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While everyone’s focused on Saturday College Football right now and NFL tomorrow… .. a market maker on Kalshi is quietly trying to get down $7K on a UFC fight to go the distance Selene’s Maker Radar found $42K of liquidity on Kalshi available to take at -610 odds (or 86%) for Despaigne and Tuivasa to not go the distance That means the market maker offering that liquidity put in a $7K resting order at +610 odds for them to go the distance, the opposite side of what’s being offered He’s now just waiting to get matched and for people to buy into him to fill his order But you don’t have to wait to get his same order The Maker Radar let us know that FanDuel is offering that same bet at +610 Grab it before it bumps

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Does anyone else ever type 999999 into FanDuel to figure out what their limits are? No? Just me?

There's a $49K wall on Kalshi offering the Bengals at +134. The market makers (hello SIG) posting it are holding Houston, and that's the biggest wall on the board today That’s not to mention the $85K wall on Polymarket and $20K limits on Pinnacle And FanDuel’s -134 price is profitable to all of them

🔥BANGGG 5/5 legs on Underdog💰 ✅ Ronny Simon Over 0.5 hits ✅ George Kirby Under 5.5 strikeouts ✅ Jose Trevino Over 0.5 hits + runs + RBIs ✅ Jared Jones Over 5.5 strikeouts ✅ Cam Smith Under 1.5 hits + runs + RBIs We’re literally just handing out 20% EV

3/5 legs have already cashed ✅ Ronny Simon Over 0.5 hits ✅ Jose Trevino Over 0.5 hits + runs + RBIs ✅ Jared Jones Over 5.5 strikeouts Can George Kirby and Cam Smith take us home?

We built a complete baseball projection model to calculate the EV of every MLB player prop  The process of building the model was pretty interesting so thought I’d share some of it 1/ The first step was projecting the average for every stat and player combo. Sounds simple until you start to think about everything that actually moves a stat like pitcher strikeouts 2/ For a single K prop you're pulling things like: the pitcher's K rate, matchup stats, how deep he’s likely to go, park and weather, the umpire’s zone, recent form vs. full track record. The list goes on and on 3/ Then you’ve got to determine the relationship between all those variables and their weights. Plenty of stats look predictive and aren't. You test each variable, check whether it still moves the outcome once everything else is accounted for, and validate it on games the model hasn't seen. Now do that all over again for every single stat 4/ But projecting the average is only half the battle. Just having a projected average doesn’t tell you the percent likelihood of it happening. An average of 6.2 Ks doesn't tell you the chance of Under 4.5 or Over 6.5 5/ Two pitchers can both average 6 Ks and be completely different bets. One goes 5, 6, 7, 6. The other goes 2, 10, 3, 9. Same average. The first almost never clears 6.5. The second does it half the time 6/ So step two is turning every projection into a real % for every line. That's our fair value The resulting projection and probability is what we use as our fair value to compare against all the current lines offered on sportsbook and prediction markets. The gap is our EV What do you think, should we build an NFL projection model next?