This week
Pat is on the road against KC. We project 14.7 receiving yards on 1.9 targets. The number comes out of a drive-level simulation of the game rather than a season average — it asks how many possessions his side is likely to get, what they do with them, and how much of that flows through him.
How much he's on the field
47% — that's Pat's average snap share over 15 games. That's a limited role, and it caps everything else on this page. A player on a third of the snaps can't produce like a starter no matter how efficient he is, and the projection reflects the opportunity rather than the talent. This is the number to check first on any football page. Everything else here is downstream of it.
What kind of receiver he is
Pat has caught 35 of 53 targets (66%) for 412 yards and 1 touchdown — 7.8 yards per target. Yards per target is the honest efficiency number here, because catch rate mostly measures how far downfield he's used: a slot receiver on screens will always catch more of them than a deep threat, without being better.
His last 5 games
Over that stretch Pat has 140 total yards. A handful of games is thin evidence in a seventeen-game season. It nudges the projection; it doesn't drive it.
How the model reads him
Pat's projection starts with the game, not with him. We simulate the matchup drive by drive — how many possessions each side gets, how far they travel, how often they score — and then ask what share of that flows through him given his role. That ordering matters: a productive player on a team that runs 55 plays a game has a lower ceiling than a lesser one on a team that runs 70.
What we'd flag
Read this knowing the limits. A seventeen-game season makes every rate noisy; game script can invert a player's usage inside one afternoon; and depth-chart changes often surface too late to be in the projection.