The Site ratings at slow time controls can be quite reliable for servers where strong players congregate (ICC, FICS to name a few) as the ratings VERY closely reflect your true playing strength if you've played enough games. For very standardized rating systems such as USCF and FIDE/ELO, you will notice that the different rating classes tend to point to the ...
An unofficial list of the highest Tournament Performance Ratings (TPRs) on record in standard FIDE classical tournaments since 1970 is here: https://deletionpedia.org/en/List_of_highest_chess_Tournament_Performance_Ratings
Because this list was last updated in May 2015, high TPRs after that would not be included. However, I'm tentatively doubtful there has ...
TPR calculators and expected rating change.
Basically Performance rating is the average of your opponent's ratings with an adjustment based on the score of the game. For each win, you add your opponent's rating + 400, a draw is just your ...
For a very accurate rank of a player's quality, you can use the excellent tool provided by www.chess-db.com. It lets you upload your games and after some minutes it outputs the quality of both players in percentage compared with the best moves of a strong engine.
This is the page to upload a PGN file:
And this is ...
Section 1.48 of the FIDE Title Regulations effective from 1 July 2017 specifies how the performance rating is calculated. The average rating of the opponents is adjusted by a value determined by looking up the percentage score in a table.
For example, after Round 12 of the 2018 Candidates Tournament, Ding Liren had 6.5 out of 12 points, for a rounded ...
Yes, a double check is when two pieces give check at the same time. It doesn't matter how you got to that position. As to whether there's an error on that wiki, it's probably best to try to ask its author. Maybe they can provide the full list of positions for you to compare.
I can think of two ways of giving double check while promoting. One is where you ...
Under FIDE rules, the performance rating is calculated by taking the average of your opponent's ratings, and then adding a factor from a table based on performance. Let's say you played 5 games, against people rated 1380, 1390, 1400, 1430, and 1900, and had 3 wins and 2 losses. You scored 60%, or 0.6. According to the table in section 1.49 of this ...
A: Let's use bishop for our example. xrayBishopAttacks works if we have the following position:
but it doesn't work if you have this:
The f3 knight is not pinned because there is something else behind it. obstructed takes this into consideration.
B: Once you get the pinned pieces, you can just do XAND to check if the piece you want to move is pinned. If ...
The real speed in bitboards is created by precomputing the bitboards for every instance. This means that you already have the attacked squares for a rook on d4 and every other piece on every square. Even faster is to use magic bitboards, but that is too complicated for a forum. Although both are written in c, I suggest Crafty to understand bitboards ...
There is a game theory of why 1st round NFL drafts don't perform as well as expected. The reasoning is that the player had an above average couple of games and returned to his average performance. By the same logic, there are later round drafts who have stellar careers.
I'm not going to make a judgement based on three games, or even your archive on ...
Your code looks fine. We can't really give you the exact cause, but we can give you some hints.
Q: How did you generate sliding pieces?
Sliding piece generation is typically the slowest because we need to check the enemy pieces. Stockfish uses magic bitboard, which is also used by Houdini and Komodo.
Q: How did you generate legal moves?
Stockfish always ...
Caffeine increases 'manual productivity' while decreasing creativity commensurately. That is, if you're packing groceries or stocking shelves, tank up. If you need to think, ease up. YMMV of course.
There is no silver bullet. Eat right, sleep plenty, and exercise.
Given the new requirements, I tried to do a calculation. I couldn't find one on the internet suitable for this task, but this one suggests that for one game between a 2150 and a 2450 player, the following probabilities hold (from the standpoint of the weaker player):
To get a score of 4.5 or more, which is needed to score a ...
Answering my own question here. I've managed to increase the speed of the move generation code, by implementing the pinnedPices() routine.
The C++ version runs Perft (start_pos, 6) under ~3.5 secs, including hash updates.
Here's some Java code for reference (messy indentation, sorry):
//return bitboard of pinned pieces for player side
public static long ...
The bigger weights file corresponds to a larger Neural Network, which means more computation per node, but better evaluation per node.This is expected, and there is nothing that can make a bigger NN as fast as a smaller NN. The best solution is to use a small NN for blitz time control. I would personally recommend LD2 (available at Lc0.org/LD2)
python-chess already has the built in utilities to handle conversions. Here is an example:
board = chess.Board('rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1')
WP = board.pieces(chess.PAWN, chess.WHITE)
BP = board.pieces(chess.PAWN, chess.BLACK)
print (int(WP), int (BP))
print (list(WP), list(BP))
print ("\nWHITE PAWNS:\n" + str(...
Yes, it was luck or you are stronger in longer time controls. No one can really say which is the case for you personally, considering you only played a few longer games. To find out you just have to play more and see.
Move generation has been tested to death in modern chess engines, and the current consensus is that the following two approaches are optimal for sliding pieces:
A lookup table indexed by PEXT of the relevant occupancies ("Fancy PEXT Bitboards")
A lookup table indexed by the higher order bits of the product of the Bitboard of relevant occupancies ...
Performance rating doesn't make sense for a single game, it only makes sense if you play a bunch of games (at least 4 or 5) in a chess event. For example, in a round robin tournament with 4 players, where every player plays twice against every opponent (with White and Black), every player plays 6 games in total, and the performance rating will give useful ...
The menu for the analysis board has sliders for CPUs and memory (see screenshot below). Have you tried adjusting those? Maybe whether they actually work or not depends on which browser you are using. If they don't, I think this question would be best suited for the Lichess feedback forum, since it might be a bug.
It probably depends on the person and how often you drink energy drinks to begin with. If you don't ordinarily drink them, I would advise against it. I made the mistake of taking an energy drink before a tournament even though i ordinarily didn't drink them. It increased my energy at the expense of focus. My mind was racing and i couldn't concentrate. ...
Yes, the case you mentioned would also qualify as a double check.
But it also depends on what your definitions are. If the Perft result does consider that to not be a double check, it doesn't mean you have to abide by it.
At least for some players, yes, although how many games, the type of games, and in what period of time, causes burn out, I would assume varies from player to player. I've been reading "Bent Larsen's Best Games," and he mentions how he was drained after playing several consecutive events, but after a month's vacation, came back refreshed.
I found these sources for "meditation" among the past 2 worlds champions:
Q : Do you practise meditation and if so, how effective do you find it?
A: I don’t meditate regularly and hence I do not know the extent to which it can help.
To convert a single bitboard to a numpy array:
def bitboard_to_array(bb: int) -> np.ndarray:
s = 8 * np.arange(7, -1, -1, dtype=np.uint64)
b = (bb >> s).astype(np.uint8)
b = np.unpackbits(b, bitorder="little")
return b.reshape(8, 8)
To convert multiple bitboards to a numpy array:
def bitboards_to_array(bb: np.ndarray) ->...
In wild games with opposite side castling, etc anything is possible. Chances to win for the underdog increase. With your attacking style you are more likely to see much above average (but also much below average) performance than if you played quiet positional chess.
That being said, you have a decent understanding on where to put the pieces. Still plenty ...
chess.com CAPS. Compare CAPS score from chess.com (requires subscription), to table found in a graphic on this:
Also of interest:
Note of caution: Caps scores for anyone particular game ...
What you're asking does not exist by my knowledge. However, this is my idea:
You'll need samples with the following features, (1) Chess position, (2) Move made in the position, (3) Rating of the player that made the move.
Let's say you have 1 billion samples. You can train a computer algorithm on these samples that can predict for each move in a position ...