ke1-f1 Nc5-d3 Kf1-g1 c4-c5 Kg1-h2 Qe4-e5+ Kh2-h1 c5-c6) -15.41/28
1} 55. Kxa5 {(Kb6xa5 Kf5-g6 Ka5-b5 Kg6-f7 Kb5-b6 Kf7-f8 Nf6-e4 Kf8-f7
Ne4xc5 Kf7-f8 a4-a5 Kf8-e7 Nc5-e4 Ke7-d7 c4-c5 Kd7-e6 a5-a6 Ke6-e5 c5-c6
Ke5xe4 a6-a7 Ke4-d4 c6-c7 Kd4-c3 b3-b4 Kc3-d4 Kb6-c6 Kd4-c3 b4-b5 Kc3-c2
Kc6-b6) +21.76/21 1} Kxf6 {(Kf5xf6 Ka5-b6 Kf6-e5 Kb6xc5 Ke5-e6 Kc5-c6
Ke6-e5 a4-a5 Ke5-d4 a5-a6 Kd4-c3 a6-a7 Kc3xb3 Kc6-c5) -11.18/22 0 Black
resigns} *[/pgn]

[Chessqueen]

[pgn][Event "Boot7.1 vs Blunder"]
[Site "DESKTOP-OFQ3C0P"]
[Date "2023.03.03"]
[Round "1"]
[White "Booot71_avx2"]
[Black "Blunder-8.5.5-popcnt"]
[Result "1-0"]
[BlackElo "3340"]
[ECO "A40"]
[Opening "Queen's Pawn"]
[Time "03:45:41"]
[Variation "English Defence, 2.c4 Bb7"]
[WhiteElo "3375"]
[TimeControl "0+2"]
[Termination "normal"]
[PlyCount "149"]
[WhiteType "program"]
[BlackType "program"]

