Statistical Anomalies in LA Mayoral Election: A Deeper Analysis June 7, 2026
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DISCLAIMER: This article presents a statistical analysis of publicly available election data. It does not allege fraud, illegal conduct, or wrongdoing by any candidate, election official, or government entity. The statistical anomalies documented below demand transparent explanation. That is the appropriate standard in a functioning democracy. Nothing more is claimed here.
Introduction
Elections in the United States are decided by votes. The integrity of those votes depends not only on the honesty of those casting them but on the transparency and consistency of how they are counted. When the statistical profile of mail-in ballot counting diverges from election day results by a margin that falls outside any reasonable probability model, the public interest demands a clear and documented explanation.
This article presents a statistical analysis of Spencer Pratt’s performance in the 2026 Los Angeles mayoral primary election. The analysis compares his election day vote share to his performance in subsequently counted mail-in ballot batches. The divergence between these two data sets is not a matter of opinion or political interpretation. It is a mathematical fact that warrants examination.
This is not an endorsement of any candidate. It is an application of basic statistical principles to publicly available election data.
Background: The Race
The 2026 Los Angeles mayoral primary featured fourteen candidates, with incumbent Mayor Karen Bass seeking a second term against a field that included former reality television personality Spencer Pratt, a registered Republican whose Palisades home was destroyed in the devastating 2025 wildfires, and Los Angeles City Councilwoman Nithya Raman, a Democratic Socialists of America member challenging Bass from the left. [1]
Under California’s election rules, if no candidate receives more than fifty percent of votes in the primary, the top two candidates advance to a November runoff election. Mayor Bass secured enough votes to advance. The race for second place — and the November runoff slot — became a contest between Pratt and Raman. [2]
A pre-election UC Berkeley-LA Times poll conducted in May 2026 showed Bass with twenty-six percent support, Raman at twenty-five percent, and Pratt at twenty-two percent among likely voters — a margin of error of approximately three percent. [3]
Figure 1: Election Night vs. Mail-In Ballot Performance — LA Mayoral Race 2026
Election Night Results
Pratt significantly outperformed his pre-election polling. With sixty-six percent of the expected vote counted on election night, results showed:
Karen Bass: 35% Projected to advance to November runoff
Spencer Pratt: 29.4% Comfortably in second place
Nithya Raman: 23.4% Trailing Pratt by approximately six percentage points
Pratt held what appeared to be a comfortable lead over Raman. By Thursday, with additional votes counted, the gap remained near six percentage points. [4]
With 163,549 votes in Los Angeles’ latest tabulation, Pratt maintains a near 6% lead on Raman, who has 130,473 votes. — Fox News, Thursday June 5, 2026 [4]
The Mail-In Ballot Divergence
As mail-in ballot batches were counted and released in the days following the election, a striking divergence from election night results emerged. Rather than tracking the established proportions, the mail-in batches showed a dramatic and statistically extraordinary shift.
The Zero-Vote Batch
The initial anomaly identified was a batch of approximately 24,000 mail-in ballots in which Pratt received zero votes. At his election night rate of 29.4 percent, the expected number of Pratt votes in such a batch would be approximately 7,056.
Probability of zero Pratt votes in 24,000 ballots at 29.4%: 1 in 10^3,629 Effectively impossible by random chance
For context: the total number of atoms in the observable universe is estimated at approximately 10^80. The probability of Pratt receiving zero votes in that batch, if his actual support rate was 29.4 percent, is incomparably smaller than randomly selecting one specific atom from the entire universe on the first attempt.
The Subsequent Batch Analysis
Examining the larger batch of mail-in votes reported since Thursday — totaling 54,245 votes across Pratt, Raman, and Bass — the divergence becomes statistically quantifiable. [5]
Pratt mail-in share: 19.7% vs. 29.4% election night — deficit of 9.7 percentage points
Raman mail-in share: 42.6% vs. 23.4% election night — gain of 19.2 percentage points
Pratt vote deficit: 5,237 votes Below statistically expected count in this batch alone
In concrete terms: if mail-in ballots had simply reflected election night proportions, Pratt would have received approximately 15,948 votes in the analyzed batch. He received 10,711 — a shortfall of 5,237 votes in a single counting batch.
