Today · Oct 3 · 18 events Games under way Settled· Sep 30

Regular season · week 4 · Sunday, Oct 4, 1:00 PM ET

New York JetsatChicago BearsEXPERIMENTAL

Soldier Field

New York JetsChicago BearsSaved on this device

67°F · 10 mph wind from the WNW · 0% chance of rain · mostly sunny — not used by the model; no weather term enters the numbers below.

Simulation story

5 chapters · read from the published artifact

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› Loading the matchup model› Reading the outcome distribution from 10,000 simulated games› Preparing the score scenariosPress Play to step through what the model expects, chapter by chapter, or read the report below.

NYJ @ CHI

New York Jets at Chicago Bears at Soldier Field.

Simulation

What our model expects

10,000 simulated games · model nfl-regular-season-public-v1

Projected score

NYJ 19 — 28 CHI

the middle of our simulated outcomes, not a call on the exact final

Win chance

NYJ 20.6% · CHI 77.2%

how often each side won in 10,000 simulations · ties 2.2%

Total points (both teams)

8 in 10 simulations landed between 30 and 64

CHI winning margin

a minus means NYJ wins by that much · 8 in 10 between -9 and 25

Live game state

Live beta

The left side is what the live source reports right now. The right side is the GameTime forecast made before kickoff — it is frozen and does not change while the game is played.

Live now

Checking the live feed…

Pregame GameTime · frozen

NYJ: 19 (21% pregame win chance)
CHI: 28 (77% pregame win chance)

Forecast frozen at Oct 3, 2:37 PM ET. It does not change during the game.

Model details

From the margin-of-victory Elo win head, published exactly as evaluated on held-out 2006–2021 — no shrink toward 50% is applied, and no claim to out-predict the sportsbook market is made. Generated 2026-10-03T18:37:22Z under model nfl-regular-season-public-v1 and frozen pre-kickoff; every forecast is settled against the official result.

Projected scorecard

expected statistical summaries · not one simulated game

NYJ 19 — 28 CHIwin chance NYJ 20.6% · CHI 77.2%total 47 (30–64)margin +9

NYJ

Likely TD scorers

Garrett Wilson 39.0%

Braelon Allen 22.7%

Kenyon Sadiq 21.4% · questionable

Passing

Geno Smith 229 pass yds (129–371)

Rushing leaders

Braelon Allen 13 rush yds (1–54)

Geno Smith 7 rush yds (0–39)

Receiving leaders

Garrett Wilson 5 rec · 54 yds

Kenyon Sadiq 2 rec · 25 yds · questionable

Isaiah Williams 2 rec · 14 yds

CHI

Likely TD scorers

D'Andre Swift 57.8%

Kyle Monangai 33.9%

Luther Burden III 31.2%

Passing

Case Keenum 230 pass yds (129–372)

Rushing leaders

D'Andre Swift 55 rush yds (15–138)

Kyle Monangai 31 rush yds (5–97)

Receiving leaders

Luther Burden III 4 rec · 42 yds

Kalif Raymond 4 rec · 46 yds

D'Andre Swift 2 rec · 14 yds

pass interceptions · First/last/2+ touchdown — withheld, with the exact bar each failed

pass interceptions: RESEARCH_ONLY
First/last/2+ touchdown: DISABLED — no ordering model and no calibration receipt of their own; never derived from anytime probabilities

Model detail — who this forecast leaves out (6)

Breece Hall NYJ — Not playing: Listed Out.
Adonai Mitchell NYJ — Not playing: Listed Out.
Mason Taylor NYJ — Not playing: Listed Out.
Will Levis NYJ — Role not yet observed: no game for NYJ yet this season — role at NYJ not yet observed.Historical prior, not used in these numbers: 14 games for TEN, 13.3 rush yds · 160.3 pass yds per game.
Kyle Monangai CHI — No receiving projection: the receiving model's usage pool does not include his 2026 role here yet.
Caleb Williams CHI — Not playing: Listed Out.

