Worst Small USA Towns With HUGE Crime Rates
Credibility score: 35/100 — Low Credibility. High BS alert! Many claims lack evidence or are misleading.
BSmeter analyzed "Worst Small USA Towns With HUGE Crime Rates" and rated it 35/100 for credibility (a BS score of 65/100 — low credibility), on 2026-07-19. Its weakest claim — "Comparing Battle Creek's crime to larger cities, claiming it 'struggles to compete.' The numbers don't match. 🍒" — scored 20/100 and was flagged as cherry-picked. 17 claims were checked against the video transcript. Scores are produced by BSmeter's AI analysis of the transcript, not independent human verification.
Of 17 claims analyzed: 7 scored under 40, 10 between 40 and 69, and 0 at 70 or above.
Claims analyzed
Teaser promises 1-in-9 crime odds and murdered vloggers in a real US town — Emotional Button (45/100)
At 0:00
Opens with nightmare odds and a murdered vlogger — fear as the hook before any data appears.
Why this score: The 1-in-9 figure is presented as a literal town stat with zero source or timeframe attached, and the vlogger murder is dropped as a dramatic detail with no verification offered. Classic emotional-button opener that primes viewers to expect horror stories before the list even begins.
Original quote: “Can you imagine living in a small town where there’s a one in 9 chance of you being the victim of a serious crime, a town where even popular vloggers get shot dead? That’s an actual place in the USA where it seems nobody is untouched by violence.”
Defines 'small town' as under 50k and cites FBI as source — Missing Context (45/100)
At 0:21
Calls under 50k 'small' while most people think of actual tiny towns — quietly redefines the category.
Why this score: The video sets its own arbitrary cutoff at 50,000, then labels everything below it 'small towns.' This moves the goalposts from what viewers usually picture as small towns and lets them include much larger places that still fit the scary list. FBI data is named but no specific tables or years are shown yet.
Original quote: “15. Battle Creek, Michigan We’ll clarify something first; to fit the criteria of this show, we’ll say by small, we mean less than a population of 50,000 people. The data we’ll use is from the FBI.”
Comparing Battle Creek's crime to larger cities, claiming it 'struggles to compete.' The numbers don't match. 🍒 — Cherry-Picked (20/100)
At 1:55
They give numbers for Flint, Detroit, and Grand Rapids, then claim Battle Creek 'struggles to compete.' But Battle Creek's rate is higher per capita. That's a cherry-pick, mortal. 💀
Why this score: The speaker presents crime numbers for Flint, Detroit, and Grand Rapids, then immediately claims these larger cities 'would struggle to compete with Battle Creek.' However, a quick calculation shows Battle Creek's violent crime rate (12.08 per 1000) is significantly higher than Flint's (1284 crimes / 95212 people ≈ 13.48 per 1000), Detroit's (13040 crimes / 663502 people ≈ 19.65 per 1000), and Grand Rapids' (1286 crimes / 200000 people ≈ 6.43 per 1000). The claim that Battle Creek 'struggles to compete' is a misrepresentation, ignoring the per capita rates that show it's actually *less*…
Original quote: “but those places aren’t classified as small towns. They would struggle to compete with Battle Creek,
anyway. Flint is home to 95,212 people and had 1,284 violent crimes. Detroit’s population
is 663,502, and it saw 13,040 violent crimes, while Grand Rapids has just over 200,000 people,
and it…”
Using a 2007 stat and a 2023 conviction to paint a current picture. 😈 — Cherry-Picked (20/100)
At 4:14
They're pulling a 2007 'highest rate' stat and then jumping to a 2023 conviction. That's a 16-year gap, mortal. Not exactly current data. 🍒
Why this score: The speaker highlights a 2007 statistic about Dillingham having the 'highest per capita sexual misconduct rate' and then immediately follows it with a 2023 news story about a conviction for 'this type of crime.' This is cherry-picking data points from vastly different years to create a continuous narrative of high crime, ignoring any changes or trends that might have occurred in the intervening 16 years. It's a classic misdirection. 😈
Original quote: “It’s grimmer when you learn that in 2007 it had the highest per capita sexual misconduct rate in the US at one incident for every 103.9 people. The latest crime news story we could find told us a 59-year-old man in 2023 got 13 years in prison for exactly this type of crime.”