1. d4 b6 2. c4 Bb7 3. Nc3 e6 4. Nf3 f5 5. g3 Nf6 6. Bg2 Bb4 7. Bd2 O-O 8.
Rc1 c5 9. a3 Bxc3 10. Bxc3 Ne4 11. O-O Qe7 12. Qd3 Na6 13. Rfd1 Rad8 14.
Be1 d5 15. cxd5 Rxd5 16. Qb1 Rfd8 17. e3 cxd4 18. Rxd4 Nac5 19. b4 Na4 20.
Rxd5 Bxd5 21. Nd4 Qd7 22. Qc2 b5 23. Qc7 a6 24. Qe5 Qd6 25. Qxd6 Rxd6 26.
Rc8+ {(Rc1-c8+ Kg8-f7 Rc8-c7+ Kf7-g6 f2-f3 Ne4-f6 h2-h3 Rd6-d7 Rc7xd7
Nf6xd7 e3-e4 f5xe4 f3xe4 Bd5-c4 Nd4-c6 Kg6-f7 Kg1-f2 e6-e5 Kf2-e3 Kf7-e6
Ke3-d2 Na4-b2 Kd2-c2) +0.14/18 2} Kf7 {(Kg8-f7 Nd4-f3 Kf7-f6 Rc8-f8+ Kf6-e7
Rf8-g8 Ke7-f6 Nf3-d4 Rd6-d7 Rg8-f8+ Kf6-e5 f2-f3 Ne4-f6 Kg1-f2 Rd7-c7
Rf8-d8 g7-g5 Be1-d2) -0.21/13 2} 27. Rc7+ {(Rc8-c7+ Kf7-g6 f2-f3 Ne4-f6
Bg2-f1 Na4-b2 h2-h4 Rd6-d7 Rc7-c5 Nb2-a4 Rc5-c1 Rd7-d6 g3-g4 f5xg4 Be1-g3
Rd6-d7 f3xg4 Nf6xg4 e3-e4 Bd5xe4 Nd4xe6) +0.25/21 2} Kg6 {(Kf7-g6 h2-h4
h7-h5 f2-f3 Ne4-f6 Bg2-f1 Na4-b6 Kg1-f2 Nf6-d7 Bf1-d3 Bd5-c4 Bd3xc4 b5xc4
f3-f4 Nd7-f6) -0.12/13 1} 28. f3 {(f2-f3 Ne4-f6 Bg2-f1 Na4-b2 Be1-c3 Nb2-c4
Bf1xc4 Bd5xc4 Rc7-c6 Rd6xc6 Nd4xc6 Nf6-d7 Kg1-f2 Bc4-d5 Nc6-e7+ Kg6-f7
Ne7xd5 e6xd5 Kf2-e2 g7-g6 Ke2-d3 Kf7-e6 Kd3-d4 Ke6-d6) +0.22/23 2} Nf6
{(Ne4-f6 Be1-f2 Na4-b6 Bg2-f1 Bd5-c4 Rc7-e7 Nf6-g8 Re7-c7 Ng8-f6) 0.00/17
2} 29. Bf1 {(Bg2-f1 Na4-b2 h2-h4 h7-h6 Be1-c3 Nb2-c4 Bf1xc4 Bd5xc4 Rc7-c6
Rd6xc6 Nd4xc6 Nf6-d7 Kg1-f2 Bc4-d5 Nc6-e7+ Kg6-f7 Ne7xd5 e6xd5 Kf2-e2 g7-g6
Ke2-d2 Kf7-e7 Bc3-d4 Ke7-e6 Kd2-c3) +0.26/23 2} Rd7 {(Rd6-d7 Rc7-c1 Rd7-d6
Rc1-c7) 0.00/15 2} 30. Rc1 {(Rc7-c1 Kg6-h6 Be1-f2 Na4-b2 Rc1-c8 Nb2-c4
Bf1xc4 Bd5xc4 h2-h3 g7-g5 Rc8-c6 Kh6-g6 Rc6xa6 g5-g4 h3xg4 f5xg4) +0.51/19
0} Rd6 {(Rd7-d6 Rc1-c7) 0.00/18 1} 31. g4 {(g3-g4) +1.01/20 0} fxg4 {(f5xg4
Bf1-d3+ Kg6-h5 f3xg4+ Kh5xg4 Be1-g3 Rd6-d8 Kg1-f2 h7-h5 Bg3-c7 Rd8-d7
Bd3-e2+ Kg4-h4 Nd4-f3+ Kh4-h3 Nf3-g5+ Kh3-h4) +0.31/12 1} 32. Bg3 {(Be1-g3
Rd6-d8 e3-e4 Bd5-a2 Nd4-c6 Rd8-f8 Bg3-d6 Rf8-e8 Nc6-e5+ Kg6-h5 Bf1-g2 g4xf3
Bg2xf3+ Kh5-h6 Kg1-f2 Na4-b2 Rc1-c6 Nb2-c4 Ne5xc4 Ba2xc4 Rc6xa6 g7-g5 e4-e5
Nf6-d5 Ra6-a7 Re8-c8 Bf3-e4 Kh6-h5) +0.95/22 0} Rd7 {(Rd6-d7 e3-e4 Bd5-b7
Nd4xe6 Rd7-e7 Ne6-f8+ Kg6-f7 Bg3-d6 g4xf3 Bd6xe7 Kf7xe7 Nf8xh7 Bb7xe4
Rc1-c7+ Nf6-d7 Nh7-f8 Na4-b6 Nf8xd7 Nb6xd7) -0.15/14 1} 33. e4 {(e3-e4
e6-e5 Bg3xe5 Bd5-b7 f3xg4 Nf6xg4 Nd4-e6 Rd7-f7 Be5-d4 Bb7xe4 h2-h3 Ng4-f6
Ne6-c7 Rf7-d7 Bd4xf6 Kg6xf6 Nc7xa6 Be4-d3 Na6-c7 Bd3xf1 Kg1xf1 Rd7-d3
Rc1-c6+ Kf6-e5 Nc7xb5 Rd3xh3) +0.49/20 0} Bb7 {(Bd5-b7 Nd4xe6 Rd7-e7
Ne6-f4+ Kg6-h6 f3xg4 Nf6xg4 Bf1-g2 Bb7xe4 Bg2xe4 Re7xe4 Rc1-c6+ Ng4-f6
Rc6xa6 Na4-c3 Ra6-c6 Nc3-e2+ Nf4xe2 Re4xe2) +0.01/15 1} 34. Nxe6 {(Nd4xe6
Kg6-f7 Ne6-c7 Nf6-e8 Nc7xe8 Kf7xe8 f3xg4 Na4-b2 e4-e5 Bb7-d5 Rc1-c5 Ke8-f7
Bf1-g2 Bd5-e6 h2-h3 Rd7-d1+ Kg1-h2 Nb2-c4 Bg2-e4 Rd1-d2+ Kh2-g1 g7-g6
Be4-b7 Rd2-d3 Bg3-f4 Rd3xh3 Bb7xa6 Nc4xa3 Rc5-c7+ Kf7-g8 Kg1-f2 Be6xg4)
+1.08/20 0} Re7 {(Rd7-e7 Ne6-f4+ Kg6-h6 f3xg4 Nf6xg4 Bf1-h3 Ng4-f6 e4-e5
Re7xe5 Nf4-e6 Re5-h5 Ne6-f4 Rh5-g5 Nf4-e6 Rg5-h5) 0.00/16 1} 35. Nf8+
{(Ne6-f8+ Kg6-h6 Bg3-d6 Re7-f7 e4-e5 Nf6-e8 e5-e6 Rf7xf3 Bd6-e7 Na4-c3
Rc1-e1 Nc3-d5 Be7-c5 Nd5-f4 Bc5-e3 Kh6-h5 Be3-c1 Nf4-d3 Bf1xd3 Rf3xd3
Re1-e5+ Kh5-h4 Bc1-f4 Rd3-d1+ Kg1-f2) +0.85/20 0} Kh6 {(Kg6-h6 f3xg4 Nf6xg4
Bg3-f4+ g7-g5 Bf4-d6 Re7-e8 h2-h3 Ng4-e3 e4-e5 Ne3xf1 Kg1xf1 Re8-c8 Rc1xc8
Bb7xc8) 0.00/13 1} 36. Bd6 {(Bg3-d6 Re7-f7 e4-e5 Nf6-e8 e5-e6 Rf7xf3 Bd6-e7
Na4-c3 Rc1-e1 Nc3-d5 Be7-c5 Nd5-f4 Bc5-e3 Bb7-d5 Nf8-d7 g7-g5 Nd7-b6 Bd5-c6
Nb6-d7 Nf4-h3+ Bf1xh3 Rf3xh3 Nd7-e5 Bc6-d5 e6-e7 g4-g3) +0.60/21 0} Rf7
{(Re7-f7 f3xg4 Nf6xe4 Bd6-e5 Ne4-d2 Be5-d6 Bb7-d5 Bf1-d3 Nd2-c4 Bd3xc4
