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Posted

Honestly, the lineup roulette right before gametime is where most models fall apart. I started tracking beat reporter tweets for last-minute injury updates and it's been a gamechanger for those last-second bets.

Posted

Yeah the betting perspective angle is interesting because you really need a separate set of data for sarp money movements vs public betting percentages, those two often tell completely different stories about a game.

Posted

Wait so we can actually pull recent pass map data for EPL squads and stack that against sportsbook movement before the overnights adjust? That lveel of prep for like Arsenal games could finally pin down why the sharp side always overreacts to a fullback rotation before the line moves real late.

Posted

Tracking line movements before kickoff tells you more than half the stat sheets people cling to. Books adjust late for a reaon and it’s rarely because they got generous.

Posted

I like using xG differentials for soccer squads esecially when a team like Brighton keeps underperforming their numbers it’s just a matter of time before the odds catch up and you can pounce on some nice plus money spots.

Posted

I tracked total fouls in a WNBA game last week after noticing one ref crew averages 6 more whistles than league mean, cashed the over easily while everyone else stared at point props.

Posted

I get the appeal but I think too many people lean on metrics as a crutch. You can watch a whole season of xG and still miss that a key midfielder is out sick right before the match.

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