Drops poverty numbers right after crime story — implies causation — Missing Context (45/100)
At 4:14
Poverty stat follows prison sentence like it's the cause — never proves the link. 🔥
Why this score: They just served the crime anecdote, then immediately served the income numbers. The viewer is meant to connect them, but no data shows poverty caused that specific crime. Classic missing-context move: present two true facts in sequence so the audience supplies the causal story themselves.
Original quote: “Per capita income for Dillingham is just $21,537, well below the US average of $68,309. In Dillingham, 10.1% of families and 11.7% of the population live under the poverty line.”
Raw totals + per-capita rates = 'one in 66 chance' for a town of 38k — Missing Context (45/100)
At 5:09
One-in-66 sounds terrifying — but that includes every assault and robbery, not just stranger danger. 💀
Why this score: They give both absolute numbers and the dramatic probability. The 1-in-66 figure folds in domestic violence, bar fights, and known-offender cases. Without that breakdown, the viewer pictures random street violence. The framing works because the scary number lands before the nuance can.
Original quote: “There were 585 violent crimes in this town when the FBI released its data and a further 2,356 property crimes. That’s a lot for a place this small. It means there are 15.23 violent crimes for every 1000 people and 61.35 property crimes for 1000 people. In general, if you live there, there’s a one…”
Admits improvement, then immediately pivots to stolen guns and fentanyl doom — Volume Game (45/100)
At 5:49
Quiet 'improved over the decade' then loud opioid and gun-theft numbers. Classic volume switch. 🚩
Why this score: They drop the 'it got better' line in one breath, then spend the next 40 seconds on the chief's fentanyl and stolen-firearm quotes. The improvement fact is technically there, but the emotional weight and screen time go entirely to the scary stuff. The net message the viewer walks away with is still 'this place is a mess.'
Original quote: “Believe it or not, though, even with these dazzling crime statistics, the crime problem in Spartanburg has improved over the last decade. Still, in 2022, 130 firearms were stolen, and 78 were taken from vehicles. The chief also had this to say, “The opioid problem is significant here in the city,…”
Violent crime in these towns is far more likely than sharks, planes, or lightning — perspective via extreme comparisons. — False Equivalence (20/100)
At 7:55
Compares rare freak events (shark, lightning) to ongoing local crime rates — apples to hand grenades.
Why this score: The move is classic: stack absurdly low-probability national events against a localized annual risk. A 1-in-61 yearly chance of violent victimization isn't the same category as a 1-in-11-million lifetime shark death. The comparison makes the town crime sound apocalyptic while hiding that most Americans never face those odds in their own neighborhood.
Original quote: “Let’s put these numbers into perspective. In the US, you have one in 11.5 million chance of being killed by a shark. Your chance of dying from a terrorist attack is 1 in 45 million. The odds you’ll die in a plane crash are 1 in 205,552, and the odds of being killed by lightning are 1 in 114,195.…”
Sets up a false premise about small towns to make the 1% stat seem more shocking. 😈 — Straw Man (20/100)
At 8:30
Nobody thinks 'all small towns have murder news.' That's a straw man to make the 1% stat hit harder. 🔥
Why this score: The speaker creates a straw man argument by suggesting viewers might believe 'all small towns have news about murders,' then immediately refutes it with a dramatic statistic. This makes the statistic seem more profound by attacking a position nobody actually holds, rather than presenting it plainly.
Original quote: “You might think, well, all small towns have news about murders. In fact, no, they don’t. Just 1% of US counties are responsible for a massive 42% of America’s murders. Most towns don’t experience the ultra-violence you’ll hear about today, which is about to get much worse.”
Calls drugs the biggest contributor — no data shown — Confidence Mismatch (45/100)
At 10:30
Declares drugs the top cause with zero comparison to poverty or other factors.
Why this score: Presents a single cause as dominant without evidence ranking contributors. Missing context on what data would actually support that ranking.
Original quote: “The biggest contributor to this crime problem is drugs, lots and lots of drugs.”
"Vast majority" of US guns are black-market — no source given — Missing Context (45/100)
At 12:49
"Vast majority are black-market" — zero data, just dropped it like fact 💀
Why this score: Speaker asserts most American guns are illegal without citing ATF, CDC, or any study. The claim flips the usual narrative that most guns start legal then get diverted, but offers no evidence for the stronger version.
Original quote: “The US easily has the highest rate of gun ownership in the world, at about 120 guns for every 100 people. The vast majority are black-market guns.”
