This week
Rhamondre is hosting GB. We project 44.6 rushing yards, 18.5 receiving yards on 2.9 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
Rhamondre has averaged 64% of his team's snaps across 20 games. That's a rotational-to-starter share. It's the number most likely to move his projection week to week, because a swing of ten points of snap share moves everything downstream with it. 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.
What kind of back he is
Rhamondre has 233 carries for 1030 yards (4.4 a carry) and 7 rushing touchdowns. He's also seen 64 targets for 529 yards — pass-game work is what separates a back who plays on third down from one who leaves the field, and it's worth more to a projection than the same yardage on the ground. Running-back yardage swings hard on the blocking in front of him, which is why the model weighs opportunity — carries and targets — above efficiency.
His last 5 games
Over that stretch Rhamondre has 400 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 Rhamondre 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.