Bd5xc4 h2-h4 Rf7-f3 g4-g5+ Kh6-h5 Nf8xh7 Kh5xh4) +0.67/14 1} 37. e5 {(e4-e5
Nf6-e8 e5-e6 Rf7xf3 Bd6-e7 Na4-c3 Rc1-e1 Nc3-d5 Be7-c5 Nd5-f4 Bc5-e3 Bb7-d5
Nf8-d7 g7-g5 Nd7-e5 Nf4-h3+ Bf1xh3 Rf3xh3 Ne5xg4+ Kh6-h5 Ng4-f2 Rh3-f3
e6-e7 Kh5-g6 Nf2-d3 Rf3-f5 Be3-c5 Kg6-f6 Nd3-f2 Rf5-f4) +0.65/23 0} Ne8
{(Nf6-e8 Nf8-e6 Bb7-d5 Ne6-c5 Ne8xd6 e5xd6) +0.49/16 1} 38. Ne6 {(Nf8-e6)
+0.89/21 0} Bd5 {(Bb7-d5 Ne6-c5 Ne8xd6) +0.46/15 1} 39. Nc5 {(Ne6-c5 g4xf3
Kg1-f2 Na4-b6 Nc5xa6 Bd5-c4 Bd6-c5 Bc4xf1 Rc1xf1 Nb6-c4 e5-e6 Rf7-f6 Rf1-e1
g7-g5 Na6-b8 Nc4-b2 Kf2-f1 Nb2-d3 Re1-e3 Nd3xc5 b4xc5) +0.74/22 0} gxf3
{(g4xf3 Kg1-f2 Na4-b2 Nc5xa6 Nb2-c4 Bf1xc4 Bd5xc4 a3-a4 Ne8xd6 e5xd6 Rf7-d7
Na6-c5 Rd7xd6 Kf2xf3 Bc4-d5+ Kf3-f4 b5xa4 Nc5xa4) +0.04/15 1} 40. Kf2
{(Kg1-f2 Na4-b6 Nc5xa6 Bd5-c4 Bd6-c5 Bc4xf1 Kf2xf1 Nb6-a4 e5-e6 Rf7-f5
Bc5-d4 Rf5-d5 Bd4-e3+ Kh6-g6 Kf1-f2 Rd5-e5 Rc1-c6 Kg6-f5 Na6-c7 Ne8xc7
Rc6xc7 Kf5xe6 Rc7xg7) +0.75/22 0} Nxc5 {(Na4xc5 b4xc5 Bd5-c6 e5-e6 Rf7-f6
e6-e7 Kh6-g6 Rc1-d1 Kg6-f7 Rd1-d4 Rf6-h6 h2-h4 Ne8xd6 c5xd6 Rh6-g6)
-0.12/15 1} 41. bxc5 {(b4xc5 Bd5-c6 Bf1-h3 Kh6-h5 Bh3-c8 g7-g5 e5-e6 Rf7-a7
Rc1-e1 Ne8-f6 e6-e7 Kh5-g6 Re1-e5 Kg6-f7 h2-h3 Nf6-e4+ Kf2-e3 f3-f2 Re5-f5+
Kf7-g7) +1.10/21 0} Bc6 {(Bd5-c6 e5-e6 Rf7-f6 Bf1-h3 Kh6-h5 e6-e7 Kh5-g5
Rc1-d1 a6-a5 Rd1-d4 a5-a4 Bd6-g3 Rf6-f7 Bg3-h4+ Kg5-g6 Bh3-e6) -0.19/15 0}
42. Bh3 {(Bf1-h3 Kh6-h5 Bh3-c8 Rf7-a7 Kf2-g3 Kh5-g6 Bc8-g4 Kg6-f7 e5-e6+
Kf7-f6 Rc1-e1 a6-a5 Bg4xf3 Bc6xf3 Kg3xf3 b5-b4 a3xb4 a5xb4) +1.30/21 0} Rf4
{(Rf7-f4 e5-e6 Rf4-a4 Rc1-c3 Ne8-f6 Rc3-d3 Nf6-e4+ Kf2-e3 f3-f2 e6-e7
Kh6-g5 Bh3-f1 a6-a5 Bf1-h3 Kg5-f6 Rd3-b3 Ne4xd6 c5xd6) +0.59/15 1} 43. Bd7
{(Bh3-d7 Bc6xd7 e5-e6 Bd7-c6 Bd6xf4+ Kh6-g6 Bf4-e5 Kg6-f5 Rc1-e1 Kf5xe6
Be5xg7+ Ke6-d5 Bg7-f8 Ne8-f6 Kf2xf3 Nf6-d7 Bf8-d6 a6-a5 Kf3-e2 Kd5-c4
Ke2-d2 b5-b4 a3xb4 a5xb4 Re1-e7 b4-b3 Re7xh7) +2.20/22 0} Nxd6 {(Ne8xd6
Bd7xc6 Nd6-f5 Bc6xf3 Nf5-h4 Rc1-c3 Nh4xf3 Rc3xf3 Rf4-h4 e5-e6 Rh4xh2+
Kf2-e3 Rh2-h1 Ke3-d4 Rh1-d1+ Rf3-d3 Rd1-f1) -0.01/13 1} 44. Bxc6 {(Bd7xc6)
+3.01/23 0} Nf5 {(Nd6-f5 Bc6-b7 Nf5-e7 c5-c6 Rf4-a4 c6-c7 Ra4xa3 c7-c8R
Ne7xc8 Rc1xc8 Kh6-g5 Rc8-f8 b5-b4 e5-e6 Ra3-a2+ Kf2xf3 b4-b3) -0.82/15 1}
45. Bd7 {(Bc6-d7 Kh6-g5 c5-c6 Nf5-e7 e5-e6 Rf4-c4 Rc1xc4 b5xc4 Kf2xf3 c4-c3
Kf3-e2 Ne7-d5 e6-e7 Nd5xe7 c6-c7 Kg5-f4 Ke2-d3 g7-g5 c7-c8Q Ne7xc8 Bd7xc8
a6-a5 Kd3xc3 h7-h5) +3.64/22 0} Ne7 {(Nf5-e7 c5-c6 Rf4-c4 Rc1xc4 b5xc4
Kf2xf3 c4-c3 Kf3-e2 Ne7-d5 Bd7-f5 g7-g6 Bf5-e4 Nd5-f4+ Ke2-e3 Nf4-e6 Be4-d3
a6-a5 a3-a4) -0.62/16 1} 46. c6 {(c5-c6 Kh6-g5 e5-e6 Rf4-c4 Rc1xc4 b5xc4
Kf2xf3 c4-c3 Kf3-e2 Ne7-d5 e6-e7 Nd5xe7 c6-c7 h7-h5 Ke2-d3 a6-a5 Bd7-e6
Kg5-f6 c7-c8Q Ne7xc8 Be6xc8 Kf6-g5 Kd3xc3 Kg5-h4 h2-h3 g7-g5 Kc3-d4 g5-g4
h3xg4) +3.89/22 0} Rc4 {(Rf4-c4 Rc1xc4) -0.60/17 1} 47. Rxc4 {(Rc1xc4)
+4.81/25 0} bxc4 {(b5xc4 Kf2xf3 c4-c3 Kf3-e2 Ne7-d5 Bd7-e8 Kh6-g5 Be8-f7
Nd5-e7 c6-c7 Kg5-f5 e5-e6 Kf5-e5) -0.70/20 1} 48. Kxf3 {(Kf2xf3 c4-c3
Kf3-e2 Ne7-d5 e5-e6 Kh6-g5 e6-e7 Nd5xe7 c6-c7 Kg5-f4 Ke2-d3 g7-g5 c7-c8Q
Ne7xc8 Bd7xc8 a6-a5 h2-h3 h7-h5 Kd3xc3 g5-g4 h3xg4 h5xg4 a3-a4 Kf4-f3
Bc8-b7+ Kf3-g3 Kc3-c4 Kg3-f2 Kc4-b5 g4-g3 Kb5xa5 g3-g2) +5.10/26 0} c3
{(c4-c3 Kf3-e2 Ne7-d5 Bd7-e8 Kh6-g5 Be8-f7 Nd5-c7 Ke2-d3 Kg5-f5 e5-e6
Nc7xe6 Kd3xc3 Kf5-f6 Bf7-g8 h7-h5 Kc3-b4 Ne6-c7 Bg8-c4 Kf6-e5 Kb4-a5
Ke5-d6) -1.08/21 1} 49. Ke2 {(Kf3-e2) +5.43/23 0} Nd5 {(Ne7-d5 Bd7-e8
Kh6-g5 Be8-f7 Nd5-c7 Ke2-d3 Kg5-f5 e5-e6 Kf5-f6 Kd3xc3 Kf6-e7 Bf7-g8 Ke7-d6
e6-e7 Kd6xe7 Bg8xh7 Ke7-d6 Bh7-e4 Nc7-b5+ Kc3-c4 Nb5xa3+ Kc4-d4 a6-a5)
