How our ELWAY forecasts work

Silver Bulletin · collected 2026-09-08 · by Nate Silver commentary
Read the original at Silver Bulletin ↗

Summary

The Silver Bulletin's ELWAY forecasting model has undergone significant updates and refinements for the 2026 season. The key improvements include a revamp of the QBERT component to give quarterbacks more credit for completions, drops, and penalties, such as pass interference calls, which are now treated as completed passes. According to the article, these changes will benefit quarterbacks like Dak Prescott, who was previously penalized by not being credited for DPIs in last year's model. The updates aim to improve ELWAY's performance and accuracy in predicting game scores and player statistics.
Written by the local model on 2026-09-08, using this article's own text rather than the other coverage of the same event (that is the story summary below).

Signals How these are calculated →

Claims extracted
314
claim-shaped sentences
Uncertain
6%
18 of 314 hedged
Leaning
not political
takes no side on a contested political question
Publisher trust
not scored
Commentary is not rated for newsroom trust
Outlets on this story
1
Sports
Narrative spread
1
articles carrying this framing
Analyzed 2026-09-08 · how these are computed

AI analysis (generated at analysis time, not now)

Story summary

The Silver Bulletin has updated its 2026 model, ELWAY, which analyzes NFL teams' performance. The changes aim to refine the model's performance by fixing minor issues and improving its handling of injuries and team ratings. Specifically, 18 out of 314 predictions made this year were deemed uncertain. According to Nate Silver, the model's creator, these updates should lead to a significant improvement in ELWAY's accuracy. One notable change is the addition of more detailed injury handling, which will now take into account factors such as the position and severity of an injury. The team also revamped QBERT, its quarterback evaluation tool, to give quarterbacks credit for completions on dropped passes and estimate the additional yards and touchdowns that would have resulted from a caught pass. These updates were made possible by AI tools that helped identify inefficiencies and bugs in the code.

Written for “ELWAY Forecasting Model” on 2026-09-08, grounded in this article and the 0 other(s) covering the same event.
Why this leaning score
This article does not take a side on a contested political question, so it has no leaning score. That is an answer rather than a gap: a match report or a rescue can be warmly or critically written without being left or right, and scoring it anyway is how approval of a subject gets recorded as a political position.
No political leaning scored for article 6975 · logged 2026-09-08

Story

📰 ELWAY Forecasting Model
Sports · 1 article(s) covering the same event. This is the one the site leads with.

How this is being covered How these are calculated →

Article leaning vs. publisher reliability
Source leaning vs. consistency

Compared with similar articles

This article reads unscored and hedges 6% of its claims. Each row says how that neighbour differs.
New York Post
⚖️ leaning not scored 🔴 11% hedged 1 of 9 📰 publisher trust 58
“Article A discusses NFL predictions for AJ Brown, while Article B explains how a forecasting model called ELWAY works, with no mention of AJ Brown or the Patriots”
QBERT 2026 NFL quarterback ratings different event · 80%
Silver Bulletin
⚖️ leaning not scored 🔴 1% hedged 1 of 74
“Article A describes a static landing page for QBERT, while Article B mentions an update to ELWAY and references QBERT as a component of it.”

Publisher

Silver Bulletin · 22 article(s) · 0 correction(s) detected
No corrections detected for this publisher. That may mean careful reporting, or simply that nothing has been checked.

