This week
Matthew is on the road against ATL. We project 16 receiving yards on 2 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
Matthew has averaged 47% of his team's snaps across 3 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. Opportunity is the first thing the model reads and the last thing it gives up on — production without snaps is noise, and snaps without production usually corrects.
His last 3 games
Over that stretch Matthew has 70 total yards. In a sport with seventeen games, a five-game window is closer to an anecdote than a trend — which is why usage, not this, anchors the number.
How the model reads him
The number on Matthew is a share of a simulated game. First the matchup: possessions, field position, how each offense is likely to move. Then his slice of it, set by usage rather than by reputation. How those pieces are weighted is ours and gets re-tuned against results; the output is published and graded, which is the half you can check.
What we'd flag
Football's sample sizes are brutal — seventeen games a season means a "trend" is often four data points. Injuries and game script move usage more than talent does week to week, and a blowout can erase a starter's second half. For Matthew specifically, Matthew has only 3 games in our log, so every rate on this page is fragile.