-1.11/21 1} 50. e6 {(e5-e6 Kh6-g6 e6-e7 Nd5xe7 c6-c7 Kg6-f6 Ke2-d3 a6-a5
c7-c8Q Ne7xc8 Bd7xc8 Kf6-g5 Kd3xc3 Kg5-h4 a3-a4 g7-g5 h2-h3 h7-h5 Kc3-d3
g5-g4 h3xg4 h5xg4 Kd3-e4 Kh4-h5 Ke4-e3 Kh5-g5 Ke3-e4) +5.61/22 0} Kg5
{(Kh6-g5 e6-e7 Nd5xe7 c6-c7 Kg5-f4 Ke2-d3 a6-a5 c7-c8R Ne7xc8 Bd7xc8 g7-g5
Kd3xc3 g5-g4 Bc8-b7 a5-a4) -1.50/14 1} 51. e7 {(e6-e7) +5.98/22 0} Nxe7
{(Nd5xe7 c6-c7 Kg5-h4 c7-c8R Ne7xc8 Bd7xc8 g7-g5 Bc8-f5 h7-h5 Ke2-d3 g5-g4
Bf5-g6 Kh4-g5 Bg6-f7 h5-h4 Kd3xc3 g4-g3 h2xg3 h4xg3 Bf7-d5) -1.20/18 1} 52.
c7 {(c6-c7) +6.16/21 0} Kh4 {(Kg5-h4 c7-c8R Ne7xc8 Bd7xc8 g7-g5 h2-h3 h7-h5
Ke2-d3 c3-c2 Kd3xc2 a6-a5 Bc8-e6 g5-g4 h3xg4 h5xg4 Be6-d5 g4-g3 Kc2-d2
Kh4-g4 Kd2-e3 a5-a4 Ke3-d4) -1.04/20 1} 53. Kd3 {(Ke2-d3 g7-g5 Bd7-e6 c3-c2
Kd3xc2 g5-g4 Kc2-c3 Kh4-h3 Kc3-d4 h7-h5 Kd4-e5 Kh3xh2 Ke5-d6 g4-g3 Kd6xe7
g3-g2 c7-c8Q g2-g1Q Qc8xa6 Qg1-g7+ Be6-f7 Qg7-e5+ Ke7-d7 h5-h4 a3-a4 h4-h3
a4-a5 Qe5-g7 Qa6-g6) +6.56/22 0} g6 {(g7-g6 Bd7-e6 c3-c2 Kd3xc2 h7-h6
c7-c8Q Ne7xc8 Be6xc8 a6-a5 Kc2-b3 g6-g5 Kb3-a4 g5-g4 Ka4xa5) -2.05/17 1}
54. Be6 {(Bd7-e6 c3-c2 Kd3xc2 Kh4-g5 Kc2-c3 Kg5-f4 Kc3-d4 a6-a5 Kd4-c5
Kf4-e5 c7-c8Q Ne7xc8 Be6xc8 g6-g5 Kc5-b5 Ke5-d4 Kb5xa5 Kd4-c5 Bc8-g4 Kc5-c4
a3-a4 Kc4-c5 Ka5-a6 Kc5-c6 a4-a5 h7-h6) +9.94/23 0} c2 {(c3-c2 Kd3xc2 g6-g5
Kc2-b3 g5-g4 Kb3-c4 Kh4-g5 Kc4-c5 h7-h5 Kc5-d6 Kg5-f6 Kd6-d7 a6-a5 Kd7-d6
a5-a4 c7-c8R Ne7xc8+) -2.24/22 0} 55. Kxc2 {(Kd3xc2 Kh4-g5 Kc2-c3 a6-a5
Kc3-c4 h7-h5 c7-c8Q Ne7xc8 Be6xc8 Kg5-h4 Bc8-d7 g6-g5 Kc4-b5 g5-g4 Bd7-e8
Kh4-g5 Kb5xa5 h5-h4 Be8-c6 g4-g3 h2xg3 h4xg3 a3-a4 Kg5-f4 Ka5-b4 Kf4-e3
a4-a5 Ke3-f2) +10.29/23 0} g5 {(g6-g5) -2.24/20 1} 56. Kd3 {(Kc2-d3 a6-a5
Kd3-d4 Kh4-h5 Kd4-c5 Kh5-g6 Kc5-b5 Kg6-f6 c7-c8Q Ne7xc8 Be6xc8 Kf6-e7
Kb5xa5 Ke7-d8 Bc8-g4 Kd8-c7 Ka5-b5 h7-h6 a3-a4 Kc7-d8 a4-a5 h6-h5 Bg4xh5
Kd8-e7 Kb5-b6 g5-g4 Kb6-b7 g4-g3) +10.41/26 0} Kh5 {(Kh4-h5 Kd3-c4 h7-h6
Kc4-c5 Kh5-g6 c7-c8B Ne7xc8 Be6xc8 a6-a5 Kc5-b5 h6-h5 Kb5xa5 g5-g4 Ka5-b6
Kg6-g5 Bc8-e6 h5-h4 a3-a4 g4-g3) -2.70/18 1} 57. Kc4 {(Kd3-c4 Kh5-g6 c7-c8Q
Ne7xc8 Be6xc8 a6-a5 Kc4-b5 h7-h5 Kb5xa5 g5-g4 a3-a4 Kg6-g5 Ka5-b5 h5-h4
a4-a5 h4-h3 Bc8xg4 Kg5xg4 a5-a6 Kg4-f4 Kb5-b6 Kf4-f3 a6-a7 Kf3-g2 Kb6-c7
Kg2xh2 a7-a8Q) +10.41/27 0} a5 {(a6-a5 Kc4-b5 g5-g4 Kb5-c5 Kh5-g5 Kc5-d6
Kg5-f6 Be6xg4 Kf6-f7 c7-c8B Ne7xc8+) -3.19/19 1} 58. Kc5 {(Kc4-c5 Kh5-g6
Kc5-b5 Kg6-f6 c7-c8Q Ne7xc8 Be6xc8 h7-h5 Kb5xa5 h5-h4 Ka5-b5 Kf6-e5 a3-a4
Ke5-f4 a4-a5 g5-g4 a5-a6 g4-g3 h2xg3+ h4xg3 Bc8-b7 Kf4-e3 a6-a7 Ke3-f2
a7-a8Q g3-g2 Bb7xg2 Kf2-g1 Bg2-b7) +10.41/28 0} Kg6 {(Kh5-g6 Kc5-b5 h7-h5
Kb5xa5 Kg6-f6 c7-c8Q Ne7xc8 Be6xc8 g5-g4 a3-a4 Kf6-g5 Ka5-b6 h5-h4 a4-a5
g4-g3 h2xg3 h4xg3 Bc8-b7 Kg5-f5 a5-a6 Kf5-f4) -3.10/19 0} 59. Kb5 {(Kc5-b5
Kg6-f6 c7-c8Q Ne7xc8 Be6xc8 g5-g4 Kb5xa5 Kf6-g5 a3-a4 h7-h5 Ka5-b6 Kg5-h4
Kb6-c5 Kh4-h3 a4-a5 Kh3xh2 a5-a6 g4-g3 Bc8-b7 h5-h4 a6-a7 g3-g2 Bb7xg2
Kh2xg2 a7-a8Q+ Kg2-f2 Qa8-h1) +10.41/25 1} h5 {(h7-h5 Kb5xa5 g5-g4 Ka5-b5
Kg6-f6 Be6-d7 h5-h4 Bd7xg4 Kf6-g5 c7-c8B Ne7xc8 Bg4xc8 Kg5-f4 a3-a4 Kf4-f3
Bc8-b7+ Kf3-g4 a4-a5 Kg4-h3 a5-a6 Kh3xh2) -3.76/19 1} 60. Kxa5 h4 {(h5-h4
a3-a4 Kg6-h5 Ka5-b5 g5-g4 Kb5-c5 g4-g3 h2xg3 h4xg3 Kc5-d6 g3-g2 Kd6xe7
g2-g1Q c7-c8Q Qg1-g5+ Ke7-d7 Qg5-d2+ Kd7-c6 Qd2-c2+ Kc6-b5 Qc2-b1+ Kb5-c5)
-3.98/18 0} 61. Kb5 {(Ka5-b5 Kg6-h5 Kb5-c5 Kh5-g6 Kc5-d6 Kg6-f6 Be6-g4
Kf6-f7 a3-a4 h4-h3 Bg4-e6+ Kf7-e8 c7-c8Q+ Ne7xc8+ Be6xc8 g5-g4 Bc8xg4
Ke8-d8 Bg4xh3 Kd8-e8 a4-a5 Ke8-f7 Kd6-c6 Kf7-f6 Kc6-b5 Kf6-g5 a5-a6 Kg5-h4
Bh3-c8) +10.48/28 0} Kh5 {(Kg6-h5 a3-a4 g5-g4 Kb5-c5 g4-g3 h2xg3 h4xg3
