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Other · reviewed 2026-05-16

What are the odds of severe financial harm from regular sports betting?

Evidence quality 4.13/5

Eight-dimension review score against the quality rubric . Each dimension scored 1–5.

D1 Source grounding
3/5
D2 Source authority
4/5
D3 Arithmetic
3/5
D4 Uncertainty
5/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
4/5
D8 Caveat completeness
4/5
Average 4.13/5

Lifetime probability · lifetime, US adult

1 in 100

1.0% lifetime chance

Most people underestimate this.

range 1 in 250 to 1 in 50

lifetime, US adult each band = 10× rarer → zoomed to your factors See full scale →
certain 1 in 1K 1 in 1M 1 in 1B
1 in 11 1 in 667

● your factors — click this risk ▾ to reveal

≈ As likely as

A mobile phone displaying a sports betting app interface with a downward balance indicator, muted palette, flat vector illustration.

Perceived

Sports betting is widely framed as entertainment — a minor stake on a game you would have watched anyway. The post-2018 expansion of legal, mobile-first sportsbooks has normalized wagering in ways that lottery tickets and casino trips never quite did, in part because the products are embedded in sports-media consumption rather than requiring a trip to a dedicated venue. Marketing language leans on "responsible gaming" disclosures while simultaneously promoting parlay products with house edges of 15–30%. Most regular bettors do not identify as problem gamblers, and the financial harm from sports betting is largely invisible until it reaches a crisis — credit exhausted, debt unserviceable — rather than accumulating in a way that triggers earlier intervention.

Rough estimate: ~1 in 100 US adults over a lifetime; ~1-2% of regular bettors face serious harm

Source: editorial intuition, not polled

Actual

States legalizing online sports betting saw bankruptcy rates rise 25–30% and debt collections rise 8% (Hollenbeck, Larsen & Proserpio 2024)

US adults in states that legalized online sports betting post-2018 Murphy v. NCAA, credit bureau panel 2016–2023

Show derivation

Two-factor estimate: (A) P(US adult becomes a regular sports bettor) and (B) P(severe financial harm | regular sports bettor). Factor A: The NY Fed (2026) reports approximately 3% of the US population took up sports betting after their state legalized it, concentrated in younger male demographics. However, the 2018 expansion covered 38+ states by 2025 and the lifetime participation rate is higher than any single cross-section; we estimate 5% of US adults will be regular sports bettors at some point in their lifetime (including states that have not yet legalized, and accounting for future expansion). Factor B: Hollenbeck, Larsen, and Proserpio (2024) find a 25–30% increase in the probability of bankruptcy filing in online-betting states. If the baseline bankruptcy rate among adults in betting-adjacent demographics is ~8% (consistent with the US lifetime bankruptcy rate of ~10%), a 25–30% relative increase implies approximately 10–12% absolute severe-harm rate among regular bettors (using bankruptcy and equivalent severe debt as the indicator). Baker et al. (NBER w33108) find that credit card debt increases, available credit decreases, and overdraft frequency rises among bettors, with effects concentrating among financially constrained households. Combined: 0.05 × 0.20 = 0.010. The 0.20 factor reflects a conservative conversion of the Hollenbeck relative-risk increase to an absolute rate among the regular-bettor subgroup (not the general population). Uncertainty range: 0.004 (3% participation × 12% harm rate among heavy users) to 0.020 (7% participation × 28% severe-harm rate at the upper confidence interval). "Severe financial harm" is defined as bankruptcy filing, debt collections exceeding $5,000, or credit-score decline >50 points attributable to sports-betting activity.

