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#2
How to post games, videos, images to the forum
lichess.org/forum/lichess-feedback/how-to-post-games-videos-and-images-to-the-forum

Lichess Blog:
lichess.org/blog

How the game analysis works:
lichess.org/blog/WFvLpiQAACMA8e9D/learn-from-your-mistakes

Introducing Lichess Curator. Brilliant studies by brilliant people.
lichess.org/blog/XJ-tZRAAACYAhWvY/paging-all-content-creators
lichess.org/inbox/new?user=lovlas.

Shadow Bans
lichess.org/forum/lichess-feedback/show-cheater-flag--i-am-marked-as-cheater-but-it-is-not-visible-to-me-?page=2#19

The AI Cheat Detecting Code
github.com/clarkerubber/irwin

Lichess API
lichess.org/api

Lichess Lagging?
lichess.org/lag

How Stockfish plays chess.
www.quora.com/What-is-the-algorithm-behind-Stockfish-the-chess-engine

Stockfish source.
github.com/official-stockfish/Stockfish

Eval function in Stockfish
github.com/official-stockfish/Stockfish/blob/master/src/evaluate.cpp
#5
api.semanticscholar.org/CorpusID:8505573
"Besides, the method allows to propose strategies that are clearly readable and useable for a purpose such as teaching chess"
22:36
api.semanticscholar.org/CorpusID:36406265
Influence of Search Depth on Position Evaluation
22:43
Automated Chess Tutor
api.semanticscholar.org/CorpusID:14100018
22:44
"In this paper, we present some core mechanisms for automated commenting in terms of relevant goals to be achieved or preserved in a given position."
22:44
The influence of context on information processing
api.semanticscholar.org/CorpusID:211217267
pubmed.ncbi.nlm.nih.gov/32086661/
22:48
Keywords: Chess game; Cognitive load; Contextual characteristics; Information processing
22:53
www.semanticscholar.org/paper/Conditional-Logic-is-Complete-for-Convexity-in-the-Marti/38bcd56984c2c388026e0fa705aa6b931edbe472

leelanalysis.com/
#6
Automated Chess Tutor
api.semanticscholar.org/CorpusID:14100018
PDF is here
www.researchgate.net/publication/220962518_Automated_Chess_Tutor

A 13 page paper on creating a chess tutor program.
Abstract
While recently the strength of chess-playing programs has grown immensely, their capability of explaining in human understandable terms why some moves are good or bad has enjoyed little attention. Progress towards programs with an ability to provide intelligent commentary on chess games, either played by a program or by a human, has been negligible in comparison with the progress concerning playing strength. The typical style of a program’s “comments” (in terms of the best variations and their numerical scores) is of little use to a human who wants to learn important concepts behind the variations. In this paper, we present some core mechanisms for automated commenting in terms of relevant goals to be achieved or preserved in a given position. By combining these mechanisms with an actual chess engine we were able to transform this engine into a chess tutor/annotator that is capable of generating rather intelligent commentary. The main advantages of our work over related approaches are: (a) it has the ability to act as a tutor for the whole game of chess, and (b) it has a relatively solid chess understanding and is thus able to adequately comment on positional aspects.
#10
Graphing tournament games played versus ELO rating .

The author says
"I have only tested the power law with data up to at least 199 games and with FIDE ratings from players who enter the domain quite young."
en.chessbase.com/post/the-learning-curve-for-chess-skill

It remains to be seen if a power law equation would fit an amateur player's improvement.

See also:
http://beginchess.com/2009/08/02/anatomy-of-a-chess-player-from-beginner-to-expert/

http://www.uschess.org/index.php/June/Moving-up-the-Ladder-A-Class-Player-on-Gaining-200-Rating-Points.html/

Picking the Amateur’s Mind – Predicting Chess Player Strength from Game Annotations
www.aclweb.org/anthology/C14-1031.pdf

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