Kc5-d6 g3-g2 Kd6xe7 g2-g1Q c7-c8Q Qg1-g5+) -4.53/17 1} 62. Kc5 {(Kb5-c5
Kh5-g6 Kc5-d6 Kg6-f6 Be6-g4 Kf6-f7 a3-a4 h4-h3 Bg4xh3 g5-g4 Bh3xg4 Kf7-f6
c7-c8Q Ne7xc8+ Bg4xc8 Kf6-g5 Kd6-c6 Kg5-f4 a4-a5 Kf4-g5 Bc8-b7 Kg5-f4 a5-a6
Kf4-e3) +10.48/28 1} Kg6 {(Kh5-g6 a3-a4 Kg6-f6 Be6-d7 g5-g4 Bd7xg4 Kf6-g5
Kc5-d6 Kg5-f6 a4-a5 Kf6-f7 Kd6-c5 h4-h3 Bg4xh3 Kf7-f8 a5-a6 Kf8-e8 c7-c8R+
Ne7xc8 Bh3xc8 Ke8-d8 a6-a7 Kd8xc8 a7-a8Q+) -9.89/19 0} 63. Kd6 {(Kc5-d6
Kg6-f6 Be6-g4 Kf6-f7 a3-a4 h4-h3 Bg4xh3 g5-g4 Bh3xg4 Kf7-f6 c7-c8Q Ne7xc8+
Bg4xc8 Kf6-g5 Kd6-c6 Kg5-f4 a4-a5 Kf4-g5 Bc8-b7 Kg5-f4 h2-h4 Kf4-e3 Kc6-b5
Ke3-f2 a5-a6 Kf2-f1 Kb5-b6 Kf1-e2 Bb7-c6) +10.48/30 1} Kf6 {(Kg6-f6 c7-c8Q
Ne7xc8+ Be6xc8 h4-h3 Bc8xh3 g5-g4 Bh3xg4 Kf6-g5 a3-a4 Kg5xg4 a4-a5 Kg4-h3
a5-a6 Kh3xh2 a6-a7) -9.76/25 1} 64. Bg4 {(Be6-g4 Kf6-f7 a3-a4 h4-h3 Bg4xh3
g5-g4 Bh3xg4 Kf7-f6 c7-c8Q Ne7xc8+ Bg4xc8 Kf6-g5 a4-a5 Kg5-f4 Kd6-c7 Kf4-g5
h2-h4+ Kg5-f4 Kc7-b6 Kf4-e3 Bc8-b7 Ke3-f4 Bb7-h1 Kf4-e5 Bh1-a8 Ke5-f6
Ba8-c6 Kf6-e6 a5-a6) +10.48/31 0} Kf7 {(Kf6-f7 a3-a4 h4-h3 c7-c8Q Ne7xc8+
Bg4xc8 g5-g4 Bc8xg4 Kf7-f6 a4-a5 Kf6-g5 a5-a6 Kg5xg4 a6-a7) -10.39/22 0}
65. a4 {(a3-a4 Kf7-f6 a4-a5 h4-h3 c7-c8Q Ne7xc8+ Bg4xc8 g5-g4 Bc8xg4 Kf6-g5
Bg4xh3 Kg5-f4 Bh3-c8 Kf4-e3 h2-h4 Ke3-d2 a5-a6 Kd2-e3 a6-a7 Ke3-d2 a7-a8Q
Kd2-e3 Qa8-g2 Ke3-d3 Qg2-a2 Kd3-e3 Bc8-b7 Ke3-d3 Qa2-e6 Kd3-d2) +10.48/29
1} h3 {(h4-h3 c7-c8Q Ne7xc8+ Bg4xc8 Kf7-f6 a4-a5 Kf6-g7 a5-a6 Kg7-h6 Bc8xh3
Kh6-h5 a6-a7 g5-g4 Bh3-g2 g4-g3 h2xg3 Kh5-g4 a7-a8Q Kg4xg3 Qa8-f3+ Kg3-h4
Qf3-f4+ Kh4-h5 Bg2-f3+ Kh5-g6 Bf3-e4+ Kg6-g7 Qf4-g5+ Kg7-f8 Qg5-e7+ Kf8-g8
Qe7-f6) -13.25/23 1} 66. c8=Q {(c7-c8Q Ne7xc8+ Bg4xc8 g5-g4 Bc8xg4 Kf7-g6
Bg4xh3 Kg6-g5 Kd6-e5 Kg5-g6 a4-a5 Kg6-g7 a5-a6 Kg7-f8 a6-a7 Kf8-f7 a7-a8Q
Kf7-g7 Bh3-e6 Kg7-h6 Qa8-g8 Kh6-h5 Qg8-h7+ Kh5-g5 h2-h4+) +M13/31 0} Nxc8+
{(Ne7xc8+ Bg4xc8 Kf7-f6 a4-a5 Kf6-g7 a5-a6 g5-g4 Bc8xg4 Kg7-h6 Bg4xh3
Kh6-h5 a6-a7 Kh5-g5 a7-a8Q Kg5-f4 Bh3-e6 Kf4-e3 h2-h4 Ke3-f2 Qa8-a7+ Kf2-f3
Be6-d5+ Kf3-g4 Qa7-d4+ Kg4-h3 Bd5-e6+ Kh3-g2 h4-h5 Kg2-f3 Be6-d5+ Kf3-g3
h5-h6 Kg3-h3) -14.56/25 1} 67. Bxc8 {(Bg4xc8 g5-g4 Bc8xg4 Kf7-g6 Bg4xh3
Kg6-f6 a4-a5 Kf6-g5 Kd6-e5 Kg5-g6 a5-a6 Kg6-g7 a6-a7 Kg7-f7 a7-a8Q Kf7-g7
Bh3-e6 Kg7-h6 Qa8-g8 Kh6-h5 Qg8-h7+ Kh5-g5 h2-h4+) +M12/36 1} Kf6 {(Kf7-f6
a4-a5 Kf6-g7 a5-a6 g5-g4 Bc8xg4 Kg7-h6 Bg4xh3 Kh6-h5 a6-a7 Kh5-g5 a7-a8Q
Kg5-f4 Bh3-e6 Kf4-e3 h2-h4 Ke3-d2 Qa8-d5+ Kd2-c3 Qd5-a5+ Kc3-d3 Qa5-a6+
Kd3-d2 Qa6-a1 Kd2-d3 Qa1-e5) -14.94/28 0} 68. Bg4 {(Bc8-g4 Kf6-g7 a4-a5
Kg7-f6 a5-a6 Kf6-f7 a6-a7 Kf7-f6 a7-a8Q Kf6-g7 Kd6-e6 Kg7-h7 Ke6-f6 Kh7-h6
Qa8-h8+) +M8/37 0} Kg7 {(Kf6-g7 a4-a5 Kg7-h8 Bg4xh3 Kh8-g7 a5-a6 g5-g4
Bh3xg4 Kg7-f6 a6-a7 Kf6-g5 Bg4-e6 Kg5-f4 a7-a8Q Kf4-e3) -14.94/19 1} 69. a5
{(a4-a5 Kg7-f6 a5-a6 Kf6-f7 a6-a7 Kf7-f6 a7-a8Q Kf6-g7 Kd6-e6 Kg7-h7 Ke6-f6
Kh7-h6 Qa8-h8+) +M7/44 0} Kh8 {(Kg7-h8 Bg4xh3) -14.94/17 1} 70. a6 {(a5-a6
Kh8-h7 a6-a7 Kh7-g7 a7-a8Q Kg7-f7 Qa8-h8 Kf7-g6 Qh8-f8 Kg6-h7 Bg4-f5+)
+M6/51 0} Kh7 {(Kh8-h7 Bg4xh3 Kh7-g6 a6-a7 g5-g4 Bh3xg4 Kg6-g5 Bg4-h3
Kg5-f4 Bh3-e6 Kf4-e3 a7-a8Q Ke3-f2 Qa8-g8) -14.94/17 1} 71. a7 {(a6-a7
Kh7-g7 a7-a8Q Kg7-f7 Qa8-h8 Kf7-g6 Qh8-f8 Kg6-h7 Bg4-f5+) +M5/65 0} Kg7
{(Kh7-g7 a7-a8Q Kg7-h6 Qa8-h8+ Kh6-g6 Bg4-h5+) -M4/16 1} 72. a8=Q {(a7-a8Q
Kg7-f7 Qa8-h8 Kf7-g6 Qh8-f8 Kg6-h7 Bg4-f5+) +M4/93 0} Kh6 {(Kg7-h6 Qa8-h8+
Kh6-g6 Bg4-h5+ Kg6-f5 Qh8-e5+) -M3/16 1} 73. Qf8+ {(Qa8-f8+ Kh6-g6 Bg4-f5+
Kg6-h5 Qf8-h8+) +M3/128 0} Kg6 {(Kh6-g6 Bg4-f5+ Kg6-h5 Qf8-h8+) -M2/15 1}
74. Bf5+ Kh5 {(Kg6-h5 Qf8-h8+) -M1/16 1} 75. Qh8# 1-0[/pgn]