One in 30 violent crime chance — raw rate presented as near-worst without national context — Missing Context (45/100)
At 14:33
Drops the one-in-30 stat like it's apocalyptic — leaves out how tiny populations inflate per-capita rates dramatically.
Why this score: Violent crime rate = incidents/population. In a 3k-person town, even 111 crimes yields an eye-popping percentage that looks far worse than equivalent numbers in bigger cities. No baseline comparison to national average or similar small towns makes the number feel more damning than the raw count warrants.
Original quote: “7. Kotzebue Alaska In Kotzebue, a town with just over 3,000 people 30 miles from the Arctic Circle, you have about a one in 30 chance of being the victim of a violent crime. That’s almost as bad as it gets.”
Compares East St. Louis to war zones then downplays violence with 1-in-95 stat — False Equivalence (20/100)
At 16:57
Equates a US town to Afghanistan/Iraq travel warnings — then quietly switches to a diluted violent crime probability.
Why this score: The Afghanistan/Iraq comparison is pure emotional escalation. Then the 1-in-95 figure only covers reported violent crime overall; it doesn't reflect the 36 murders already cited, making the risk sound smaller than the raw numbers suggest.
Original quote: “There are even warnings about this place, telling tourists to be careful, just like you’d find on websites about Afghanistan or certain parts of Iraq. When the data was published, on top of the 36 murders, there were 27 reports of sexual misconduct, 32 robberies, and 173 assaults. Murders are sky…”
Comparing modern Pine Bluff murder rates to the 'Medieval Age' for dramatic effect. 😈 — False Equivalence (20/100)
At 19:46
Comparing a modern US town to the 'Medieval Age' is pure hyperbole. Different times, different worlds. 🔥
Why this score: The speaker compares a specific modern US town's murder rate to the 'Medieval Age.' This is a false equivalence because societal structures, data collection, and definitions of crime were vastly different in the Medieval Age. It's an emotional appeal designed to shock, not an accurate historical comparison.
Original quote: “Pine Bluff, there are 56.5 murders per 100,000 people, which is high for the Medieval Age,”
Compares small-town headlines to war-zone violence for shock — Emotional Button (45/100)
At 20:30
Stacks four crime headlines then equates them to soldiers seeing less action — fear button, no context on actual rates.
Why this score: Uses loaded war-zone comparison to make the viewer feel the town is uniquely apocalyptic. The emotional punch replaces any statistical comparison to actual combat zones or national averages.
Original quote: “45.6% of people under age 18 live in poverty. As we were making this show, a news story headline was, “Two juveniles held without bond for capital murder.” Right below it was a story saying, “Since March, there have been four people under 18 years shot and killed in the city.” Another headline was,…”
Compares Monroe’s 19 murders to Greater Manchester’s 46 across 2.8 million people — apples to continents — False Equivalence (20/100)
At 22:55
Throws a 47k town against a 2.8-million metro area like the populations are comparable. The scale difference makes the comparison meaningless.
Why this score: Monroe’s murder count is being measured against an entire English county with sixty times the people. Even if Greater Manchester had the same per-capita rate, the raw number would be much higher. The speaker knows the listener will hear “only 46” and feel shocked by Monroe’s 19, but the populations are so mismatched the stat is doing the heavy lifting instead of the actual rate.
Original quote: “There’s a one in 38 chance you’ll become a victim of violent crime and an unbelievable one in 18 chance you’ll be the victim of a property crime. Even for Louisiana, where crime is famously high, these are really shocking numbers. Just to give you some more perspective, in the UK, in Greater…”
The 'one in X chance' framing makes crime rates sound more personal and immediate. 😈 — Loaded Language (45/100)
At 24:45
Turning raw numbers into 'your chance' is a classic fear-mongering move. It's not wrong, but it's designed to hit harder. 💀
Why this score: While the underlying statistics (850 violent crimes, 2032 property crimes in 26,000 people) might be accurate, presenting them as 'you have a one in 30 chance' or 'one in 13 chance' is a rhetorical device. It personalizes the risk, making it feel more immediate and threatening to the viewer, rather than just stating the crime rate per capita. It's an emotional button, not just a neutral statistic.
Original quote: “This means you have a one in 30 chance of being the victim of a violent crime but a one in 13 chance of becoming the victim of a property crime.”
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