Range

How wide the outcomes are

the 10th to 90th percentile of each team's simulated score

Team	Low (10th)	Projected	High (90th)
New York Jets	8	19	32
Chicago Bears	16	28	40

Exact score

The likeliest final scores

from an event-based simulation of touchdowns and field goals, solved onto the median margin and total above

Score (NYJ – CHI)	Chance
17–20	0.71%
17–27	0.63%
24–27	0.60%
20–23	0.55%
10–27	0.54%
20–17	0.53%

No single scoreline is likely — these are the most common of hundreds. The projected score above is derived from the medians and answers a different question: the middle of the distribution, not its most common point.

Key numbers

How often it lands on 3, 7, 10 or 14

football's margins pile up on those four — this is the one thing a normal-draw model cannot show you

Margin	This game	Last 3 regular seasons
Decided by exactly 3	8.6%	14.2%
Decided by exactly 7	6.3%	8.3%
Decided by exactly 10	5.2%	4.2%
Decided by exactly 14	4.8%	4.4%
Any of the four	24.9%	31.1%

The right-hand column is what actually happened across 816 regular-season games (2023, 2024, 2025) — the same finals this engine was fitted to. It gets the shape right, with 3 the most common margin by a distance, and it is not calibrated to the number: it puts less weight on 3 and more on 10 than those seasons did.

NYJ touchdowns

2.2

CHI touchdowns

3.0

NYJ field goals

1.5

CHI field goals

2.0

Tied after regulation

3.1%

Comparison

Us versus the sportsbooks

two independent reads, shown side by side

Our win chance

77.2%

CHI to win

Sportsbook win chance

62.9%

CHI to win, read from 8 sportsbooks' odds with their built-in margin removed

Difference

+14.3 pp

ours minus the sportsbooks', in percentage points — not a recommendation

Total points: ours vs sportsbooks

47 vs 43

our projected total against the sportsbooks' over/under line

The sportsbook numbers are the books' own, shown for context. A difference is a difference — this model is not validated to out-predict the sportsbook market.

Prices captured 2026-10-03T18:08:15Z — before kickoff.

Player projections · 16 modelled

The player board

Every modelled player, with his availability. Players listed out carry no volume projection.

D'Andre SwiftMatchupCHI vs NYJStartSun 1:00 PM ETMarketDraftKingsYes -120Captured Sat 12:52 PM ETModelGameTimePicks57.8%
Garrett WilsonMatchupNYJ vs CHIStartSun 1:00 PM ETMarketDraftKingsYes +150Captured Sat 12:52 PM ETModelGameTimePicks39.0%
Kyle MonangaiMatchupCHI vs NYJStartSun 1:00 PM ETMarketDraftKingsYes +190Captured Sat 12:52 PM ETModelGameTimePicks33.9%
Luther Burden IIIMatchupCHI vs NYJStartSun 1:00 PM ETMarketDraftKingsYes +230Captured Sat 12:52 PM ETModelGameTimePicks31.2%
Kalif RaymondMatchupCHI vs NYJStartSun 1:00 PM ETMarketDraftKingsYes +330Captured Sat 12:52 PM ETModelGameTimePicks30.9%
Braelon AllenMatchupNYJ vs CHIStartSun 1:00 PM ETMarketDraftKingsYes +115Captured Sat 12:52 PM ETModelGameTimePicks22.7%
Kenyon SadiqMatchupNYJ vs CHIStartSun 1:00 PM ETquestionableMarketDraftKingsYes +225Captured Sat 12:52 PM ETModelGameTimePicks21.4%
Rome OdunzeMatchupCHI vs NYJStartSun 1:00 PM ETMarketDraftKingsYes +320Captured Sat 12:52 PM ETModelGameTimePicks19.9%
Colston LovelandMatchupCHI vs NYJStartSun 1:00 PM ETMarketDraftKingsYes +240Captured Sat 12:52 PM ETModelGameTimePicks18.3%
Case KeenumMatchupCHI vs NYJStartSun 1:00 PM ETMarketNot offeredModelGameTimePicks15.8%
Isaiah WilliamsMatchupNYJ vs CHIStartSun 1:00 PM ETMarketDraftKingsYes +425Captured Sat 12:52 PM ETModelGameTimePicks13.0%
Jeremy RuckertMatchupNYJ vs CHIStartSun 1:00 PM ETMarketDraftKingsYes +750Captured Sat 12:52 PM ETModelGameTimePicks11.9%
Cole KmetMatchupCHI vs NYJStartSun 1:00 PM ETMarketDraftKingsYes +550Captured Sat 12:52 PM ETModelGameTimePicks11.0%
Geno SmithMatchupNYJ vs CHIStartSun 1:00 PM ETMarketDraftKingsYes +900Captured Sat 12:52 PM ETModelGameTimePicks9.9%
Brittain BrownMatchupCHI vs NYJStartSun 1:00 PM ETMarketNot offeredModelGameTimePicks9.4%
Kene NwangwuMatchupNYJ vs CHIStartSun 1:00 PM ETMarketDraftKingsYes +2200Captured Sat 12:52 PM ETModelGameTimePicks8.3%

