The STL-LAA game was a reminder of what a low-run-environment matchup can look like when everything breaks right — one run total is an outlier, but we were pointed at the right number and the right direction. The two pushes are a feature of betting totals, not a bug: when you're right about the run environment and the game lands on the number, that's the market doing its job. It stings a little, but it means the read was essentially correct.
The LAD-PHI loss is worth sitting with. Nine and a half was a number that acknowledged both offenses were capable of running it up, and they did exactly that. Fourteen runs in a game with two legitimate rotations suggests the ballpark context and the day's conditions mattered more than the model weighted them. That's an honest note for the process going forward.
On the DFS side, the pitching projections for Cole and Cavalli translated into real production at the top of the leaderboard. The Alcantara miss and the Ohtani zero are the kind of variance that comes with a full slate — you can be right on the process and still take the loss on the scoreboard. The Ortiz performance is the most interesting data point: when a player puts up 31 points against a projection of 6.18, that's not model error, that's a player having the game of his month. The model isn't built to predict that. No model is.
We go again Thursday. The process stays the same: call what the data actually supports, own what doesn't land, and never dress up a push as a win just because the math was close.