Who wrote this

Nate Silver
18 article(s) here · 1 carrying a prediction
🔮 Not only does QBERT now give a QB credit for a completion on a drop, but we also estimate the additional yards and touchdowns (and even the avoided interceptions2) that would have resulted from the caught pass.
2026-09-08 · assertive framing · How our ELWAY forecasts work
🔮 🏈 The latest on ELWAY September 7, 2026 Our ELWAY forecasts have relaunched for the 2026 NFL season!
2026-09-08 · assertive framing · 2026 ELWAY NFL projections
🔮 The charts and tables will be updated regularly, and some of the text will change, too.
2026-09-05 · assertive framing · QBERT 2026 NFL quarterback ratings
🔮 Next week, we’ll launch our midterms model, with complete forecasts of the 435 U.S. House races, 35 Senate races, and 36 gubernatorial races on the ballot this November, as well as the overall likelihood of each party controlling each chamber and all kinds of other details.1 The model performed quite well in 2018 after the code was basically rewritten from scratch, and again in 2022 after some further tweaks mostly to reflect increasing political polarization.
2026-09-05 · assertive framing · What Trump's latest slump means for the midterms
🔮 The margin is narrow, but when there aren’t a lot of votes left, will be hard for Stevens to make up.
2026-09-05 · assertive framing · What to make of Michigan
🔮 In the Silver Bulletin/FiveThirtyEight tradition, we’ve always given names to our sports models (PELE, ELWAY) — but never to our election forecasts.
2026-09-04 · assertive framing · How FLIPR forecasts the midterm elections
🔮 Our midterms model, which we’re now calling FLIPR 🐬 — Forecast with Leading Indicators, Polls and (Expert) Ratings — launched today!
🔮 Not only am I profoundly interested in increasingly less abstract questions about how AI progress might disrupt society, but I’m also becoming much more of a power user because AI programming tools have reached the point where they’re now quite helpful with programming our various politics and sports models.
2026-09-04 · assertive framing · Why does everyone hate data centers?
🔮 But as responsible forecasters, we have to say: that’s usually not how congressional elections work, and that narrative is outdated in more than one way.
2026-09-04 · assertive framing · Beware big swings in midterm forecasts
🔮 The podcast, Still Counting, will be produced by Crooked Media.
More on this subject from Nate Silver
2026 ELWAY NFL projections
2026-09-08 · Silver Bulletin · 83% similar
QBERT 2026 NFL quarterback ratings
2026-09-05 · Silver Bulletin · 67% similar
All 18 articles by Nate Silver →

Topics

ELWAY NFL QBERT Seattle Seahawks Silver Bulletin

Subjects

ELWAY ORG · 8× QBERT ORG · 6× Dak Prescott PERSON · 1× Drake Maye PERSON · 1× Jalen Hurts PERSON · 1× Josh Allen PERSON · 1× Lamar Jackson PERSON · 1× NFL ORG · 1× Seattle Seahawks ORG · 1× Silver Bulletin ORG · 1×

Narrative

Most of these are on the order of minor nuisances — the toilet in the upstairs bathroom doesn’t always flush — but collectively, we expect this cleanup to considerably improve ELWAY’s performance.1 Apart from this debugging, most of our work this off-season was concentrated in three areas: A refit of QBERT; Switching from efficiency per play to efficiency per drive as ELWAY’s main layer for assessing team quality; And much more detailed handling of injuries.
framing: assertive · carried by 1 article(s) · first seen 2026-09-08
🔮 Not only does QBERT now give a QB credit for a completion on a drop, but we also estimate the additional yards and touchdowns (and even the avoided interceptions2) that would have resulted from the caught pass.
2026-09-08 · Silver Bulletin
How our ELWAY forecasts work · assertive framing

Claims (314 extracted, 18 hedged)

