Flop Characteristics and their Effect on EV

In this video, I show the data-driven approach I used to try to quantify the effect of these flop characteristics - such as the suitedness, connectedness, high-card, and other variables - on the overall EV of our range. For the analysis, I looked at scenario where the CO raised preflop to 4 BB and the BB was the only defender. The pot size is 8.5 BB and stack sizes are 100 BB.

I estimated ranges for the CO and BB and entered them into a solver. I then generated a data set of 184 flops (using PioSolver’s 184-flop sample) using GTO+. This included the Equity and EV of both ranges across all of the flops. Utilizing this data and the flop characteristics, I created a linear regression model to quantify the effect each flop characteristic has on the overall EV of the board.

For more of my work, check out my website at https://lukich.io

Видео Flop Characteristics and their Effect on EV канала Michael Lukich