He has beaten his expected points in 2 of 3 seasons. Whether that is a skill or a countdown decides what he is worth at 132.5 overall.
Zach Charbonnet scored 183.4 fantasy points in 2025. The volume he earned was worth 157.1. That gap of 26.3 points is the single most important thing to understand before drafting him at 132.5 overall.
Rather than reading a season average, it is worth finding the point the season actually turned. Our shift detector flags in-season changes large enough to clear a statistical threshold, then asks what moved around them.
The largest single move was Week 16: fantasy points went up from 9.2 to 20.8, a 126.7% change, at 3.78 standard deviations. The cause was structural — the play-calling changed. He also missed Weeks 3, 8.
Year over year the engine classifies 2025 as a breakout that leaned on touchdown luck. That is the label to carry into the projection, because it separates a player who lost snaps from one who kept them and converted worse.
He finished 10.79 points per game on 24 touches — down 0.2% from his 2024 rate with SEA. Every part of that is real and none of it is in dispute.
What is worth separating is how much of it he earned. Expected points strip out the finishing and ask a narrower question: given the targets he drew, where they came from on the field, and how far downfield they travelled, what was that usage worth? For 2025 the answer was 157.1 points — 9.2 per game. He scored 26.3 more than that, a 16.7% overshoot.
The expected line underneath the season was 18.8 catches for 142 yards and 0.9 touchdowns, and he cleared it.
1 of his 16 games produced 25 or more points: Week 17 against CAR (26.2). Strip it and the remaining 15 games average 10.3.
Spike weeks win fantasy games and a player who produces them is more valuable than one who never does — he is a ceiling play with real weeks off. 7 games came in under 10 points, including Week 2 against PIT (1) and Week 6 against JAX (4.7).
The three largest overshoots — Week 17 (+11.7), Week 7 (+8.8), Week 12 (+5.7) — are the same games. The spikes were not extra volume. They were finishing.
1 of his 3 seasons ran hot: 2025 (+16.7%). 1 came in below what the usage justified: 2023 (-14.6%). Across all 3 he has scored 23.8 points more than his usage was worth.
The reflexive read is regression. Finishing above expectation is unstable, and a player who does it repeatedly is usually one whose luck has not run out yet.
But an expected-points model has a specific blind spot, and it is worth naming: it converts usage at league-average rates. A target twenty yards downfield is worth what the average receiver does with a target twenty yards downfield. If a player is reliably better than average at winning a particular kind of target, he will beat the model every single year, and calling that luck is just mislabelling a skill.
So the question is not whether he beat the number. It is whether there is a mechanism.
Across 116 targets and four seasons, he has been a fundamentally different receiver depending on what the defence played. Against man he has caught 73.5% for 5.15 yards per target and -0.184 expected points added per target. Against zone: 85.2%, 5.68 yards, -0.07 EPA.
That is a gap of -0.114 EPA per target on a sample of 34 man targets against 81 zone. The catch rate goes the other way — he catches more against zone — which is exactly what you would expect from a receiver whose value is in winning contested downfield throws rather than in finding soft spots underneath.
The shell detail sharpens it. Cover 3 is the look he has faced most: 30 targets, 5.6 yards per target, -0.101 EPA. His best is Cover 1, single-high man at -0.015 on 23 targets.
The weakness is specific. Against Cover 2 he has caught 82.8% for 5.59 yards a target and -0.102 EPA across 29 looks — a gap of 0.1 expected points a target between his best coverage and his worst.
This does not prove the overshoot repeats. It does mean the pattern has a stated cause rather than being a coin that keeps landing heads.
Across 119 graded prop lines, he has gone over 48.7% of the time. On rushing yards specifically the number is 38.7% across 31 lines, missing the posted number by an average of 3.6%.
That cuts against him. A book that has him beaten 61% of the time on his most-graded market is not a market being slow — it is a market that has him priced correctly and a player who keeps falling short of it.
Touchdowns are the control. His anytime-TD market implied a 38.6% rate and he converted at 48.4% — a gap of 9.8 points, which is worth noting.
Seattle returns 4 of 6 continuity slots — qb1, wr1, te1, hc — with Sam Darnold at quarterback, Mike Macdonald as head coach and Brian Fleury calling it. The offence projects to 30.43 pass attempts a game at medium confidence.
The pie is stable. His slice is the question. Our share model has him at 5.9% against the 8.6% he ran, with a range of 3.2% to 8.5%.
That number is built from 25 comparable players — same age band, same prior share, same team, same coordinator — not from a depth chart. The closest three went Jeffery Wilson 8.7% to 7.2%, Miles Sanders 8.1% to 9.3%, A.J. Dillon 7.9% to 0%. Two held, one fell hard.
Across 2,022 player-seasons we swept every stat for whether it predicts NEXT year's points, and kept only the ones that replicated in all five. f_timeToLOS (r 0.128), f_snapTrend (r 0.103), f_fantasyForm (r 0.078) carry. week-to-week volatility (r -0.163) and receiving EPA per game (r -0.143) run negative — a player who was hyper-efficient on low volume tends to come back down, so a gaudy per-touch number is a warning rather than a selling point.
So the figures worth weighing for him: a 7.6% target share, 1.8% of the air yards, a WOPR of 0.13, on the field for 48.4% of snaps. He finished 25 at the position — RB3.
Vegas sets an implied total for every team every week, and some offences beat theirs systematically. Over 106 games, SEA has come in +1.16 points against its own implied total, clearing it in 54% of weeks.
That is a real structural tailwind. Every skill player in this offence gets a small, repeatable bonus the market prices late.
One related finding worth carrying: across 1,280 cases we measured what happens after a team's implied total slides, and the correlation is -0.37 — negative, meaning the market over-corrects. A falling team total is more often a buying window than a warning.
Our board has him at 87 points, 5.4 per game across 16 expected games — 8.7 catches, 62 yards, 0.6 touchdowns. That is RB6, 179 overall, and -68 points of value over a replacement starter.
It is a step down from 2025, and the reason is volume rather than efficiency. The projection assumes he keeps doing what he does on slightly fewer looks.
The books do not agree on him. . That 24.1-pick gap between Sleeper and Underdog is the practical thing to act on: in a Underdog-priced room he is available later than his consensus number suggests.
He goes at 132.5 overall on consensus, and the books are far apart — 24.1 picks between cheapest and priciest, which is a real value window. He is latest on underdog and earliest on sleeper: sleeper 125.8, espn 149.9, yahoo 128.1, underdog 161.2, cbs 126.3.
At 132.5 you are paying a WR2 price for a player whose median outcome is a WR2 season with five weeks that win you the game outright and four that lose it. The bust rate of 46% is real and so is the 98% boom rate.
The call: fair value, not a discount. The reason to take him is the ceiling and the betting record. The reason to pass is that you are buying a profile that has beaten its expected output four years running and only needs to stop once.
Ask the Coach about Zach Charbonnet Every number in this piece, plus your league's roster and scoring, in one answer.Expected points are computed from realised usage — targets, air yards and field position — against league-average conversion, not from projections. Prop records cover 119 graded lines. Projections are anchored to consensus with our engine applied as a capped tilt; the raw engine figure is stated where it differs. Nothing here is betting advice.