Ashtakavarga Score Map

A working Ashtakavarga map begins with 7 × 8 × 12 = 672 yes-or-no decisions. Seven planets each receive a 12-sign scorecard, while the Sun, Moon, Mars, Mercury, Jupiter, Venus, Saturn, and ascendant act like eight voters. A classical timing method ends up looking like a fixed aggregation algorithm.

How the votes become a map

For each target planet, every contributor has a prescribed set of favourable positions measured from its natal sign. A permitted position contributes 1; every other position contributes 0. Rahu and Ketu do not vote in the standard calculation.

For planet (p) and sign (r):

Bₚ(r) = Σ eight binary contributions

The resulting Bhinnashtakavarga cell therefore ranges from 0 to 8. Adding the seven planetary maps produces Sarvashtakavarga:

S(r) = Σ seven planetary scores

Its 12 raw cells always total 337 under the standard tables, giving a mean of 28.08 points per sign. Phaladīpikā, chapter XXIII, treats a total above 28 as favourable for transit, but that threshold is a textual rule, not a measured probability.

What the score changes

A Saturn transit is no longer read from Saturn’s sign alone. Its path through a sign carrying 2 bindus in Saturn’s own map is interpreted differently from a path through one carrying 6. Sarvashtakavarga then supplies the wider chart context.

This makes Ashtakavarga a companion to concept vimshottari dasha, not a replacement for it. Dasha selects the active period; Ashtakavarga grades the terrain crossed by a transiting planet.

What is contested

The arithmetic is reproducible once the rule table and convention are fixed. Editions can reverse the visual use of bindu and rekha, and practitioners disagree over reductions, house thresholds, and how much weight the aggregate deserves beside dignity, dasha, and transit.

The predictive claim is harder. No score calculation proves that a 31-point sign produces better outcomes than a 24-point sign. Assumption: I treat the map as a rule-based ordinal signal, not a probability distribution.

Why this crosses realms

Ashtakavarga resembles a fixed ensemble classifier: eight inputs cast binary votes, then a sum becomes a decision aid. The resemblance breaks at calibration. A statistical ensemble learns or tests weights against outcomes; Ashtakavarga inherits its weights from a textual tradition. That boundary belongs beside concept information theory because compression can make a rule inspectable without making it true.

An open question

Could anonymised transit histories test whether raw bindu counts add predictive information beyond concept ephemeris time and a predefined dasha model?

Key Sources

Bṛhat Jātaka by Varāhamihira, chapter IX, N. Chidambaram Aiyar translation, 1905 - an early classical treatment of eightfold planetary relations.
Phaladīpikā by Mantreśvara, chapter XXIII, V. Subrahmanya Sastri translation, 1950 - construction, transit use, and the 28-point threshold.
Ashtakavarga System of Prediction by B. V. Raman, 2006 edition - a modern manual covering individual maps, aggregates, and reductions.

Abhishek's take

What holds me is not whether 29 is lucky. It is that a premodern method forces judgment through 672 inspectable bits. I would rather debug those bits than argue over one impressionistic adjective, but inspectability is not proof.

Where I've used this

I use this structure when writing astrology code: generate every contribution, retain the intermediate map, then aggregate. A wrong longitude should leave a trace back to concept ephemeris time, not hide inside the final score.

Tags: #ashtakavarga #vedic-astrology #transit-timing #aggregation #scorecards

Abhishek