Mathematical prediction of Vidhan Sabha Seats

© Anant  ·  State Electoral Mathematics  ·  Original Research

State Vidhan Sabha
Electoral Model

V(E) = f(x₁…x₂₁) — 21-Variable function mapped to each state's Vidhan Sabha seat count | © Anant

Select State / UT — Choose a State / UT — Uttar Pradesh (403) Maharashtra (288) West Bengal (294) Bihar (243) Madhya Pradesh (230) Tamil Nadu (234) Rajasthan (200) Karnataka (224) Gujarat (182) Andhra Pradesh (175) Odisha (147) Kerala (140) Assam (126) Telangana (119) Punjab (117) Jharkhand (81) Chhattisgarh (90) Haryana (90) Jammu & Kashmir (90) Uttarakhand (70) Delhi (70) Himachal Pradesh (68) Tripura (60) Manipur (60) Meghalaya (60) Nagaland (60) Arunachal Pradesh (60) Goa (40) Mizoram (40) Sikkim (32) Puducherry (30)

403

Total Seats

202

Majority Mark

215

Safe Majority

Select a state to see context

⚡ Live Vidhan Sabha Seat Simulator — drag sliders

V(E) Score

—

Projected Seats

—

State Range

Min: 0
Max: —

Verdict

Select a state first

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Seat Distribution

0——— ✦——

0–2 Wipeout

3–19 Fringe

20+ Opposition

Majority−1 Hung

Majority Simple

60%+ Comfortable

75%+ Landslide

Click card to expand · drag slider → live seat update

Master State Electoral Seat Function — © Anant

V(E) = Σ _i=1→21 w_i · x_i · c_i (t,s) + I_alliance − δ_anti-incumb + ε_shock

S(seats) = round( V(E) × N )    where N = total Vidhan Sabha seats of the state
subject to: S ∈ [0, N]  ·  S_min = 0  ·  S_max = N  ·  majority = ⌊N/2⌋ + 1
For each state, N varies: UP=403, MH=288, WB=294, TN=234 … Sikkim=32

Symbol Definitions

V(E) ∈ [0,1]

Electoral Victory Probability — normalised across all 21 variables

wᵢ ∈ [0,1]

Weight of variable i — shifts by state, election cycle, and political context

xᵢ ∈ ℝ

Intensity of variable i — positive amplifies; negative reduces V(E)

cᵢ(t,s)

Contextual multiplier — function of time t and specific state s

I(alliance)

Alliance seat-transfer bonus — pre-poll coalition vote share synergy

δ

Anti-incumbency decay ∝ Tenure × Fatigue × Failure_count

ε(shock)

Exogenous shock — sudden local/national event altering outcome

S ∈ [0, N]

Final seat projection bounded by state's total Vidhan Sabha strength

21 Component Sub-Functions

Mathematical Constraints

∴

S ∈ [0, N]

Bounded by state's seat count N

∴

V(E) ∈ [0, 1]

Normalised probability

∴

Majority = ⌊N/2⌋+1

Simple majority threshold varies by state

∴

wᵢ state-specific

Weights differ: RP, RL higher in TN/WB; J higher in UP/BI

∴

RP, RL amplified in S-India

Regional & language variables more powerful in Tamil Nadu, Bengal, etc.

∴

Non-linear interactions

J×D (North India); RL×RP (South/East); WE×YV (new states)

Select a state from the dropdown above to see its electoral history equations

© ANANT — All Rights Reserved

All original analytical content, mathematical framework, state-specific variable definitions,
formulae, and electoral model design are the exclusive intellectual property of Anant.
Unauthorised reproduction or distribution is prohibited.

V(E) = 21-Variable State Electoral Function  |  S(seats) ∈ [0, N] where N = state Vidhan Sabha strength
Original analytical model by Anant. Not a predictive algorithm.