Given that Wikipedia is already changing its tune on the reliability of Benford's Law in detecting fraud, it's obvious that those utilizing it to analyze the election results are right over the target. This Twitter thread shows how statistical analysis demonstrates that the excessively pro-Biden electoral counts are obviously fraudulent.
Which, of course, is why Infogalactic is a much better source of information on the subject:
law, also called the first-digit law, is a phenomenological law about the
frequency distribution of leading digits in many (but not all) real-life sets
of numerical data. The law states that in many naturally occurring collections
of numbers the small digits occur disproportionately often as leading
significant digits. For example, in sets which obey the law the number 1 would
appear as the most significant digit about 30% of the time, while larger digits
would occur in that position less frequently: 9 would appear less than 5% of
the time. If all digits were distributed uniformly, they would each occur about
11.1% of the time. Benford's law also concerns the expected distribution for
digits beyond the first, which approach a uniform distribution.
Accounting fraud detection
In 1972, Hal Varian suggested that
the law could be used to detect possible fraud in lists of socio-economic data
submitted in support of public planning decisions. Based on the plausible
assumption that people who make up figures tend to distribute their digits
fairly uniformly, a simple comparison of first-digit frequency distribution
from the data with the expected distribution according to Benford's Law ought
to show up any anomalous results. Following this idea, Mark Nigrini showed that
Benford's Law could be used in forensic accounting and auditing as an indicator
of accounting and expenses fraud. In practice, applications of Benford's Law
for fraud detection routinely use more than the first digit.
the United States, evidence based on Benford's law has been admitted in
criminal cases at the federal, state, and local levels.