2026 changes to ELWAY and QBERT ELWAY was an ambitious model when we launched it last year. asserted
we → launch → it
It already incorporated a number of layers: rolling team ratings dating back to the dawn of the NFL, gradually adding in advanced stats as they became available; quarterbacks in the form of QBERT; off-season roster movement; and a wide array of adjustments for factors such as injuries and home-field advantage. asserted
they → incorporate → injuries
But ELWAY was a bit like a fancy new house that had never really been lived in. asserted
that → live → house
It got some of the big headlines right — including becoming an early fan of the Super Bowl Champion Seattle Seahawks. asserted
some → get → Champion
But because ELWAY had less tenure than other Silver Bulletin models, some parts felt less polished or slightly unfinished. asserted
parts → have → models
So we put a lot of work into ELWAY and QBERT this year. asserted
we → put → ELWAY
Most of this doesn’t change its architectural blueprint, but ELWAY’s original intentions are now implemented more effectively, we hope. asserted
we → change → blueprint
AI tools were quite helpful for performing a thorough audit of its code and uncovering a few inefficiencies and even some bugs. asserted
tools → perform → inefficiencies
Most of these are on the order of minor nuisances — the toilet in the upstairs bathroom doesn’t always flush — but collectively, we expect this cleanup to considerably improve ELWAY’s performance.1 Apart from this debugging, most of our work this off-season was concentrated in three areas: A refit of QBERT; Switching from efficiency per play to efficiency per drive as ELWAY’s main layer for assessing team quality; And much more detailed handling of injuries. asserted
most → flush → injuries
If this text sounds familiar, most of it is duplicated from the QBERT landing page as of when we launched it this season. asserted
we → sound → it
We are quite confident that drops should be attributed to the WR, not the quarterback. asserted
drops → attribute → WR
Not only does QBERT now give a QB credit for a completion on a drop, but we also estimate the additional yards and touchdowns (and even the avoided interceptions2) that would have resulted from the caught pass. asserted
that → give → pass
QBs who had fewer drops than expected, like Drake Maye last year, suffer a slight penalty. asserted
who → have → penalty
Yards gained on pass interference calls deserve credit. asserted
Yards → gain → credit
Last year’s model ignored penalties. asserted
model → ignore → penalties
But having collected penalty data, we now simply treat defensive pass interference (DPI) calls as completed passes, giving a QB credit for the completion, the first down, and the air yards associated with the “catch”. asserted
we → collect → catch
This benefits QBs like Dak Prescott, who had 268 yards essentially erased from his stat line last year on DPIs, by far the highest in the league. asserted
yards → benefit → league
Furthermore, intentional grounding calls are now treated as incompletions worth minus-10 yards. asserted
calls → treat → incompletions
Other QB-related penalties are still ignored because we’ve found they don’t provide much signal. asserted
they → relate → signal
QBERT likes rushing QBs more than the consensus, but not all QB rushes are created equal. asserted
rushes → like → consensus
We now give far less credit to TDs from sneak plays versus other rushing TDs and also apply a penalty term to sneaks to ensure that they don’t have positive expected value relative to other QB plays. asserted
they → give → plays
Over the past three years, two QBs have benefited disproportionately from sneaks: Jalen Hurts (30 sneak TDs) and Josh Allen (21). asserted
QBs → benefit → sneaks
Isolating sneaks does result in slightly more credit to non-sneak rushing TDs, however. asserted
Isolating → isolate → TDs
Pocket passers were being undervalued. asserted
passers → undervalue → ?
Last year, the coefficients used in QBERT were fitted on data from 2016-2024. asserted
coefficients → use → 2016
We’ve now collected advanced-stat data going back to 2006 and refitted QBERT over a larger sample. asserted
We → collect → sample
This matters because 2016-2024 was a highly favorable era for mobile QBs like Lamar Jackson, Allen and Mahomes, whereas the late 2000s and early ‘10s were more favorable to pocket passers (Brady, Brees, Manning). asserted
2000s → matter → passers
This makes QBERT more robust across eras and also brings it more in line with the conventional wisdom, helping modern pocket passers like Stafford. asserted
QBERT → make → Stafford
Touchdowns now matter less, and the process that produces TDs matters more. asserted
that → matter → TDs
Last year’s version of QBERT was essentially pegged to ESPN QBR. asserted
version → peg → QBR
QBR is a smart system, much better than traditional NFL passer ratings, and still serves as an important scaffold for our system. asserted
QBR → serve → system
Our reverse-engineering of QBR suggests that it places an extremely high value on touchdowns, equivalent to something like 45 yards per passing TD. uncertain
it → suggest → TD
Other systems like ANY/A assign less than half as much credit to TDs. asserted
systems → assign → TDs
While there is some persistent skill in red zone play, TDs are both noisy and opportunity-dependent, and TD rates don’t “travel” all that well when a QB changes teams. asserted
QB → be → teams
Long story short: the reward given to TDs has been reduced by 50 percent, with credit instead flowing into categories like first downs that better predict touchdowns in the long run. asserted
that → give → run
The 2025 version of QBERT accounted for the game script, giving more credit to quarterbacks who establish early leads. asserted
who → account → leads
The rationale was that offenses are less efficient with a lead late in the game because it’s rational for them to play conservatively and run out the clock. asserted
them → ’ → clock
However, upon review, essentially all of the difference stems from replacing quarterback plays with handoffs to running backs. asserted
all → stem → backs
Thus, we’ve removed the game-script variables. asserted
we → remove → variables
Mostly, they were giving QBs extra credit for being on good teams, undermining QBERT’s goal of separating QB performance from team performance. asserted
they → give → performance
…and 274 more, not listed.
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