Caveats: The 1% lifetime estimate is built on post-2018 data from states that legalized o…

The 1% lifetime estimate is built on post-2018 data from states that legalized online sports betting, then extrapolated to US adults broadly — the long-run lifetime harm rate depends on whether access continues to expand and whether problem-gambling infrastructure grows proportionally. The Hollenbeck et al. 25–30% relative bankruptcy increase is a population-level effect; converting it to an absolute harm rate among regular bettors requires assumptions about the baseline bankruptcy rate in the bettor subpopulation that carry meaningful uncertainty. This entry covers severe financial harm (bankruptcy or equivalent credit collapse) — a large additional population of regular bettors will experience moderate financial harm (increased debt, credit-score declines) that falls below this threshold. The companion entry gambling-addiction-financial-ruin covers the broader gambling-disorder population; this entry focuses specifically on the post-2018 mobile sports-betting wave and its direct financial consequences. "Regular sports bettor" is not a clinical term — it is used here to mean betting at least weekly over a sustained period, consistent with the active-bettor populations studied in the cited literature.

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Compare to:

In the seven years since the Supreme Court struck down the federal ban on sports betting in Murphy v. NCAA (2018), legal mobile wagering has spread to more than 38 states and embedded itself in sports-media consumption at a speed that outpaced the public-health infrastructure around it. A 2024 analysis by Hollenbeck, Larsen, and Proserpio (using 4.38 million anonymized credit bureau records and a staggered difference-in-differences design) found that states legalizing online sports betting saw 25–30% increases in personal bankruptcy filing probability, ~12-point average credit-score declines, and substantial rises in debt collections and auto delinquencies. The Federal Reserve Bank of New York (2026) reported that while legal sports bettors represent only 3% of the population in legalized states, credit delinquencies among that 3% spiked by more than 10%. Extrapolating to a US adult lifetime — accounting for continued expansion and the ~5% lifetime regular-bettor participation rate — roughly 1 in 100 US adults will experience severe financial harm from regular sports betting. The companion entry gambling-addiction-financial-ruin documents the broader gambling-disorder population; this figure is specific to the mobile sports-betting era and its direct credit consequences.

The harm mechanism is well-characterized: mobile access collapses the temporal gap between impulse and action that historically functioned as a circuit-breaker for problem gambling. NBER Working Paper 33108 (Baker, Balthrop, Johnson, Kotter, and Pisciotta) finds that sports betting spending does not displace other gambling or discretionary consumption; it comes primarily from savings and investment, crowding out positive-expected-value financial behavior. The effect concentrates among financially constrained households for whom the margin of error is smallest: credit card debt increases, available credit shrinks, and overdraft frequency rises. Parlay products — multi-leg bets with house edges of 15–30%, despite being marketed at near-even odds — have become the primary revenue driver for legal sportsbooks and disproportionately attract younger, more financially vulnerable bettors.

The 1% lifetime estimate covers severe financial harm: bankruptcy, debt collections, or credit collapse. A larger population of regular bettors experiences moderate financial harm (meaningful debt accumulation, reduced savings, deteriorated credit scores) that falls below this threshold. Young men aged 18–34 face roughly four times the baseline risk, as they represent the primary target demographic for sportsbook marketing and the highest uptake rates in the post-2018 data. Daily mobile app users face disproportionately higher harm than weekly or occasional bettors; the financial damage concentrates in frequency, not stake size. Casual bettors — one straight-bet per week, no parlay products — account for a small share of the aggregate harm documented in the credit-bureau and transaction data.

Claim ledger

Every number below is what each source reported, with the verbatim quote we relied on and how we arrived at our figure. Click any link to verify directly.

