TL;DR – @radtaylor9’s thoughts mirror my own on the issue of quantifying edge and then applying it to bankroll management + utilize opponent tracking software / scrape opponent lineups to create a power ranking + a weighted recent results ranking to combat players now purchasing good tout plays + contest entering times for non-H2Hs.
Long Version
@rdtaylor9 – I think your post is closest to the correct answer and basically what I concluded using my past experience (+ the insights from @mlbmodel). It looks like @znmeb touched on something I tried in the past in his first response.
The only thing other thing I tried doing to some success was scraping the lineups of all the contests I could (against the ToS so gets tricky/technical) and evaluating the strength of the plays chosen by each contestant and creating an opponent power ranking. This actually led me to finding an RG Top 10 TPOY player who was a negative EV player in cash games. I ended up scooping almost all of his 2013-2014 NFL H2Hs until he finally stopped posting them. However, after this one player stopped posting H2Hs, I noticed something with several players the more they played – their results drastically and rapidly improved. One would assume that a player would gradually get better at DFS with more experience, but there were several players that went from hugely losing players to winning players seemingly overnight. My hypothesis is that they started using a site like this one to get better projections / plays which made all my old data useless and any potential edge calculation “impossible”. It was this obvious finding that led me to my question of diminishing edge in the other thread.
The above, in conjunction with all the key pieces @rdtaylor9 already pointed out, IMO, is the only way to truly determine a H2H edge in any predictive manner and potentially apply it to bankroll management. Tools to track results are absolutely something every player should have, but they aren’t predictive and will lead you to overestimating your actual edge – especially in a static priced DFS environment.
Speaking of H2H, game selection also will determine this edge quantification process. IMO, if you’re playing 50/50s or double/triple/quadruple ups, if you do maintain an opponent tracking ranking through scraping, you’re best severed by joining contests that are as close to full as possible so you can identify the strength of the field. For instance, even in as low as $2 contests, you may sometimes find that the first 10 entrants in a 100 field 50/50 are condia, 1ucror, 00oreo00, etc. and you’re already playing at a far smaller edge than you would in a normal 50/50. I have actually seen from some of the data I scraped from some qualifiers that is almost the opposite – that if a respected “pro” puts in the max amount of entries early, you’ll see the participation from the other pros fall below their normal participation number and the edge is actually greater than normal qualifiers. A good example of this was 2015 MLB I believe when BeepImaJeep would put his entries in early and you’d see other “pros” put in a much smaller amount of lineups than normal. Only after he maxed out his live final seats did you see some of those same pros start entering their normal amount of lineups again.
Obviously, the sooner you join a contest, the more limited the opponent information is, the harder it is to even approximate field strength / edge.
It’s just so super complicated and so hard to actually quantify that it’s a really great thought experiment / learning exercise, but far more complicated than sports betting. Really great discussion though, this is quickly becoming a daily stop of mine.