The volume held. The finishing did not. Whether 2025 was the player breaking or the situation breaking decides what he is worth at 107 overall.
Kyle Monangai scored 163.8 fantasy points in 2025. The volume he earned was worth 178.4 — he finished 14.6 points BELOW what his own usage justified. That is a different problem from losing the job, and it is the single most important thing to understand before drafting him at 107 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 6: fantasy points went up from 2.9 to 10.4, at 4.14 standard deviations. The cause was structural — the offense around him got sharply better. He also missed Week 5.
He finished 8.62 points per game on 227 touches, his first full season. 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 carries he took, where on the field they started, and the targets he drew out of the backfield, what was that usage worth? For 2025 the answer was 178.4 points — 9.4 per game. He scored 14.6 FEWER than that, an 8.2% shortfall.
The expected line underneath the season was 829 rushing yards and 6.1 rushing touchdowns, plus 28.9 catches for 218 yards and 1.3 receiving touchdowns — and he came in under it.
Against the expected line, he finished 846 rushing yards, 5 rushing touchdowns, 23 catches, 222 receiving yards — against 829, 6.1, 28.9, 218 expected.
45% of the entire shortfall came from rushing touchdowns. He hit 82% of his expected rushing touchdowns, against 102% of his expected rushing yards and 80% of his expected catches and 102% of his expected receiving yards.
That matters because touchdowns are the least repeatable part of a scoring line. Volume and yards reflect a role; touchdowns reflect a role plus a quarterback putting the ball where it can be caught in a nine-yard window. A player who holds his catches and yards while losing five touchdowns has not lost his job — he has lost the coin flips.
That distinction matters more than the raw finish. A player who loses his role posts a low score and a low expected score. Kyle Monangai posted a low score on an expected total of 178.4 — 9.4 points a game of earned opportunity. The targets were still coming. What went wrong happened after the ball was in the air.
Not one of his 17 games cleared 25 points. His best was 22.8 in Week 9. For a player who had cleared it routinely before 2025, that is the clearest single symptom of the year — not a change in what he was asked to do, a change in what came of it.
A steady floor has its own value, but this was not a floor season by choice. 11 games came in under 10 points, including Week 1 against MIN (2.1) and Week 2 against DET (4.6).
The three largest overshoots — Week 7 (+4.4), Week 13 (+3.6), Week 12 (+3.2) — are the same games. The spikes were not extra volume. They were finishing.
Not one of his 1 seasons is flagged as running hot. 1 came in below what the usage justified: 2025 (-8.2%). Across all 1 he has scored 14.6 points fewer than his usage was worth.
The reflexive read on a down year is decline. But the direction of the miss matters: finishing BELOW expectation is the more correctable of the two errors, because the hard part — earning the volume — is the part that held.
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 missed the number. It is whether there is a mechanism.
Across 43 graded prop lines, he has gone over 48.8% of the time. On rushing yards specifically the number is 57.1% across 14 lines, beating the posted number by an average of 42.3%.
That is close enough to a coin flip that the market has him fairly priced on his primary market. There is no edge to claim in either direction.
Touchdowns are the control. His anytime-TD market implied a 30.4% rate and he converted at 33.3% — a gap of 2.9 points, which is noise.
Chicago returns 5 of 6 continuity slots — qb1, wr1, rb1, te1, hc — with Caleb Williams at quarterback, Ben Johnson as head coach and Press Taylor calling it. The offense projects to 33.59 pass attempts a game at medium confidence.
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 Chuba Hubbard 8% to 11.2%, Isiah Pacheco 5.8% to 9.8%, A.J. Dillon 8% to 7%. All of them held their share.
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. time to the line of scrimmage (r 0.128), snap-share trend (r 0.103), recent scoring form (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: 190 carries, 40.4% of his team’s red-zone carries, 40.7% of the goal-line work, a 40.9% snap share. His carries produced -0.021 EPA per play, and he ran a 7.1% target share out of the backfield.
Vegas sets an implied total for every team every week, and some offenses beat theirs systematically. Over 104 games, CHI has come in +0.48 points against its own implied total, clearing it in 52% 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 157.3 points, 9.8 per game across 16 expected games — 777 rushing yards, 5.9 rushing touchdowns, 19.2 catches for 154 yards. That is RB4, 87 overall, and 0 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.
explicitly the case study for "successful low-draft-capital rookie RBs almost never keep the role the following year" — flagged as a real historical pattern the site should treat with real skepticism regardless of how good his rookie tape looked.
That is the current read. It is a change — in 2026-06-05 the position was LIKE: Cheap round-8 Bears exposure with a possible Montgomery-light goal-line role; ~11 touches/game as a rookie. Big contingent upside if Swift gets hurt. The tough Bears schedule is a real drag on RB game…
It rests on these draft principles:
The books do not agree on him. Kyle Monangai is a board split: Sleeper takes him ~95, ESPN lets him slide to ~133 (38.8-pick gap). That 38.8-pick gap between Sleeper and ESPN is the practical thing to act on: in a ESPN-priced room he is available later than his consensus number suggests.
He goes at 107 overall on consensus, and the books are far apart — 38.8 picks between cheapest and priciest, which is a real value window. He is latest on espn and earliest on sleeper: sleeper 94.6, espn 133.4, yahoo 97.9, underdog 98.3, cbs 102.2.
He goes at 107 and our board has him 87. That is 20 picks of discount on a RB4 projection — you are getting the RB4 outcome at a price the room has set below it.
The case for: a 91% boom rate.
The case against: a 39% bust rate.
The call: take him at his ADP and do not talk yourself out of it.
Ask the Coach about Kyle Monangai 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 43 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.