Which nakshatra are most people born under?

None of them, in the sense the question is usually asked. Counted across 1,657 birth charts stored on AstroMedha on 26 August 2026, the highest tally is a tie: Ardra and Swati at 73 charts each, 4.41 percent. The lowest is Shravana at 45, 2.72 percent. Those two rates look different enough to mean something. They do not. Split the same 1,657 charts in half by the date each person signed up and the leader of one half sits 16th out of 27 in the other half.

A nakshatra is one of the 27 equal segments the sidereal zodiac is divided into, each 13 degrees 20 minutes wide, measured against the fixed stars rather than the seasons. Your nakshatra, also called your birth star, is the segment the Moon occupied at the moment you were born. Every one of the 27 collects close to one twenty-seventh of all births, and the star sitting at the top of any "most common birth star" list is there by luck of the draw.

What was counted

The population is every birth chart saved in AstroMedha's profile table as of 26 August 2026. There were 1,661 rows. Three carry a birth date later than the count date, which is a typing slip rather than a birth, and one has a birthplace that resolves to no timezone at all. Those four were dropped. 1,657 charts were computed. No row in the table carries a test-account marker, so nothing was excluded on that ground.

The charts belong to 1,632 accounts. 1,631 of them are the account holder's own birth details and 26 were entered for somebody else, usually a family member. Folding together rows that repeat the same name, date and clock time leaves 1,620 distinct people. The profiles were created between 27 March and 25 August 2026, so this is five months of sign-ups rather than a lifetime archive.

Birth years run from 1946 to 2026, with a median of 1997. Eight in ten of the charts fall between 1977 and 2007. 1,375 of the 1,657 birthplaces name India as the country, and of the 1,573 charts whose birthplace was resolved to map coordinates, 1,420 of those coordinates fall inside India. 1,405 charts were cast at Indian Standard Time. This is an Indian population born mostly in the last five decades, and every number on this page should be read as a description of that group first.

Two facts about the birth times matter more here than they would on most pages, because the Moon moves fast enough that an hour changes the answer.

The first is the clock. AstroMedha writes 12:00 exactly when somebody skips the birth-time field, so a chart showing noon on the dot is a chart with no real time behind it. 194 of the 1,657 are that placeholder and 1,463 carry a real clock. The database also carries a birth_time_known flag, and it is deliberately not the test used here: a schema change in August 2026 set that flag to false for every row already in the table, whether or not a real time had been given. The clock is the test.

The second is rounding. 318 of the 1,657 birth times land exactly on the hour and 1,130 land on a multiple of five minutes, against the 28 and 331 you would expect if people reported to the exact minute. Birth times get remembered as "about six o'clock". Rounding to the nearest hour moves the Moon by about 0.28 degrees at its average speed and at most 0.32, which is 2 to 2.4 percent of a nakshatra and 8 to 9.6 percent of a pada, so it almost never changes the star and sometimes changes the quarter. A birth time wrong by whole hours is the bigger risk, and that one is measured below.

Every chart was cast the same way: Swiss Ephemeris positions, the Lahiri sidereal ayanamsa, and the birth timezone resolved at the birth date and place rather than at today's date, so a birth inside a daylight-saving period is not shifted by an hour. The Moon's nakshatra depends on the instant of birth and not on where that birth happened, so a vague birthplace does not shift the count directly. It shifts the timezone the clock is read in, and the timezone shifts the instant. The size of that effect on this table is measured two sections down.

The full count, all 27

Zodiac order, not rank order, so you can find yours without hunting. The last column is what the sky itself did over 88.5 years, measured separately and explained further down.

An even split would put 61.37 charts in every row. The observed counts run from 45 to 73. Whether that range means anything is the whole question, and it takes three separate tests to answer, because each one catches a different way of being fooled.

Test one: is the whole table further from even than chance allows?

The standard measure of "how far is this table from an even split" is the chi-square statistic. It adds up the squared distance of each of the 27 rows from the 61.37 an even split predicts, scaled so that the total can be read as a probability: how often 27 genuinely equal bins would drift this far apart on their own. For these counts the statistic is 32.594 across 26 degrees of freedom, and that happens by chance about 17 times in 100.

Seventeen in a hundred is unremarkable. To check that the reference is the right one for a table this size, the same test was run against 200,000 simulated sets of 1,657 charts drawn from a genuinely even 27-way split. 17.29 percent of those simulations landed at least as far from even as our real charts did. The two agree, so nothing about the shape of this table is out of the ordinary.

Test two: is the leader higher than a leader should be?

The chi-square measures the table as a whole. It can miss a single row that is genuinely elevated, which is the claim a "most common nakshatra" headline actually makes. So the same 200,000 simulations were asked a narrower question: when you deal 1,657 charts into 27 truly equal bins, how high does the highest bin go?

