Greetings,
Was struggling with this question today. To properly parameterize and backtest a model you have to provide the spread\odds of every game. Ideally I'd imagine that you want all those spreads\odds to come from the same book, and not be "best available" or "average". So, say I find a +EV model using historical lines from Pinnacle. Is it reasonable to assume that I could take the same model and apply it to another book (with the same juice), like say BetOnline? Since I'm a US player, Pinnacle is out for me.
My first answer was that when my Pinnacle model took a side in a game, I could bet anywhere so long as the line was equal or "better" than Pinnacle, and that makes sense, but its also an additional parameter in the model that is much harder to backtest (something like "bet only when Pinnacle is not the best available line").
Any thoughts? Do you build models\systems that apply only to particular sportsbooks and fail on others?
Thanks,
podonne
Was struggling with this question today. To properly parameterize and backtest a model you have to provide the spread\odds of every game. Ideally I'd imagine that you want all those spreads\odds to come from the same book, and not be "best available" or "average". So, say I find a +EV model using historical lines from Pinnacle. Is it reasonable to assume that I could take the same model and apply it to another book (with the same juice), like say BetOnline? Since I'm a US player, Pinnacle is out for me.
My first answer was that when my Pinnacle model took a side in a game, I could bet anywhere so long as the line was equal or "better" than Pinnacle, and that makes sense, but its also an additional parameter in the model that is much harder to backtest (something like "bet only when Pinnacle is not the best available line").
Any thoughts? Do you build models\systems that apply only to particular sportsbooks and fail on others?
Thanks,
podonne