# Senate expert-rating research

October 19, 2026. Model/source cutoff October 18. New expert weights: zero.

Final expert ratings improve the historical benchmark; ratings known at the polling cutoff do not yet validate an extra forecast weight.

Cook, Sabato’s Crystal Ball, and Rothenberg/Inside Elections are tested separately, as a consensus, and with candidate fundamentals. Final Wikipedia predictions for prior cycles are the user-authorized main source. The three ratings are correlated judgments that already use polling, rather than three independent new surveys.

The current model’s historical polling cutoff is sixteen days before each election. Final ratings often appear closer to Election Day and can contain later information. I therefore also retrieved the latest Wikipedia revision before each historical cutoff, and compared final versus cutoff ratings on identical available race/training cohorts. Missing archived ratings remain missing.

Across all 130 polled races in 2016–2024, the earlier-chosen blend of candidate fundamentals, lean and final expert consensus lowers average margin error from 4.613 to 4.286 points. It improves four of five cycles and worsens 2024. Its whole-election p-value versus the active forecast is 0.250. Compared with the same fundamentals model without experts, error falls from 4.638 to 4.286; that paired p-value is 0.062. These are exploratory results with only five national test elections.

The cutoff-date evidence covers 120 races across the same five cycles. Its earlier-chosen expert/fundamentals blend changes error from 4.441 to 4.427 points, an improvement of only 0.014. On exactly that available cohort, using final ratings instead reaches 4.357. This is too little cutoff-valid improvement for the configured acceptance checks; forecast weights remain unchanged.

As a direct polling correction, fitting all three expert ratings separately improves error beyond identical existing-factor controls by 0.039 points using final ratings, or 0.034 using cutoff ratings. Neither reaches the 0.05-point incremental threshold. The controls themselves are experimental; their gain over the active model is not credited to expert ratings.

Toss-up is zero; tilt, lean, likely and safe/solid are signed ordered levels 1, 2, 3 and 4. Positive means a Democratic/main-opposition advantage and negative means Republican. These are feature levels, not assumed vote margins or win probabilities. Consensus requires at least two raters; individual rater coefficients, index weights and blends are fitted only on earlier election outcomes. A toss-up is distinct from a missing rating.

All final tables for 2006–2024 and the current 2026 table are cached with source hashes. Archived tables supply the separate cutoff test; no supported 2006 cutoff table was extracted, and some older tables omit safe races. Final 2008 has no Sabato column, so it is not invented. The 2026 Inside Elections public export agrees with all 35 Wikipedia ratings. Direct Cook and Sabato pages returned HTTP 403 during this check; their Wikipedia entries are retained as the explicitly authorized source without claiming direct verification.

Source joins distinguish regular and special elections. Arizona 2020 is matched as the McSally/Kelly special election while preserving the upstream model’s flag. California 2022 shares a rating only because its source note explicitly covers both simultaneous ballots. Older transposed tables are parsed by full state names, avoiding a Virginia/West Virginia overlap; source typos and shared explicit consensus rows are documented.

The final-rating benchmark mixes a later information horizon with the frozen polling forecast. Its numerical acceptance checks alone do not authorize a present-cutoff forecast change. The cutoff test is the relevant timing check. These development elections have already been inspected; five cycles, selected historical coverage and overlapping training limit statistical claims. Rating agreement does not automatically reduce uncertainty. No new expert coefficient, probability adjustment or simulation change is activated.

## Learned expert/fundamentals blends

Lower is better; errors are equal-cycle mean absolute D-minus-R margin errors in percentage points. Compare each row with its own polling benchmark.

| Rating information | Races / cycles | Polling error | Learned expert/fundamentals blend error |
|---|---|---|---|
| Final ratings, full historical sample | 130 / 5 | 4.613 | 4.286 |
| Ratings known at cutoff | 120 / 5 | 4.441 | 4.427 |
| Final ratings, same cutoff-covered cohort | 120 / 5 | 4.441 | 4.357 |

## Sources and downloads

- [Test protocol](expert_ratings_test_protocol.json)
- [Results and learned weights](expert_ratings_analysis.json)
- [Historical predictions](expert_ratings_backtests.csv)
- [Scores by election](expert_ratings_cycle_scores.csv)
- [Rating labels and source links](expert_ratings_sources.csv)
- [Prepared rating features](expert_ratings_features.csv)
- [Coverage and source notes](expert_ratings_preparation.json)
- [Research current scenarios](expert_ratings_current_scenarios.csv)
- [Validation](expert_ratings_validation.json)

Primary source check: [Inside Elections public current export](../../../sources/senate_candidates/expert_ratings/current_primary_check.json). Archived raw pages and revisions: [source manifest](../../../sources/senate_candidates/expert_ratings/manifest.json).