Eric Truett

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A couple of comments, one theoretical and one practical. The theoretical comment is that the "no negatively correlated players" rule is likely a bad idea, especially as the slate size...

I would set these values when you create players. In my opinion, do not use load_players_from_csv because it assumes your projections are in the DK salary file, which is likely...

I thought about this some more and I can explain it better. The basic premise is that individual lineup optimization is a different problem than multi-lineup optimization. There are certain...

I would start with a simple question - why are you projecting TE (or some other position) to have scores that would allow them to land in your optimal lineup...

Change ``` @SitesRegistry.register_settings class DraftKingsFootballSettings(DraftKingsSettings): sport = Sport.FOOTBALL min_games = 2 positions = [ LineupPosition('QB', ('QB',)), LineupPosition('RB', ('RB',)), LineupPosition('RB', ('RB',)), LineupPosition('WR', ('WR',)), LineupPosition('WR', ('WR',)), LineupPosition('WR', ('WR',)), LineupPosition('TE', ('TE',)), LineupPosition('FLEX', ('WR',...

Can you post your full code - I just tried the line of code you posted and did not encounter any errors.

I would load the players using load_players rather than load_player_from_csv. This allows you to preprocess data to your heart's content. So, here, it could look like the following: ``` import...

Find the player with ```get_player_by_id``` and then use ```optimizer.remove_player``` If you want to remove them all in one fell swoop, then you could use the following: ``` for p in...