  1. [1] SSRN (Hollenbeck, Larsen & Proserpio) — The Financial Consequences of Legalized Sports Gambling
    The Financial Consequences of Legalized Sports Gambling
    Statistic
    Online sports gambling legalization raised bankruptcy probability 25–30%; average credit score declined ~12 points; debt collections, auto delinquencies, and debt consolidation loans all rose significantly
    Excerpt
    “"In states allowing online sports gambling, the likelihood of a personal bankruptcy filing rose 25% to 30% in the years after legalization. General access to sports betting was associated with a modest decline in average credit scores (0.7 points), while online sports gambling led to a substantially larger decline (about 12 points). The study found substantial increases in average bankruptcy rates, debt sent to collections, use of debt consolidation loans, and auto loan delinquencies." ”
    Source data from
    2024-07-26
    Accessed
    2026-05-04
    Calculation
    This study provides the relative-risk anchor for the native display figure and for Factor B in the normalized estimate. The 25–30% relative increase in bankruptcy probability is a causal estimate from a staggered difference-in-differences design using ~4.38 million anonymized credit-bureau records. Critically, the effect is substantially stronger for online (vs. retail) betting, which is now the dominant form of legal sports wagering. The 28% mid-range is used as the native numerator. Converting this relative estimate to an absolute harm rate among regular bettors requires knowledge of baseline harm rates, which is imputed from the US adult lifetime bankruptcy rate of approximately 10%.
    Independence
    Credit bureau panel data (University of California Credit Panel) is independent from both the NBER Baker et al. household transaction data and from NCPG survey instruments, providing a third distinct measurement approach.
  2. [2] National Bureau of Economic Research (NBER Working Paper 33108) — Gambling Away Stability: Sports Betting's Impact on Vulnerable Households
    Gambling Away Stability: Sports Betting's Impact on Vulnerable Households
    Statistic
    Sports betting reduces savings, increases credit card debt, decreases available credit, and raises overdraft frequency; effects concentrate among financially constrained households
    Excerpt
    “"We find that the increase in sports betting does not displace other gambling or consumption but significantly reduces savings, as risky bets crowd out positive expected value investments. These effects concentrate among financially constrained households, as credit card debt increases, available credit decreases, and overdraft frequency rises." ”
    Source data from
    2024-10-01
    Accessed
    2026-05-04 · archived copy
    Calculation
    Baker, Balthrop, Johnson, Kotter, and Pisciotta (NBER w33108) use household transaction data with a staggered difference-in-differences framework to establish causal effects at the transaction level. This study is complementary to Hollenbeck et al.: where Hollenbeck uses credit bureau outcomes (bankruptcy, credit score), Baker et al. trace the mechanism through spending and savings decisions. Together they establish both the mechanism and the downstream financial consequence of regular sports betting.
    Independence
    NBER w33108 uses household bank-transaction-level data, methodologically distinct from the Hollenbeck et al. credit bureau panel. Both teams applied staggered difference-in-differences to the post-2018 state-level legalization variation, providing independent identification of the same causal effect.
  3. [3] CNBC / Federal Reserve Bank of New York — As March Madness unfolds, NY Fed highlights sports betting toll on consumer credit health
    As March Madness unfolds, NY Fed highlights sports betting toll on consumer credit health
    Statistic
    Credit delinquency rates rose ~0.3% overall in states where sports betting is legal; among the 3% who took up betting, delinquencies spiked more than 10%
    Excerpt
    “"Credit delinquency rates rose about 0.3% overall in states where sports betting is legal, despite legal sports bettors making up only 3% of the population. But, looking only at the 3% of the population who took up sports betting after their state legalized it, credit delinquencies spiked by more than 10% among gamblers." ”
    Source data from
    2026-03-25
    Accessed
    2026-05-04 · archived copy
    Calculation
    The NY Fed data provides the participation rate estimate used in Factor A: approximately 3% of the population became sports bettors post-legalization in each state. The 10%+ delinquency spike among that 3% is a behavioral concentration effect consistent with Hollenbeck et al. and Baker et al. The NY Fed figure is used to calibrate the activity rate in the lower bound of the uncertainty range; the normalized estimate uses 5% as a lifetime participation assumption to account for continued legal expansion and younger cohorts who will age into betting availability.