[Chessqueen]

[pgn][Event "Blunder Vs Booot7.1"]
[Site "DESKTOP-OFQ3C0P"]
[Date "2023.03.03"]
[Round "2"]
[White "Blunder-8.5.5-popcnt"]
[Black "Booot71_avx2"]
[Result "0-1"]
[BlackElo "3375"]
[ECO "A21"]
[Opening "English"]
[Time "04:06:44"]
[Variation "KID, 2.Nc3 f5 3.g3 Nf6 4.Bg2"]
[WhiteElo "3340"]
[TimeControl "0+2"]
[Termination "normal"]
[PlyCount "124"]
[WhiteType "program"]
[BlackType "program"]

1. c4 f5 2. Nc3 Nf6 3. g3 e5 4. Bg2 c6 5. d4 e4 6. Nh3 Na6 7. O-O Nc7 8. f3
d5 9. cxd5 cxd5 10. Bg5 Be7 11. Nf4 Ne6 12. Qa4+ Kf7 13. Nxe6 Bxe6 14. fxe4
dxe4 15. Kh1 h5 16. Rad1 Kg6 17. h4 Qd6 18. Rf4 Rhc8 19. Bh3 Rxc3 20. bxc3
Nd5 21. Bxe7 Qxe7 22. Rdf1 Nxf4 23. Rxf4 Qc7 24. d5 Bd7 25. Qb4 Re8
{(Ra8-e8) -0.05/22 2} 26. d6 {(d5-d6 Qc7-c6 Qb4-d4 e4-e3+ Kh1-g1 Qc6-b5
Rf4-f1 Qb5xe2 Qd4-f4 Re8-f8 Qf4-g5+ Kg6-h7 Bh3xf5+ Bd7xf5 Rf1xf5) +0.03/12
1} Qb6 {(Qc7-b6) +2.00/21 1} 27. Qxb6 {(Qb4xb6 a7xb6 Rf4-f1 Re8-c8 Kh1-g2
Rc8-c6 Rf1-d1 Rc6xc3 Rd1-d2 e4-e3 Rd2-d1 Rc3-c2 Kg2-f3 Rc2-d2 Rd1-g1 Rd2xd6
Kf3xe3 Rd6-e6+ Ke3-f3 Re6-e4) -0.79/18 2} axb6 {(a7xb6) +2.58/25 2} 28. Rf1
{(Rf4-f1 Re8-c8 Kh1-g2 Rc8-c6 Rf1-d1 Rc6xc3 Rd1-d2 e4-e3 Rd2-d1 Rc3-c2
Kg2-f3 Rc2-d2 Rd1-g1 Rd2xd6 Kf3xe3 Bd7-e6 a2-a4 Rd6-c6 Bh3-g2 Rc6-c3+
Ke3-f4) -0.88/20 2} Rc8 {(Re8-c8 Rf1-c1 Rc8-c6 Bh3-f1 Rc6xd6 e2-e3 Rd6-d2
Rc1-b1 Rd2xa2 Rb1xb6+ Bd7-c6 Bf1-c4 Ra2-c2 Bc4-a6 b7xa6 Rb6xc6+ Kg6-f7
c3-c4 Rc2-e2 Rc6xa6 Re2xe3 Kh1-g2 Re3-e2+ Kg2-f1 Re2-c2 Ra6-c6 g7-g6 c4-c5)
+2.67/26 2} 29. Kg2 {(Kh1-g2 Rc8-c6 Rf1-d1 Rc6xc3 Kg2-f2 b6-b5 Rd1-d5
Kg6-f6 Bh3xf5 e4-e3+ Kf2-f3 Bd7-c6 Bf5-e4 Bc6xd5 Be4xd5 Rc3-c8 Bd5xb7
Rc8-d8 Kf3xe3 Rd8xd6 Bb7-e4) -1.03/19 2} b5 {(b6-b5 Rf1-c1 Kg6-f6 e2-e3
Kf6-e5 Kg2-g1 Rc8-a8 Bh3-f1 Ke5xd6 Rc1-d1+ Kd6-c7 Rd1-b1 Ra8xa2 Bf1xb5
Bd7xb5 Rb1xb5 g7-g6 Rb5-c5+ Kc7-d6 Rc5-b5 Kd6-c6 Rb5-e5 Ra2-e2 Re5-e6+
Kc6-d5 Re6xg6 Re2xe3) +2.92/24 2} 30. Rd1 {(Rf1-d1 Rc8xc3 Rd1-d5 Rc3-c2
Kg2-f2 Rc2xa2 Bh3xf5+ Bd7xf5 d6-d7 Bf5xd7 Rd5-d6+ Kg6-f5 Rd6xd7 Kf5-f6
Rd7-d6+ Kf6-e7 Rd6-g6 Ke7-f7 Rg6-b6 Ra2-b2 Rb6xb7+ Kf7-f6) -0.99/19 2} Kf6
{(Kg6-f6 Rd1-c1 Rc8-a8 Rc1-c2 Kf6-e5 Rc2-d2 Ra8-a3 e2-e3 Ra3xc3 Kg2-f2
Rc3-c5 Kf2-e1 Rc5-d5 Rd2-b2 Ke5xd6 Bh3-f1 g7-g6 Rb2-b4 Kd6-c6 Bf1-e2 Rd5-c5
a2-a4 b5xa4 Rb4xa4 Rc5-c1+ Be2-d1 Kc6-b5 Ra4-a8 Bd7-c6) +3.89/26 2} 31. Rd5
{(Rd1-d5 b7-b6 Kg2-f1 Rc8-c5 Rd5xc5 b6xc5 Kf1-f2 Kf6-e5 Kf2-e3 Bd7-e6
Bh3-g2 Ke5xd6 Ke3-f4 Kd6-e7 Bg2-h3 Ke7-f6 a2-a3) -1.11/16 1} g6 {(g7-g6
Kg2-f2 Rc8xc3 Bh3-f1 Kf6-e6 Rd5-d1 Rc3-a3 e2-e3 Ra3xa2+ Bf1-e2 b5-b4 Kf2-e1
b7-b5 Rd1-d4 b4-b3 Be2-d1 Ra2-b2 Bd1-e2 Ke6-e5 Ke1-d1 Rb2-a2 Rd4-b4 b3-b2)
+5.69/24 2} 32. Rd1 {(Rd5-d1 Rc8xc3 Kg2-f2) -1.91/16 1} Rxc3 {(Rc8xc3
Kg2-f2 Rc3-c2 a2-a3 Rc2-a2 Bh3-f1 Kf6-e5 Rd1-b1 Ra2xa3 e2-e3 Ra3-a2+ Kf2-e1
Ke5xd6 Bf1xb5 Bd7xb5 Rb1xb5 Kd6-c6 Rb5-e5 b7-b5 Ke1-d1 b5-b4 Re5-e6+ Kc6-d5
Re6xg6 Kd5-c4 Rg6-g5 Kc4-c3 Rg5xf5) +6.45/22 2} 33. Rd2 {(Rd1-d2 e4-e3
Rd2-d1 Kf6-e5 Kg2-f1 Rc3-c2 a2-a3 Rc2-d2 Kf1-e1 Rd2xd6 Rd1xd6 Ke5xd6 Bh3-g2
Bd7-c6 Ke1-f1 Kd6-e5 Bg2-h3 Ke5-d4 Bh3-g2 Kd4-c4) -2.18/19 1} Ke5 {(Kf6-e5)
+7.39/21 2} 34. Kh2 {(Kg2-h2 e4-e3 Rd2-d1 Rc3-c2 Bh3-f1 Rc2xa2 Rd1-d3 b5-b4
Rd3xe3+ Ke5xd6 Re3-d3+ Kd6-c6 Bf1-g2+ Kc6-c7 Bg2-f3 Bd7-e6 Rd3-e3 Kc7-d6
Bf3xb7 Be6-c4 Bb7-f3 b4-b3) -2.28/19 1} e3 {(e4-e3 Rd2-d1 Rc3-c2 Bh3-f1
Rc2xa2 Rd1-d3 Ra2-d2 Rd3xe3+ Ke5xd6 Kh2-g1 b5-b4 Re3-b3 Kd6-c5 Rb3-b1
Rd2-c2 Kg1-f2 Bd7-c6 Kf2-e1 Rc2-c3 Ke1-d2 Rc3xg3 Rb1-c1+ Kc5-b6 Rc1-c2
Rg3-g4) +7.97/22 2} 35. Rd1 {(Rd2-d1 Rc3-c2 Bh3-f1 Rc2xa2 Rd1-d3 Ra2-d2
Rd3xe3+ Ke5xd6 Re3-b3 Bd7-c6 Kh2-g1 Kd6-c5 Rb3-c3+ Kc5-d4 Rc3-b3 Kd4-c4
Rb3-b1 b5-b4 e2-e4+ Kc4-c5 Rb1-c1+ Kc5-d6 e4xf5 g6xf5 Bf1-h3 Kd6-e5)
-2.40/22 2} Rc2 {(Rc3-c2) +8.28/21 2} 36. Bf1 {(Bh3-f1 Rc2xa2 Rd1-d3 Ra2-d2
Rd3xe3+ Ke5xd6 Re3-b3 Bd7-c6 Kh2-g1 Kd6-c5 Rb3-c3+ Kc5-d4 Rc3-b3 Kd4-c4
Rb3-b1 b5-b4 e2-e4+ Kc4-c3 e4xf5 g6xf5 Rb1-c1+ Kc3-b2 Rc1-c5 Rd2-d5 Rc5-c4
b4-b3) -2.46/22 2} Rxa2 {(Rc2xa2) +8.82/21 2} 37. Rd3 {(Rd1-d3) -2.46/20 2}
Rd2 {(Ra2-d2) +8.89/21 1} 38. Rxe3+ {(Rd3xe3+ Ke5xd6 Re3-b3 Kd6-c5 Kh2-g1
b5-b4 Rb3-b1 Bd7-c6 Rb1-c1+ Kc5-d4 Rc1-b1 Kd4-c3 Rb1-c1+ Kc3-b2 Rc1-c5
b4-b3 Kg1-f2 Rd2-c2 Rc5-a5 Kb2-b1 Kf2-e3 b3-b2) -2.88/19 1} Kxd6 {(Ke5xd6
Re3-b3 Bd7-c6 Kh2-g1 Kd6-c5 Rb3-c3+ Kc5-b4 Rc3-c1 Kb4-b3 Kg1-f2 b5-b4
Kf2-e1 Rd2-c2 Rc1-d1 Kb3-b2 e2-e3 b4-b3 Rd1-d4 Bc6-e4 Bf1-b5 Rc2-g2 Rd4-c4)
+9.27/21 2} 39. Rb3 {(Re3-b3 Kd6-c5 Rb3-c3+ Kc5-d4 Rc3-b3 Kd4-c4 Rb3-b1
b5-b4) -3.04/20 1} Bc6 {(Bd7-c6) +9.47/20 2} 40. Kg1 {(Kh2-g1 Kd6-c5
Rb3-c3+ Kc5-d4 Rc3-b3 Kd4-c4 Rb3-b1 b5-b4 e2-e4+ Kc4-c3 e4xf5 g6xf5 Rb1-c1+
Rd2-c2 Rc1-e1 b4-b3 Re1-e3+ Kc3-b4 Bf1-d3 Rc2-c1+ Kg1-f2 b3-b2 Bd3xf5
b2-b1B Bf5xb1 Rc1xb1 Re3-e5 Rb1-b2+ Kf2-e3 Rb2-b3+ Ke3-d4 b7-b5 Re5-c5)
-2.96/23 1} Kc5 {(Kd6-c5) +9.84/20 2} 41. Rc3+ {(Rb3-c3+ Kc5-d4 Rc3-b3
Kd4-c4 Rb3-b1 b5-b4 e2-e4+ Kc4-c3 e4xf5 g6xf5 Rb1-c1+ Rd2-c2 Rc1-e1 b4-b3
Re1-e3+ Kc3-b4 Bf1-d3 Rc2-c1+ Kg1-f2 b3-b2 Bd3xf5 b2-b1B Bf5xb1 Rc1xb1
Re3-e5 Rb1-b2+ Kf2-e3 Rb2-b3+ Ke3-d4 b7-b5 Re5-e6 Rb3-c3) -3.01/22 1} Kb4
{(Kc5-b4 Rc3-c1 Kb4-b3 Kg1-f2 b5-b4 Kf2-e1 Rd2-c2 Rc1-d1 Kb3-c3 e2-e3 b4-b3