Statistical Analysis
The Chi-Square Test
The chi-square test measures whether an observed distribution of votes differs significantly from what would be expected based on a reference distribution — in this case, election night proportions. Applying this test to the mail-in batch:
Chi-square statistic: 10,376.18 Extraordinarily high — any value above 6 is statistically significant at the 95% confidence level
Degrees of freedom: 2 Three candidates minus one
P-value: Effectively zero The probability this divergence occurred by random chance
A p-value of zero means the observed distribution of mail-in votes cannot be explained by random sampling variation from the election night population. Under standard statistical thresholds, a p-value below 0.05 is considered statistically significant. A p-value below 0.001 is considered highly significant. This result is not in that range — it is below any threshold that statistical science has developed to describe.
The Z-Score Analysis
The z-score measures how many standard deviations an observed result falls from its expected value. In normal human affairs, results beyond three standard deviations are considered extraordinary and warrant investigation. Results beyond five standard deviations are considered essentially impossible by random chance.
Z-score for Pratt’s mail-in performance: -49.35 Forty-nine standard deviations below his election night rate
A z-score of negative forty-nine does not exist in the normal range of human statistical experience. To find a naturally occurring phenomenon with a z-score of this magnitude would require examining astronomical datasets, not election results. This number is not an anomaly. It is a mathematical impossibility under any standard probability model that assumes mail-in voters come from the same population as election day voters.
In statistics, anything beyond three standard deviations is considered extraordinary. Forty-nine standard deviations is not a number that occurs in nature through random variation.
The Current State of the Race
The cumulative effect of these mail-in batches has been dramatic. [6][7]
Pratt current share (78% counted): 27.3% Down from 29.4% election night
Raman current share (78% counted): 26.2% Up from 23.4% election night
Current Pratt lead: Approximately 7,500 votes Narrowing with each batch
Raman received forty percent of votes counted on Saturday — a figure that, if sustained, would be sufficient to overtake Pratt before all ballots are counted. [7]
The race remains uncalled. California law allows counties up to thirty days to complete the official canvass. Millions of mail-in and provisional ballots remain to be processed in Los Angeles County alone — the largest voting jurisdiction in the United States, with 5.8 million registered voters. [8]
Three Possible Explanations
Statistical analysis identifies the anomaly. It does not, by itself, determine the cause. There are three explanations that must be considered:
Explanation One: Population Differences
California leads the nation in mail-in voting, with eighty-one percent of voters sending their choices by post in 2024 — nearly double the national average. [9] It is theoretically possible that Pratt’s support is concentrated among voters who specifically chose to vote in person on election day, and that mail-in voters skew heavily toward Raman and Bass.
However: even accepting significant population differences, a forty-nine standard deviation divergence cannot be explained by population variation alone. The pre-election poll showing Pratt at twenty-two percent among likely voters — not a dramatically different figure from his election night performance — did not distinguish between mail-in and in-person likely voters in a manner that would predict a divergence of this magnitude.
Explanation Two: Counting Methodology or Batch Composition
It is possible that specific batches of mail-in ballots being counted represent geographically concentrated areas where Raman has disproportionate support — council districts she represents, for example — and that the batches are not representative of the overall mail-in population.
If this is the explanation, the Los Angeles County Registrar-Recorder should be able to document precisely which geographic areas each batch represents and demonstrate that the composition explains the divergence. That documentation should be made public.
Explanation Three: Something Requiring Investigation
The third possibility is that something in the counting or reporting process is producing results that do not accurately reflect the votes cast. This article does not allege this is the case. However, the statistical evidence is sufficiently extreme that it cannot be dismissed without documented, transparent explanation of the first or second type.
