NFL WEEK 1

Model vs. Kalshi on all 16 openers

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Jonathan Taylor

RB · Indianapolis Colts · bye week 13

Our 2026 half-PPR projection for Jonathan Taylor, the consensus draft cost, and where the two disagree. Same numbers our model serves to AI assistants — free, no key.

Projected points

285

16.8 per game

Consensus ADP

6

round 1

RB rank

RB3

model has him RB2

2026 range

10th pct 143·median 282·90th pct 487

Measured, not simulated. Our RB projections have landed inside this band 81% of the time against a 80% target, on the 2024-25 holdout. The median sits below the projection because most players lose time — the projection is an expected total, not the typical outcome.

Week 1 distribution

Rec Yds

10th 0·median 15·90th 51

Receptions

10th 0·median 2·90th 5

Rush Yds

10th 22·median 68·90th 195

The spread comes from how far actual results have landed from projections of this size, fitted on four seasons — not a simulation. Season and week figures are different vintages: the range above is preseason, this block is Week 1.

Our board and the consensus market agree on him almost exactly at RB.

Prop market — every Kalshi strike

Full market board →
Every Kalshi player-prop strike for Jonathan Taylor with a two-sided book: the Kalshi mid, the sportsbook consensus at that strike, the gap in cents, and the cheapest venue per side. A gap is a price difference, not a recommendation.
ContractKalshiConsensusGapBest priceTrade
100+ rush ydsIND v BAL29.0¢no booksover · Kalshi 33.5¢Kalshi →
110+ rush ydsIND v BAL21.5¢no booksKalshi onlyKalshi →
130+ rush ydsIND v BAL11.5¢no booksKalshi onlyKalshi →
160+ rush ydsIND v BAL5.5¢no booksKalshi onlyKalshi →

Gap is the Kalshi mid minus the sportsbook consensus at that strike, in cents, read across two clocks — Kalshi as of Sep 7, 1:00 AM ET, books as of Sep 5, 1:15 AM ET. A gap is a price difference, not a call.

Colts 2026 schedule

Team hub →

Every game carries our model line against the live Kalshi contract price.

How this projection is built

Season projections come from our own usage model — target and carry share, efficiency and games played — then the published rank blends that model with consensus ADP at a weight fitted per position. The raw model loses to consensus ADP at every position, so the board leads with the blend and the disagreement is the content, not a claim that we are right.

The engine behind the game numbers grades at 59.6% straight up across 3,266 games (2013–2024). Those figures grade DAEPA, the underlying play-by-play model. Every published call is graded here.

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Projections as of 2026-09-06; ADP source composite. Fantasy projections are estimates, not predictions — trade and draft responsibly.