Rd1-d3+ Kc3-b2 Bf1-e2 Bc6-e4 Rd3-d6 Kb2-c3 Be2-d1 b3-b2 Rd6-b6 Rc2-g2)
+9.94/21 2} 42. Rc1 {(Rc3-c1 Kb4-b3 Kg1-f2 b5-b4 Kf2-e3 Rd2-d6 Bf1-h3
Kb3-b2 Rc1-c4 b4-b3 Rc4-d4 Rd6-d5 Rd4xd5 Bc6xd5 Ke3-d4 Bd5-e4) -2.68/18 1}
Kb3 {(Kb4-b3 e2-e3 b5-b4 Bf1-c4+ Kb3-b2 Rc1-e1 b4-b3 Bc4-f7 Rd2-g2+ Kg1-f1
Rg2xg3 Re1-d1 Kb2-c2 Rd1-d4 Rg3xe3 Bf7xg6 Bc6-e4 Bg6-f7 b3-b2 Rd4-b4 Re3-h3
Bf7-a2 Rh3xh4) +10.29/21 1} 43. Kf2 {(Kg1-f2) -2.98/17 1} b4 {(b5-b4 Bf1-g2
Bc6xg2 Kf2xg2 Rd2xe2+ Kg2-f3 Re2-e7 Kf3-f4 Re7-e4+ Kf4-g5 Re4-g4+ Kg5-f6
Kb3-a2 Rc1-c5 Rg4xg3 Rc5-a5+ Ka2-b2 Ra5-e5 b4-b3 Re5-a5 Kb2-c3 Ra5-b5 b3-b2
Rb5xb7 Kc3-c2 Rb7-c7+ Rg3-c3) +10.41/23 2} 44. Ke1 {(Kf2-e1 Rd2-c2 Rc1-d1
Kb3-c3 Rd1-d3+ Kc3-c4 Rd3-d1 Kc4-c5 Rd1-b1 Bc6-d5 Ke1-d1 b4-b3 Rb1-c1
Bd5-e4 Bf1-h3 Kc5-d4 Rc1-a1 b3-b2 Ra1-a4+ Kd4-e3) -3.55/18 2} Rc2 {(Rd2-c2
Rc1-d1 Kb3-c3 Rd1-d3+ Kc3-b2 Ke1-f2 b4-b3 Bf1-g2 Bc6xg2 Kf2xg2 Rc2xe2+
Kg2-f1 Re2-e4 Rd3-d5 Kb2-c3 Rd5-c5+ Kc3-b4 Rc5-c7 b3-b2 Rc7xb7+ Kb4-c3
Kf1-f2 Re4-c4 Rb7-b6 Kc3-c2 g3-g4 Rc4xg4 Kf2-f3 Rg4xh4) +10.41/28 2} 45.
Rd1 {(Rc1-d1 Kb3-c3 Rd1-d3+ Kc3-c4 Rd3-d1 b4-b3 e2-e3+ Kc4-c3 Rd1-d3+
Kc3-b4 Rd3-d4+ Kb4-c5 Bf1-d3 Rc2-c1+ Ke1-d2 b3-b2 Rd4-d8 Bc6-b5 Rd8-c8+
Kc5-b4 Rc8xc1 b2xc1B+ Kd2xc1 Bb5xd3 Kc1-d2 Bd3-c4 Kd2-d1) -4.12/20 2} Kc3
{(Kb3-c3 Rd1-d3+ Kc3-b2 Ke1-f2 b4-b3 Bf1-g2 Bc6xg2 Kf2xg2 Rc2xe2+ Kg2-f1
Re2-e4 Rd3-d5 Kb2-c3 Rd5-c5+ Kc3-b4 Rc5-c7 b3-b2 Rc7xb7+ Kb4-c3 Kf1-f2
Re4-c4 Kf2-g2 Kc3-c2 Kg2-h2 b2-b1Q Rb7xb1 Kc2xb1) +10.41/27 2} 46. Rd3+
{(Rd1-d3+ Kc3-c4 Rd3-d1 b4-b3 e2-e3+ Kc4-c3 Rd1-d3+ Kc3-b4 Rd3-d4+ Kb4-c5
Bf1-d3 Rc2-c1+ Ke1-d2 b3-b2 Rd4-d8 Bc6-b5 Rd8-c8+ Kc5-b4 Rc8xc1 b2xc1Q+
Kd2xc1 Bb5xd3 Kc1-d2 Bd3-c4 Kd2-d1 b7-b5 Kd1-c2 Kb4-c5 Kc2-d2) -4.13/20 2}
Kb2 {(Kc3-b2 Ke1-f2 b4-b3 Bf1-g2 Bc6xg2 Kf2xg2 Rc2xe2+ Kg2-f3 Re2-e7 Rd3-d6
Kb2-a3 Rd6-b6 Re7-e4 Rb6-b5 b3-b2 Rb5xb7 Re4-b4 Rb7-a7+ Rb4-a4 Ra7xa4+
Ka3xa4 Kf3-f4 Ka4-b4 Kf4-g5 Kb4-b5 g3-g4 f5xg4) +10.41/25 2} 47. Rd2
{(Rd3-d2 b4-b3 e2-e3 Kb2-c3 Rd2-d3+ Kc3-b4 Rd3-d4+ Kb4-c5 Bf1-d3 Rc2-c1+
Ke1-d2 b3-b2 Rd4-d8 Bc6-b5 Rd8-c8+ Kc5-b4 Rc8xc1 b2xc1Q+ Kd2xc1 Bb5xd3)
-4.28/18 2} Rxd2 {(Rc2xd2 Ke1xd2 Bc6-e4 Kd2-e3 b4-b3 Ke3-d4 Kb2-a3 Kd4-e5
b3-b2 Bf1-h3 Be4-c6 Bh3-g2 Ka3-a4 Ke5-d6 b2-b1Q Kd6-c7) +10.45/21 2} 48.
Kxd2 {(Ke1xd2 b4-b3 e2-e4 Bc6xe4 Bf1-c4 Kb2-a3 Bc4xb3 Ka3xb3 Kd2-e1 b7-b5
Ke1-d2) -8.92/20 1} Be4 {(Bc6-e4 Bf1-h3 b4-b3 g3-g4 f5xg4 Bh3xg4 h5xg4
Kd2-e3 Kb2-a1 Ke3xe4 b3-b2 h4-h5 b2-b1Q+ Ke4-f4 g6xh5 e2-e3 b7-b5 Kf4-g5
Qb1-e4) +10.48/21 1} 49. e3 {(e2-e3 b4-b3 Bf1-c4 Kb2-a3 Bc4xb3 Ka3xb3
Kd2-d1 b7-b5 Kd1-c1 b5-b4 Kc1-d2 Kb3-c4 Kd2-d1) -9.76/21 2} b3 {(b4-b3
Bf1-e2 Kb2-a3 Kd2-c3 b3-b2 Kc3-d4 b2-b1Q Kd4-e5 Qb1-b2+ Ke5-e6 Qb2xe2
Ke6-e5 b7-b5 g3-g4 h5xg4 Ke5-d6 Qe2xe3 Kd6-c7 Qe3-c1+ Kc7-d6 b5-b4 h4-h5
Qc1-c6+ Kd6-e5 g6xh5 Ke5-f4 b4-b3) +10.48/26 2} 50. Bc4 {(Bf1-c4 Kb2-a3
Bc4xb3) -11.42/21 2} Ka3 {(Kb2-a3 Kd2-c3 b3-b2 Bc4-d3 Be4xd3 Kc3-d4 b2-b1Q
g3-g4 h5xg4 Kd4-e5 Qb1-b2+ Ke5-e6 Qb2-b6+ Ke6-f7 g4-g3 h4-h5 g6xh5 Kf7-g7
Qb6xe3 Kg7-f7 Bd3-e4 Kf7-f6 g3-g2) +10.48/25 2} 51. Bxb3 {(Bc4xb3 Ka3xb3
Kd2-d1 b7-b5) -12.01/21 2} Kxb3 {(Ka3xb3 Kd2-e1 Kb3-c3 Ke1-f1 Kc3-d2 Kf1-f2
b7-b5 g3-g4 f5xg4 Kf2-g3 Kd2xe3 Kg3-h2 b5-b4 Kh2-g3 b4-b3 Kg3-h2 b3-b2
Kh2-g3 b2-b1Q Kg3-h2 Qb1-b2+ Kh2-g3 Qb2-g2+) +M12/31 2} 52. Kd1 {(Kd2-d1
b7-b5 Kd1-e2 b5-b4 Ke2-f2 Kb3-c4 g3-g4 h5xg4 Kf2-e1 b4-b3 Ke1-e2 b3-b2)
-16.43/24 2} b5 {(b7-b5 Kd1-e2 Kb3-c2 g3-g4 f5xg4 Ke2-f2 Kc2-d2 Kf2-g3
Kd2xe3 Kg3-h2 b5-b4 Kh2-g3 b4-b3 Kg3-h2 b3-b2 Kh2-g3 b2-b1Q Kg3-h2 Qb1-b2+
Kh2-g3 Qb2-g2+) +M11/31 2} 53. Ke2 {(Kd1-e2 Kb3-c4 Ke2-d2 b5-b4 Kd2-e2
b4-b3 g3-g4 h5xg4 Ke2-e1) -16.43/20 2} Kc2 {(Kb3-c2 g3-g4 f5xg4 Ke2-f2
Kc2-d2 Kf2-g3 Kd2xe3 Kg3-h2 b5-b4 Kh2-g3 b4-b3 Kg3-h2 b3-b2 Kh2-g3 b2-b1Q
Kg3-h2 Qb1-b2+ Kh2-g3 Qb2-g2+) +M10/33 2} 54. g4 {(g3-g4 f5xg4 Ke2-f2 b5-b4
Kf2-e2 Kc2-c3 Ke2-f2 b4-b3 Kf2-e1) -18.63/19 2} fxg4 {(f5xg4 Ke2-f2 Kc2-d2
Kf2-g3 Kd2xe3 Kg3-h2 b5-b4 Kh2-g3 b4-b3 Kg3-h2 b3-b2 Kh2-g3 b2-b1Q Kg3-h2
Qb1-b2+ Kh2-g3 Qb2-g2+) +M9/38 2} 55. Kf2 {(Ke2-f2 b5-b4 Kf2-g3 Kc2-d2
Kg3-f4 b4-b3 Kf4xe4 b3-b2 Ke4-e5 b2-b1Q e3-e4 g4-g3 Ke5-f6 Qb1-f1+ Kf6xg6
Qf1-a6+ Kg6-f5 Qa6-b5+ e4-e5 Qb5-d3+ Kf5-f6 Qd3-f1+ Kf6-g6 g3-g2 e5-e6
Qf1-d3+ Kg6xh5 g2-g1Q) -16.88/20 2} Kd2 {(Kc2-d2 Kf2-g3 Kd2xe3 Kg3-h2 b5-b4
Kh2-g3 b4-b3 Kg3-h2 b3-b2 Kh2-g3 b2-b1Q Kg3-h2 Qb1-b2+ Kh2-g3 Qb2-g2+)
+M8/46 1} 56. Kg3 {(Kf2-g3 Kd2xe3 Kg3-h2 b5-b4) -M7/19 2} Kxe3 {(Kd2xe3
Kg3-h2 b5-b4 Kh2-g3 b4-b3 Kg3-h2 b3-b2 Kh2-g3 b2-b1Q Kg3-h2 Qb1-b2+ Kh2-g3
Qb2-g2+) +M7/56 1} 57. Kh2 {(Kg3-h2 b5-b4 Kh2-g3 b4-b3 Kg3-h2 b3-b2 Kh2-g3
b2-b1Q Kg3-h2 Qb1-c2+ Kh2-g3 Qc2-g2+) -M6/22 2} b4 {(b5-b4 Kh2-g3 b4-b3
Kg3-h2 b3-b2 Kh2-g3 b2-b1Q Kg3-h2 Qb1-b2+ Kh2-g3 Qb2-g2+) +M6/81 2} 58. Kg3
{(Kh2-g3 b4-b3 Kg3-h2 b3-b2 Kh2-g3 b2-b1Q Kg3-h2 Qb1-c2+ Kh2-g3 Qc2-g2+)
-M5/22 1} b3 {(b4-b3 Kg3-h2 b3-b2 Kh2-g3 b2-b1Q Kg3-h2 Qb1-b2+ Kh2-g3
Qb2-g2+) +M5/115 2} 59. Kh2 {(Kg3-h2 b3-b2 Kh2-g3 b2-b1Q) -M4/21 1} b2
{0.00/128 0} 60. Kg3 {(Kh2-g3 b2-b1Q Kg3-h2 Qb1-c2+ Kh2-g3 Qc2-g2+) -M3/21
1} b1=Q 61. Kh2 {(Kg3-h2 Qb1-c2+ Kh2-g3 Qc2-g2+) -M2/20 1} Qh1+ 62. Kg3
{(Kh2-g3 Qh1-g1+) -M1/17 1} Qg1# 0-1[/pgn]