412 risks with measured probability
1 in 10 1 in 100 1 in 1K 1 in 10K 1 in 100K 1 in 1M 1 in 10M 1 in 100M 1 in 1B certain rarer → Cosmetic surgery abroad risk — 1 in 10 Infant sugar/salt and adult disease — 1 in 10 Endometriosis — 1 in 10 Hair transplant Turkey risk — 1 in 10 Knee replacement — 1 in 10 Chronic painkillers — 1 in 10 Elderly abandonment — 1 in 9.1 Complete tooth loss — 1 in 9.1 Alzheimer's — 1 in 8.3 Sleep deprivation — 1 in 8.3 Smokeless tobacco — 1 in 8.3 Cycling w/o helmet — 1 in 8.0 Bruxism tooth damage — 1 in 7.7 Vision loss — 1 in 6.7 Hernia from lifting — 1 in 6.7 Hip fracture risk — 1 in 6.7 Regular drinking — 1 in 6.7 First heart attack — 1 in 5.9 Infertility — 1 in 5.7 5+ years paid LTC — 1 in 5.6 CTE (football) — 1 in 5.0 Major depression — 1 in 4.9 Hiking injury — 1 in 4.8 Infection from sharing food with child — 1 in 4.2 Lyme disease — 1 in 4.0 Loneliness & health — 1 in 3.8 Job loss & depression — 1 in 3.7 Inheriting AUD risk — 1 in 3.5 Alcohol use disorder — 1 in 3.4 Menopause CV risk acceleration — 1 in 3.0 Silent diabetes — 1 in 3.0 Flying with cold — 1 in 2.9 Tick illness (forest) — 1 in 2.9 Silent high cholesterol — 1 in 2.9 Grandparent loss in childhood — 1 in 2.8 Pacifier floor drop — 1 in 2.8 Drug-resistant infection — 1 in 2.6 No marrow match — 1 in 2.4 Nursing home admission — 1 in 2.2 Skipping dental checkups — 1 in 2.1 False-positive mammogram — 1 in 2.0 Regular smoking — 1 in 2.0 Travelers' diarrhea — 1 in 2.0 Adventure sports — 1 in 1.8 Family caregiver probability — 1 in 1.8 LTC need after 65 — 1 in 1.8 Widowhood probability — 1 in 1.7 Unprotected sex — 1 in 1.5 Silent hypertension — 1 in 1.3 Chronic back pain — 1 in 1.3 Hand hygiene — 1 in 1.0 Cancer (any) — 1 in 7.1 E-scooter no helmet — 1 in 4.5 E-bike no helmet — 1 in 4.0 Mishandled luggage — 1 in 3.7 Deer collision — 1 in 2.7 At-fault injury crash — 1 in 2.5 Flight cancellation — 1 in 1.8 Trip disruption: war or disaster — 1 in 1.7 Home burglary (global) — 1 in 9.1 Hitchhiking assault — 1 in 8.8 Mail check fraud — 1 in 7.7 Child sexual abuse — 1 in 6.8 Stalking — 1 in 6.2 Student sexual assault — 1 in 5.7 Domestic violence — 1 in 3.7 Night walk assault — 1 in 3.6 Bicycle theft — 1 in 2.9 Sexual assault — 1 in 2.9 Home burglary — 1 in 2.6 Sexual harassment (lifetime) — 1 in 1.6 Water scarcity — 1 in 2.5 Carrington-class solar storm — 1 in 1.9 WAIS tipping point — 1 in 1.1 Indoor cat escape harm — 1 in 10 Off-leash dog bite — 1 in 8.9 Rabbit dies in 4 years — 1 in 3.3 Dog bite (non-fatal) — 1 in 1.8 Hamster dies before teenager — 1 in 1.0 Vitamin D gap — 1 in 2.9 Undercooked food — 1 in 1.6 Raw meat cross-contamination — 1 in 1.4 Food left out — 1 in 1.2 AI voice scam — 1 in 2.9 Online scam loss — 1 in 2.5 Teen cyberbullying — 1 in 2.0 Kids & explicit content — 1 in 1.9 Data breach — 1 in 1.1 Miscarriage — 1 in 6.7 Teen suicide attempt — 1 in 5.6 Postpartum depression — 1 in 4.8 Painkiller