He has beaten his expected points in 2 of 5 seasons. Whether that is a skill or a countdown decides what he is worth at 147.2 overall.
Pat Freiermuth scored 116.4 fantasy points in 2025. The volume he earned was worth 103.5. That gap of 12.9 points is the single most important thing to understand before drafting him at 147.2 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 15: targets went up from 3.2 to 4.8, a 49.3% change, at 3.19 standard deviations. The cause was structural — the offence surged. He also missed Weeks 4, 5, 13.
Year over year the engine classifies 2025 as a decline that came from the offence, not the player. 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 7.28 points per game on 57 targets — down 24.2% from his 2024 rate with PIT. 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 103.5 points — 6.5 per game. He scored 12.9 more than that, a 12.5% overshoot.
The expected line underneath the season was 41.1 catches for 427 yards and 3.3 touchdowns, and he cleared it.
The expected line was 41.1 catches for 427 yards and 3.3 touchdowns. He finished with 42, 504 and 4.
60% of the entire gain came from receiving yards alone. He hit 102% of his expected catches and 121% of his expected touchdowns — and 118% of his expected receiving yards.
1 of his 15 games produced 25 or more points: Week 7 against CIN (28.1). Strip it and the remaining 14 games average 6.1.
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. 12 games came in under 10 points, including Week 1 against NYJ (5.8) and Week 2 against SEA (6.1).
The three largest overshoots — Week 7 (+17.2), Week 12 (+5.5), Week 9 (+4.4) — are the same games. The spikes were not extra volume. They were finishing.
2 of his 5 seasons ran hot: 2024 (+19.1%), 2025 (+12.5%). 1 came in below what the usage justified: 2022 (-13.6%). Across all 5 he has scored 23.2 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 293 targets and four seasons, he has been a fundamentally different receiver depending on what the defence played. Against man he has caught 67% for 7.08 yards per target and 0.191 expected points added per target. Against zone: 74.1%, 8.2 yards, 0.277 EPA.
That is a gap of -0.086 EPA per target on a sample of 100 man targets against 193 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: 70 targets, 6.8 yards per target, 0.236 EPA. His best is Cover 4 quarters at 0.419 on 44 targets.
The weakness is specific. Against Cover 6 he has caught 61.9% for 6.29 yards a target and -0.168 EPA across 21 looks — a gap of 0.6 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 55.2% of the time. On receptions specifically the number is 62.1% across 29 lines, beating the posted number by an average of 29.7%.
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 22.8% rate and he converted at 34.5% — a gap of 11.6 points, which is worth noting.
Pittsburgh returns 4 of 6 continuity slots — qb1, wr1, rb1, te1 — with Aaron Rodgers at quarterback, Mike McCarthy as head coach and Brian Angelichio calling it. The offence projects to 32.96 pass attempts a game at medium confidence.
The pie is stable. His slice is the question. Our share model has him at 13.1% against the 13.7% he ran, with a range of 10.5% to 15.5%.
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 Tyler Higbee 14.5% to 15.7%, David Njoku 15.2% to 21.6%, Cole Kmet 15.9% to 9.1%. Two held, one fell hard.
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 11.2% target share, 13.2% of the air yards, a WOPR of 0.26, on the field for 52.5% of snaps. He averaged 2.04 yards of separation against 3.91 yards of cushion, and gained 0.77 yards after the catch above expectation. He finished 25 at the position — TE3.
Vegas sets an implied total for every team every week, and some offences beat theirs systematically. Over 106 games, PIT has come in +0.19 points against its own implied total, clearing it in 49% of weeks.
That is close to neutral — the offence 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 102.7 points, 6.8 per game across 15.2 expected games — 41.1 catches, 454 yards, 2.7 touchdowns. That is TE5, 172 overall, and -52 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. Pat Freiermuth is a board split: Yahoo takes him ~126, Underdog lets him slide to ~193 (43.4-pick gap). That 43.4-pick gap between Yahoo 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 147.2 overall on consensus, and the books are far apart — 43.4 picks between cheapest and priciest, which is a real value window. He is latest on underdog and earliest on yahoo: espn 168.9, yahoo 125.5, underdog 193.3.
At 147.2 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 29% is real and so is the 53% 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 Pat Freiermuth 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 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.