The median highest bin is 77 charts. Ninety percent of the time it lands between 72 and 85. The largest in 200,000 simulations was 109.

Our observed leader is 73, which sits below the median of what pure chance produces. Some star reached 73 or higher in 92.6 percent of the simulated even draws. A leader at 73 out of 1,657 is not evidence of anything except that 27 bins were filled.

The distance from top to bottom tells the same story from the other end. Ours is 28 charts, from Ardra and Swati at 73 down to Shravana at 45. Under an even split the median gap is 31, and 74 percent of simulations produced a gap at least as wide as ours. Our table is slightly flatter than randomness usually manages.

There is a matching way to read the confidence intervals. Ardra at 73 out of 1,657 carries a 95 percent interval of 3.52 to 5.50 percent. Shravana at 45 carries 2.04 to 3.61 percent. Those two intervals overlap, and both contain 3.70 percent, which is one twenty-seventh. The top and the bottom of the table are statistically the same number.

Test three: does the ranking hold when you split the data?

The first two tests say the spread is consistent with chance. The third shows it directly, without any statistics at all, and it is the test worth remembering.

Sort the 1,657 charts by the date the person created their profile and cut the pile in two, 828 charts in the earlier half and 829 in the later half. These are two independent samples of the same population. If some nakshatra genuinely collected more births, the two halves would agree about which one.

They do not agree at all.

• The earlier half's leader is Magha with 42 charts. In the later half, Magha ranks 16th of 27.
• The later half's leader is Swati with 43 charts. In the earlier half, Swati ranks 14th of 27.
• The rank correlation between the two halves is 0.130, and shuffling one half's ranks at random beats that figure 53 percent of the time.

A rank correlation of zero means the order in one half tells you nothing about the order in the other. 0.130 with a 53 percent chance of arising from a shuffle is zero for practical purposes. The ranking in the table above is a snapshot of which way the coins fell in one particular set of 1,657 people, and adding the next 1,657 will produce a different leader.

Change one handling decision and the leader changes

There is a plainer demonstration hiding in the data quality, and it is worth showing because it is the kind of thing a published statistic normally hides.

75 of the 1,657 charts store a timezone of UTC+0 while naming an Indian birthplace. These are rows where the birthplace was typed freely and never resolved to coordinates, so the app kept its blank-slate offset instead of Indian Standard Time. Almost certainly those 75 births happened at IST, five and a half hours ahead of what was stored.

Recompute just those 75 at IST and the rest of the table untouched:

The nakshatra changes for 24 of those 75 charts and the pada, meaning the quarter of the nakshatra the Moon sat in, changes for 70 of the 75. That single cleaning decision, touching 4.5 percent of the rows, is enough to break a tie at the top and to swap the star at the bottom. Any headline naming one most-common nakshatra is resting on choices at least this small.

What the sky itself does

Everything so far describes 1,657 people. The deeper question is whether the sky offers each nakshatra an equal share of time in the first place, and that has nothing to do with who signs up for anything. It can be measured exactly.

The Moon crosses each 13 degree 20 minute segment in roughly a day, so over a long enough span the share of time it spends in each segment is the share of births each segment can collect. Every crossing between 1 January 1946 and 26 August 2026 was located to the second by narrowing down on the exact moment the Moon's sidereal longitude passed a boundary. Over those 29,457 days there were 29,110 crossings, which is 0.988 boundary crossings per day.

The Moon does not travel at a constant speed. It runs fastest when closest to Earth and slowest when furthest, so the time it takes to cross one nakshatra ranges from 20.81 hours to 27.20 hours, with a mean of 24.29 hours. That is a swing of more than six hours between the quickest crossing and the slowest, which sounds like more than enough to favour some segments over others.

It does not, because the fast part of the Moon's orbit is not parked over any one part of the zodiac. The point of closest approach drifts steadily forward and returns to where it started every 8.85 years. Give the measurement a whole number of those cycles and every nakshatra receives the same treatment.

The gap between the most-held and least-held segment shrinks as the window covers more complete cycles, from 3.15 percent over a single decade down to 0.11 percent over ten whole cycles. Over that 88.5-year window every one of the 27 was entered either 1,183 or 1,184 times, a difference of one crossing out of nearly 1,200.

Two things follow. A decade-long window really does tilt, by a few percent, which is a genuine finding and the closest thing to a "more common" nakshatra that exists. And that tilt is a property of the decade you measured rather than of the star, so it points at a different winner each time and cancels over a human lifetime of births.

The irony sits in the last two columns. Ardra is one of the two leaders in our 1,657 charts and is the segment the Moon spent the least time in over 88.5 years.

