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datashrimp

1,419 karma · joined September 9, 2017

Founding Partner of Applied Data Science Partners (https://adsp.ai)

Author of Generative Deep Learning: Teaching Machines To Paint, Write, Compose and Play (https://www.amazon.com/Generative-Deep-Learning-Teaching-Machines/dp/1492041947/)

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datashrimp··on How to Calculate the Trappiest Openings in Chess Using Stats
I'll see what we can do!
datashrimp··on How to Calculate the Trappiest Openings in Chess Using Stats
That's good to hear! Blackmar-Diemer is favoured by this ranking system as although it's a longish line, the opponent's move are all fairly probable, with the least probable being Qxd4 at still around 20%.
datashrimp··on How to Calculate the Trappiest Openings in Chess Using Stats
Great idea!
datashrimp··on How to Calculate the Trappiest Openings in Chess Using Stats
Absolutely - in the repo, you can adjust for the skill of the opponent https://github.com/davidADSP/chess-trap-scorer.

The analysis so far has been for 1600-1800 players.

datashrimp··on How to Calculate the Trappiest Openings in Chess Using Stats
The longer lines are technically less probable, like you say - I was trying to capture the notion that a trap is more impressive if on average, moves are likely. How would you define 'sub-optimal' move in your proposal? It's a good idea -would be interesting to see it in action!