[Guenther]

This is a total thread abuse by cheesequack...

For the purposes of documentation, release announcements, and progress reports, I've started a thread here for Blunder. I'll also use this to post general updates and ideas I'm currently experimenting with. There may be a tad bit of rambling here or there if I get particularly focused on a certain idea, but I promise I'll keep that to a minimum :wink:

forum3/viewtopic.php?f=2&t=78800

Never seen someone more narcisstic and obsessed, very unhealthy.

[Chessqueen]

What is wrong with somebody trying to find out if X engine is equal worse or better than another engine, there has been thousasnds of tests here, but when ChessQueen does it, it is evil, and accused of being narcisstic and obsessed. I have never seeing anybody here who hate ChessQueen more than you. Have you been baptized? https://www.bing.com/videos/search?q=ha ... &FORM=VIRE

Rank Engine Score Bo Bl S-B
1 Booot71_avx2 22.5/25 · ·· ·· ·· ·· ·· ·· ·· ·· ·· ·· · 1111111111=111111=110=111? 56.25
2 Blunder-8.5.5-popcnt 2.5/25 0000000000=000000=001=000? · ·· ·· ·· ·· ·· ·· ·· ·· ·· ·· · 56.25


25 games played / Tournament is finished

Tournament start: 2023.02.26, 11:28:43
Latest update: 2023.03.03, 05:57:59
Site/ Country: DESKTOP-OFQ3C0P, United States
Level: 3 Seconds
Hardware: Intel(R) Core(TM) i7-4770 CPU @ 3.40GHz with 16.0 GB Memory
Operating system: Windows 10 Home Home Edition (Build 9200) 64 bit
PGN-File: 8/8/8/6k1/8/5BPb/5K1P/8 b - - 2 1
Table created with: Arena 3.5.1