What the expected-points record, the coverage data and the market say he is worth at 152.1 overall.
Juwan Johnson scored 179.9 fantasy points in 2025. The volume he earned was worth 185.2. That gap of 5.3 points is the single most important thing to understand before drafting him at 152.1 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 5: snap share went down from 93.8 to 69.2, a 26.2% change, at 6.96 standard deviations. The cause was structural — the offense collapsed. He also missed Week 11.
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 10.58 points per game on 102 targets — a 29.2% jump on his 2024 rate with NO. 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 traveled, what was that usage worth? For 2025 the answer was 185.2 points — 10.9 per game. He scored 5.3 FEWER than that, a 2.9% shortfall.
The expected line underneath the season was 73.6 catches for 765 yards and 5.9 touchdowns — and he came in under it.
Not one of his 17 games cleared 25 points. His best was 19.2 in Week 10. He wins with volume rather than with weeks that swing a matchup.
A steady floor has its own value in a lineup that needs one. 7 games came in under 10 points, including Week 4 against BUF (5.8) and Week 5 against NYG (3.7).
The three largest overshoots — Week 10 (+11.9), Week 17 (+6.2), Week 9 (+4.8) — are the same games. The spikes were not extra volume. They were finishing.
1 of his 6 seasons ran hot: 2022 (+18.5%). 1 came in below what the usage justified: 2020 (-55.4%). Across all 6 he has scored 22.2 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 294 targets and four seasons, he has been a fundamentally different receiver depending on what the defense played. Against man he has caught 59.8% for 6.43 yards per target and 0.058 expected points added per target. Against zone: 75.9%, 8.69 yards, 0.306 EPA.
That is a gap of -0.248 EPA per target on a sample of 107 man targets against 187 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 1, single-high man is the look he has faced most: 78 targets, 7.19 yards per target, 0.146 EPA. His best is Cover 6 at 0.464 on 22 targets.
The weakness is specific. Against 2-Man he has caught 42.9% for 3.62 yards a target and -0.489 EPA across 21 looks — a gap of 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 58 graded prop lines, he has gone over 63.8% of the time. On receiving yards specifically the number is 62.1% across 29 lines, beating the posted number by an average of 41.5%.
A projection model can be wrong about conversion. A book adjusting weekly, with money on the other side, being wrong 62% of the time on the same market is a harder thing to explain away.
Touchdowns are the control. His anytime-TD market implied a 21.8% rate and he converted at 20.0% — a gap of -1.8 points, which is noise.
New Orleans returns 5 of 6 continuity slots — qb1, wr1, te1, hc, oc — with Tyler Shough at quarterback, Kellen Moore as head coach and Doug Nussmeier calling it. The offense projects to 34.1 pass attempts a game at high confidence.
The pie is stable. His slice is the question. Our share model has him at 12.2% against the 15.8% he ran, with a range of 11% to 14.1%. The biggest competing claim on that pie is Chris Olave at 22.1%, 9.9 points ahead of him.
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 T.J. Hockenson 17.8% to 20.5%, Tyler Higbee 15.3% to 21.6%, Evan Engram 17.2% to 23.5%. All of them held their share.
Across 4,488 player-seasons we swept every stat for whether it predicts NEXT year's points, and kept only the ones that replicated in all five. target share (r 0.247), WOPR (r 0.218), air-yards share (r 0.142) carry. receiving EPA per game (r -0.127) and yards per target (r -0.114) and week-to-week volatility (r -0.075) 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 17.7% target share, 15.5% of the air yards, a WOPR of 0.37, a 75% snap share. He averaged 1.53 yards of separation, with -1.33 YAC over expected.
Vegas sets an implied total for every team every week, and some offenses beat theirs systematically. Over 103 games, NO has come in +0.2 points against its own implied total, clearing it in 50% of weeks.
That is close to neutral — the offense performs about where the market expects, so there is no environment bonus or penalty to apply to him either way.
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 123.4 points, 8.1 per game across 15.2 expected games — 50.6 catches, 554 yards, 2.9 touchdowns. That is TE4, 141 overall, and -31 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 34.2-pick gap between Yahoo and Sleeper is the practical thing to act on: in a Sleeper-priced room he is available later than his consensus number suggests.
He goes at 152.1 overall on consensus, and the books are far apart — 34.2 picks between cheapest and priciest, which is a real value window. He is latest on sleeper and earliest on yahoo: sleeper 164.7, espn 164.2, yahoo 130.5, underdog 153.6, cbs 148.8.
He goes at 152.1 and our board has him 141. That is 11.1 picks of discount on a TE4 projection — you are getting the TE4 outcome at a price the room has set below it.
The case for: a 53% boom rate.
The case against: a floor of 7.4 points per game, which is the outcome you are underwriting if the role moves.
The call: take him at his ADP and do not talk yourself out of it.
Ask the Coach about Juwan Johnson Every number in this piece, plus your league's roster and scoring, in one answer.Expected points are computed from realized usage — targets, air yards and field position — against league-average conversion, not from projections. Prop records cover 58 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.