Quote:
Originally Posted by Colin_Piddle
It is always a realistic goal. How hard is it to achieve at $70 abi? Pretty hard
Thanks for the input.
To achieve this long-term I believe you'd have to play a very exploitative game vs bad regs and recs alike and try to be balanced as possble vs. perceived good regs. before moving into a playstyle heavily influenced by GTO (when good regs catch on) whilst also accumulating enough of a sample on the various bad/avg. regs out there to find out ways in which they deviate from an unexploitable strategy and target these mistakes.
Understanding how the good-reg/bad-reg/rec density of an MTT playerpool affects perceived EV ROI% is also something I'd really like to look into but I don't have enough mathematical understanding to apply.
E.g. (And this is an excessively simplified version of reality that is probably completely bull****)
"I would beat this tournament for 10% true ROI% if this tournament was made up of 100% this player-type and my own entry" is how I'm defining these ROI% within different player-types. Very simplistic again but trying to illustrate a point.
121 players in this hypothetical tournament with 3 simplified player-types.
40 good regs. Vs. True ROI% = -10% (B/E in game, -10% rake)
40 bad regs. Vs. True ROI% = 10%
40 recs. Vs True ROI% = 30%
1 hero
Given this example, True ROI% would equal 10% as it would be an average of the 3 player-types.
Example as used in previous post:
36 good regs. Vs. True ROI% = -10%
72 bad regs. Vs. True ROI% = 10%
12 recs. Vs. True ROI% = 30%
1 hero
True ROI = 6%, using same method.
My model, estimations and understanding of the maths is probably completely off but if anyone could help me understand how modelling true ROI% based off playerpools works I'd be immensely grateful.