1,284

Estimates

What is the read, seat by seat, with honest error?
Why this screen exists

Fielding 300 interviews in each of 543 seats is expensive and still fragile. Multilevel regression with post-stratification does better: fit a model of vote choice across the whole national sample, then re-weight its predictions onto each constituency's own demographic composition. A seat with 74 interviews borrows strength from the 400 seats that resemble it. This is how a national broadcaster gets a seat map on a Tuesday instead of a state map in three weeks, and the post-stratification frame it needs is months of work that a rival cannot buy.

The second half is why 2024 broke. Vote share estimates were not badly off; seat forecasts were, because seat-level errors were treated as independent. They are not. If a poll is off two points nationally it is off two points nearly everywhere at once and hundreds of marginals flip together. Adding a shared swing term widens the interval roughly fourfold and, critically, contains the truth.

Which forces a presentational change. A broadcaster wants "NDA 361". The defensible output is a probability of a majority. Whether he can sell that to a television partner is the real commercial question on this screen.

Nominal interviews
2,14,600
What a rival puts on a chyron
Effective sample
1,38,900
Kish, after raking and trimming
Seats estimated
543 / 543
Via post-stratification
Headline output
P(majority)
Not a seat number pretending to be a fact
Independent seat errorsthe 2024 assumption
ACTUAL 293CENTRE 361170470

Errors cancel across 543 seats, the distribution collapses, and the model reports a tight range with high confidence. 80% interval ±12 seats.

Correlated national swingwhat actually happens
ACTUAL 293CENTRE 318170470

A shared swing term drawn per simulation, plus regional terms, on top of seat noise. 80% interval ±48 seats, and the outcome sits inside it.

Seat filepartial pooling, sample of 10 of 543
ConstituencyStatenRawPooledShrinkage80% intervalCall
BaramatiMaharashtra412+8.1+7.40.7+2.9 to +11.8Callable
WayanadKerala388+21.4+20.60.8+15.9 to +25.2Callable
KanniyakumariTamil Nadu96+2.1+4.92.8−2.4 to +12.1Too close
Chandni ChowkDelhi241+11.8+10.90.9+5.1 to +16.6Callable
DhubriAssam74−14.2−9.64.6−19.8 to +0.4Too close
GhatalWest Bengal163+3.4+1.81.6−4.9 to +8.4Too close
BastarChhattisgarh88+6.9+3.23.7−5.1 to +11.4Too close
KalaburagiKarnataka204−4.1−3.30.8−9.6 to +3.0Too close
NagaonAssam61+1.2+5.84.6−3.7 to +15.2Under quota
JaunpurUttar Pradesh527+9.6+9.40.2+5.4 to +13.4Callable

Shrinkage is large where n is small and near nil where n is deep, which is exactly the behaviour you want. Leads are expressed as a margin between the top two options in this demonstration build.