A second count, with no people in it

A rate measured over people who chose to enter their birth details on an astrology site could carry a pattern from the people rather than from the sky. So the same count was run over a population with no users in it at all: 117,829 birth moments, one every six hours from 1 January 1946 to 26 August 2026, which is the same span the real birth dates cover. Nobody is born on that timetable, which is the point of it.

The most-held nakshatra in that control takes 4,377 of the 117,829 moments, or 3.715 percent. The least-held takes 4,349, or 3.691 percent. An even split is 3.704 percent. The chi-square across all 27 comes to 0.427 on 26 degrees of freedom, which is an almost perfect fit to an even split, as it should be at that sample size.

So the flat answer holds whether you count real people or count the clock. Seventy times more moments than the real charts, and the leader beats the trailer by 28 counts out of about 4,364.

The padas are flat too, and they are the fragile part

Each nakshatra divides into four padas, meaning quarters of 3 degrees 20 minutes each. There are 108 in total, and they are what a Vedic reading uses when 27 answers is too coarse.

An even split puts 414.2 in each. The chi-square is 1.851 on 3 degrees of freedom, which arises by chance 60 times in 100. Restricting to the 1,463 charts with a real clock gives 367, 374, 348 and 374, and a chi-square of 1.238. The 117,829-moment control splits 29,475, 29,467, 29,425 and 29,462, which is as even as counting gets.

All 108 star-and-pada cells are occupied, at an average of 15.34 charts each. The busiest is Uttara Bhadrapada pada 1 with 27 and the thinnest is Pushya pada 3 with 3. Those two numbers are not a ranking of anything. With 15 charts expected per cell, a cell holding 27 and a cell holding 3 are both ordinary, and this page will not print a "most common pada" for the same reason it will not print a most common nakshatra.

The pada figures also carry a caution the nakshatra figures do not. A pada is 3 degrees 20 minutes wide and the Moon covers that in about six hours, so a birth time out by three hours moves you half a pada and lands you in the neighbouring quarter about half the time. That is what the timezone section measured from the other direction: shifting 75 charts by five and a half hours moved 24 of their nakshatras and 70 of their padas. A nakshatra survives a shaky birth time. A pada does not.

The one place our charts do depart from even

Reading the same Moon positions at sign level rather than star level gives a different verdict, and it is the one departure on this page, so here it is with its caveats attached rather than left out.

An even split puts 138.1 in each of the twelve. The chi-square is 23.398 on 11 degrees of freedom, p = 0.0155, which is a departure a conventional threshold would call real. It survives the handling variants: restricting to real-clock charts gives p = 0.027, and recomputing the 75 mis-zoned charts at IST gives p = 0.012.

Three things argue against making anything of it.

The same twelve signs measured on the 117,829-moment control give a chi-square of 0.208 on 11 degrees of freedom, with the most-held sign at 8.354 percent against the least-held at 8.320 percent and an even split at 8.333. The sky offers the twelve signs equal time to within 0.034 of a percentage point. Whatever produced the tilt in our 1,657 charts, it did not come from the sky.

This is also one of five cuts of the same 1,657 charts examined for this page: by star, by pada, by sign, by ruling planet, and by half of the data. Run five checks against a 0.05 threshold on data where nothing at all is happening and there is a 23 percent chance at least one of them comes back below it. One did.

And the 27-way cut that the 12-way cut is built from is flat, at p = 0.174. Signs contain a little over two nakshatras each, so a sign-level tilt with no star-level tilt means neighbouring stars happened to fall on the same side of the line together. That is what a run of luck looks like when you bin it more coarsely.

The honest statement is that our own users' Moon signs are not evenly spread and no cause for it has been established. It is not offered here as a fact about birth.

Which planet starts most lives

Every nakshatra is ruled by one of nine planets, three stars each, and that ruling planet decides which dasha, meaning which dated planetary period, your life opens in. The nine run in a fixed order and total 120 years, and the whole ladder is called the vimshottari, which is the scheme Vedic practice uses to date the turns of a life. Each of the nine at that top level is a mahadasha, which is the longest chapter a reading works with, and each one subdivides into shorter periods below it. The Moon's exact position inside your nakshatra sets both which planet's mahadasha you were born into and how many of its years were still unspent on that day.

An even split puts 184.1 charts under each planet, and the chi-square is 8.098 on 8 degrees of freedom, p = 0.424. Flat again, as it must be, since three flat stars per planet add to a flat planet.

The last two columns carry the part that is not a restatement. The starting planet is evenly spread, one life in nine. The number of years each planet holds is not, because the nine periods are very different lengths. Venus runs 20 years and the Sun runs 6. So one person in nine is born into a Sun period that must end by their sixth birthday at the latest, and one in nine is born into a Venus period that can still be running at 20. Over a completed 120-year cycle, 20 of those years belong to Venus and 6 to the Sun, which is 16.7 percent against 5 percent, however evenly the birth stars fell.