Model detail — who this forecast leaves out (6)

Breece Hall NYJ — Not playing: Listed Out.
Adonai Mitchell NYJ — Not playing: Listed Out.
Mason Taylor NYJ — Not playing: Listed Out.
Will Levis NYJ — Role not yet observed: no game for NYJ yet this season — role at NYJ not yet observed.Historical prior, not used in these numbers: 14 games for TEN, 13.3 rush yds · 160.3 pass yds per game.
Kyle Monangai CHI — No receiving projection: the receiving model's usage pool does not include his 2026 role here yet.
Caleb Williams CHI — Not playing: Listed Out.

Families not shown, and the exact bar each failed (2)

pass interceptions: RESEARCH_ONLY
First/last/2+ touchdown: DISABLED — no ordering model and no calibration receipt of their own; never derived from anytime probabilities

Scoring outlooktop 6 of 16 by TD chance · full list in the board’s TD tab

57.8% D'Andre Swift · CHI
39.0% Garrett Wilson · NYJ
33.9% Kyle Monangai · CHI
31.2% Luther Burden III · CHI
30.9% Kalif Raymond · CHI
22.7% Braelon Allen · NYJ

Anytime-scorer probability means scoring a touchdown — never throwing one. Void if the player does not play; questionable players carry their state above.

Reading key

What these numbers mean

Projected score: The middle outcome across every simulated game — not a prediction of the exact final.
Win chance: How often each side won across the simulations, after the calibration described above.
80% range: Eight in ten simulated games landed inside this band. Real games land outside it too.
pp (percentage points): The plain difference between two percentages. A gap is a difference, not an advantage.
Experimental: Published while its out-of-sample record is still accumulating. Every forecast is frozen before kickoff and graded against the official result.

Provenance

Where this came from

model: nfl-regular-season-public-v1 v2
simulations: 10,000
input hash: 636994e24bc849d0
generated: 2026-10-03T18:37:22Z
kickoff: 2026-10-04T17:00Z
state: UPCOMING

Player-family model provenance (4 published)

Rushing yards: Share-level model: cleared every bar when re-tested on 2014–2021 (14,502 player-games) — a second look at seasons examined once before, not a blind test. Each week's forecast is frozen before the first kickoff and graded; its blind 2026 record is still accumulating (216 graded player-games so far).
Receiving yards: props-v1 evaluation: n=3575, all promotion bars pass
Receptions: props-v1 evaluation: n=3575, all promotion bars pass
Anytime touchdown: Opportunity touchdown model: cleared every bar on a blind test of 2014–2021 (35,128 player-games never used to build it). Probabilities condition on playing — a player who does not play settles void. Each week's forecast is frozen before the first kickoff and graded; its blind 2026 record is still accumulating (524 graded player-games so far).

Our win chances come from a team rating that weights how decisively teams win. Tested on 4,281 past games it had never seen (2006–2021), it scored 0.629 on log loss (lower is better) — better than our previous rating's 0.642 and a coin flip's 0.693, but short of the sportsbooks' own odds at 0.610. It has NOT been shown to beat the sportsbook market. Where our win and margin ratings disagree on the favourite, the previous rating is used for that game. The 2026 season evaluation still runs under bars frozen in August, so every forecast stays experimental. These ratings are built from results, not from who is playing: they do not know that a starting quarterback has been ruled out. Our player projections do remove players who cannot play; the team win chance beside them does not. We tested whether adding that would help, using perfect hindsight about whether each team's main quarterback actually played — on 855 games from 2023 to 2025 it improved the win rating on average but was WORSE in one of the three seasons, so it did not clear the bar we hold these ratings to and we left the rating alone.

Educational and paper-only — not betting advice.