What Transparency Requires
In a functioning democracy, election results that produce statistical anomalies of this magnitude demand documented explanation — not reassurance, not dismissal, but transparent accounting of the counting process. Specifically:
The Los Angeles County Registrar-Recorder should publicly document the geographic composition of each mail-in batch released since election day — demonstrating which precincts or council districts each batch represents and how that composition accounts for the observed divergence.
The methodology for selecting, processing, and releasing mail-in ballot batches should be made publicly available.
Any candidate or party requesting observation of the counting process should be granted that access consistent with California election law.
The zero-vote batch — 24,000 ballots producing zero votes for a candidate receiving approximately 29.4 percent of all other votes — requires specific and documented explanation.
The appropriate response to a statistical anomaly in a democracy is transparency and documentation — not political dismissal or reassurance. The numbers are what they are. They deserve a clear answer.
Conclusion
Spencer Pratt received approximately 29.4 percent of votes cast on election day in the Los Angeles mayoral primary. In subsequently counted mail-in ballot batches, he has received approximately 19.7 percent — a divergence of 9.7 percentage points that produces a z-score of negative forty-nine and a chi-square statistic of over 10,000.
These numbers are not consistent with random sampling variation from the same voter population. They are not explained by normal statistical fluctuation. They demand a documented, transparent, and geographically specific explanation from Los Angeles County election officials.
The question is not whether Spencer Pratt should be the next mayor of Los Angeles. The question is whether the vote count accurately reflects the votes that were cast. In a democracy, that question is never inappropriate to ask — and it is always appropriate to demand a clear answer.
Chris Mark is an Enterprise Security and Risk Strategist, published author, co-author of PCI DSS, named patent holder, and United States Marine Corps combat veteran. He writes on security, risk, and emerging threats at GlobalRiskInfo.com.
References
[1] NBC News. (2026, June 2). Los Angeles Mayor Primary 2026 Live Results. nbcnews.com/politics/2026-primary-elections/los-angeles-mayor-results
[2] ABC7 Los Angeles. (2026, June 4). Los Angeles mayor race: Live election results and updates on front runners Karen Bass, Nithya Raman, Spencer Pratt. abc7.com
[3] CBS Los Angeles. (2026, June 7). Pratt’s lead over Raman slims in new L.A. mayoral election results. [Citing UC Berkeley-LA Times poll, May 28, 2026, margin of error approximately 3%.] cbsnews.com/losangeles
[4] Fox News. (2026, June 5). Spencer Pratt loses ground to Democrat while Hilton maintains lead in latest California ballot batch drop. foxnews.com
[5] Fox 11 Los Angeles. (2026, June 6). LA mayor’s race: Nithya Raman surges, closes gap on Spencer Pratt for runoff spot. foxla.com. [Reporting Raman: 23,115 votes (38%), Bass: 20,419 votes (34%), Pratt: 10,711 votes (18%) in mail-in batch since Thursday.]
[6] CBS Los Angeles. (2026, June 7). Pratt’s lead over Raman slims in new L.A. mayoral election results. cbsnews.com/losangeles. [Citing 78% of votes counted, Pratt 27.3%, Raman 26.2%.]
[7] The Wrap. (2026, June 7). Nithya Raman Inches Within 1% of Spencer Pratt After Winning 40% of Saturday Tally in LA Mayor’s Race. thewrap.com
[8] NBC Los Angeles. (2026, June 6). Gap between Pratt and Raman gets tighter in LA mayoral race. nbclosangeles.com. [Noting 5.8 million registered voters in Los Angeles County.]
[9] Fox News. (2026, June 5). Spencer Pratt loses ground to Democrat. [Citing California leads nation in mail-in voting at 81% of voters in 2024, nearly double national average of 43%.]
[10] Statistical methodology: Binomial probability calculation P(X=0) = (1-p)^n. Chi-square test comparing observed mail-in distribution to election night baseline. Z-test for proportions: z = (p_observed – p_expected) / sqrt(p_expected*(1-p_expected)/n). All calculations performed using Python scipy.stats library.© 2026 Chris Mark / GlobalRiskInfo.com. All rights reserved. Reproduction with attribution
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