That difference is the reason the question "which nakshatra is most common" is less useful than it sounds even if it had an answer. Nothing about your working life depends on how many other people share your star. It depends on where you stand on your own ladder, which the free dasha calculator will date from the same Moon position this page counted.

Why it feels like one star is everywhere

The flat answer contradicts an experience many people have, which is that a particular nakshatra seems to keep turning up among their friends and family. Both things are true and here is the mechanism.

People born on the same date almost always share a star. Among the 1,657 charts there are 166 dates carrying two or more births, giving 246 pairs of people who share a birthday-and-year. 196 of those 246 pairs share a nakshatra, which is 79.7 percent, against the 3.7 percent you would get from two people picked at random. 132 of the 246 share the nakshatra and the pada, 53.7 percent.

That follows from the Moon's speed. Sampling 200 dates from the birth span at 96 clock times each, the day's most-held nakshatra takes a median 76 percent of the day, and 191 of the 200 days hold exactly two nakshatras, one before the boundary crossing and one after. Only 6 of the 200 sat inside a single nakshatra from midnight to midnight. So your birth date narrows 27 possibilities to two, usually with one of the two holding three quarters of the day.

The clustering has a very short reach, and the same 1,657 charts show exactly how short. Taking every pair of charts born within ten days of each other: pairs born on the same date share a star 79.7 percent of the time, pairs born one day apart share it 12.3 percent of the time, and across the 1,970 pairs born between two and ten days apart, not one shared a star. The Moon takes 27.3 days to travel through all 27 segments and returns to none of them in between. So a person born the same night as you will usually carry your star, and a cousin born the same month almost never will.

The same arithmetic works against the other common assumption. Two people picked at random from our 1,657 share a nakshatra 3.777 percent of the time, against the 3.704 percent an even split predicts. They share both nakshatra and pada 0.998 percent of the time, against 0.926 percent. Both observed rates are a whisker above the even-split figure, and that whisker is the sampling wobble already measured above.

Your birthday does not fix your star either. Take one calendar date and cast it at the same clock time in every year from 1946 to 2026. The 8 May chart lands in 26 different nakshatras across those 81 years, with no star repeating more than five times. Your nakshatra belongs to the specific day you were born, not to the anniversary you celebrate.

How large a count would settle it

Suppose one nakshatra genuinely did collect more births. How many charts would it take to see that?

These are the sample sizes at which a genuine edge of that size would show up as a significant result four times out of five. At 1,657 charts this count can only rule out an edge of about a third or more, and it does rule that out. Anything subtler needs a population an order of magnitude larger.

That bound is worth stating plainly rather than hiding behind the headline. This page has not proved that all 27 nakshatras are exactly equal in the population. It has shown that the observed spread across 1,657 charts is what an even split produces, that the ranking does not replicate across halves of the same data, and that the sky offers the 27 equal time to within 0.11 percent over 88.5 years. A real effect small enough to survive all three would be too small to matter to any individual reading.

The count will be re-run as the chart store grows, and if a leader ever holds its place across a split of the data, that will be published here with the same tests attached.

Finding your own

Nothing above tells you which nakshatra is yours, because that needs your birth details rather than a table.

The free nakshatra finder takes your date, time and place of birth and returns your Moon's nakshatra, its pada, its ruling planet and its deity, using the same engine and the same Lahiri sidereal ayanamsa every number on this page was computed with. Enter the time as precisely as you have it. If your time is a rough recollection, the star it returns will usually be right and the pada may not be, for the reason given in the pada section.

Once you have the star, its own page carries the reading: the deity, the symbol, the ruling planet's signature, and what the classical texts attach to it. The free dasha calculator turns the same Moon position into your dated period ladder, and the free kundli casts the whole chart around it.

What a computed chart adds that this page cannot

Everything above is a property of a population, which is precisely why it can sit on a public page. Three things change from person to person and none of them can be tabulated.

The first is which house your Moon's nakshatra actually falls in, counted from the sign that was rising when you were born. The same star in the tenth house of career and in the twelfth house of expenditure read very differently, and the rising sign needs your birth time and birth place rather than only your date.

The second is the condition of your nakshatra's ruling planet in your own chart. The table above gives you the planet. Your chart gives you which sign it occupies, which houses it governs for you, and whether it sits strong or weak there. Two people with the same birth star and opposite placements of its ruling planet are not carrying the same reading.

The third is the ladder itself. The section on ruling planets gives you which period you started in. Your own chart gives the exact date every period boundary falls on from birth onward, and which one you are standing inside today. That is the part that answers when rather than what, and it is the reason a nakshatra reading is worth computing rather than looking up.

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