before infant vaccination — 1 in 3.8 Excessive pregnancy weight — 1 in 2.6 Unvaxxed child & measles — 1 in 2.0 Elder fraud loss — 1 in 10 Pension fund collapse — 1 in 10 Personal bankruptcy — 1 in 10 Housing crash — 1 in 8.3 Crypto total loss — 1 in 6.7 IRS audit — 1 in 6.7 Visa overstay deportation — 1 in 5.6 Long term disability working age — 1 in 4.0 Student loan default — 1 in 3.8 Whistleblower retaliation — 1 in 3.2 Career obsolescence — 1 in 2.9 Forced job exit before retirement — 1 in 2.9 Retirement shortfall — 1 in 2.6 Divorce — 1 in 2.4 Burst pipe damage — 1 in 2.2 Workplace bullying — 1 in 2.1 Deportation (undocumented) — 1 in 1.8 Funeral cost shock — 1 in 1.8 Identity theft — 1 in 1.7 Credit card fraud — 1 in 1.5 School bullying — 1 in 1.5 Insurance claim denial — 1 in 1.4 Frontline soldier casualty — 1 in 1.3 Economic recession — 1 in 1.0 Stock market crash — 1 in 1.0 Hail roof damage — 1 in 3.0 Dry toilet paper harm — 1 in 100 Secondhand smoke — 1 in 91 Gaming disorder (adults) — 1 in 83 High-heel ER visit — 1 in 79 Child throwing object — 1 in 67 Medication reaction — 1 in 58 Cat litter toxoplasmosis — 1 in 48 Mental health LTD claim — 1 in 45 Drug overdose — 1 in 42 Benzo dependence — 1 in 40 Tap water lead — 1 in 40 Medication misuse — 1 in 35 Traumatic brain injury — 1 in 33 Hospital infection — 1 in 31 Air pollution — 1 in 29 End-stage kidney disease — 1 in 29 Traveler's diarrhea (water) — 1 in 26 Skiing injury — 1 in 26 Bipolar disorder — 1 in 23 Dental tourism complication — 1 in 20 Pet parasites — 1 in 20 Undiagnosed ADHD — 1 in 20 Adult-onset food allergy — 1 in 19 Indoor cooking smoke — 1 in 18 Non-Alzheimer's dementia — 1 in 17 Working-age disabling stroke — 1 in 17 Cannabis use disorder — 1 in 16 Stroke — 1 in 15 Parent death/disability — 1 in 14 Severe hearing loss — 1 in 14 Type 2 diabetes — 1 in 13 Appendicitis — 1 in 13 Untreated depression — 1 in 13 Untreated back pain disability — 1 in 13 Heart disease — 1 in 12 Medical error death — 1 in 12 Compulsive sexual behavior — 1 in 12 Eating disorder — 1 in 11 Hip replacement — 1 in 11 Kidney stones — 1 in 11 Sedentary lifestyle — 1 in 11 Salon infection — 1 in 11 Ovarian cancer — 1 in 91 Colorectal cancer — 1 in 77 Breast cancer — 1 in 59 Liver cancer — 1 in 59 Lung cancer — 1 in 56 Prostate cancer — 1 in 50 Melanoma (UV) — 1 in 29 Low-fiber CRC risk — 1 in 23 Red meat & CRC — 1 in 21 Charred meat & cancer — 1 in 20 Maintenance crash — 1 in 83 Driving on sedating meds — 1 in 77 Texting + driving — 1 in 56 Driving after cannabis — 1 in 53 Eating while driving — 1 in 53 Unbelted crash death — 1 in 53 Speeding 20% over limit — 1 in 48 Motorcycle no helmet — 1 in 45 Spaceflight (astronaut) — 1 in 42 Video watching + driving — 1 in 32 Drowsy driving — 1 in 26 E-scooter injury — 1 in 26 Cruise ship norovirus — 1 in 24 Driving at 0.10% BAC — 1 in 16 Catalytic converter theft — 1 in 83 Pickpocketed while traveling — 1 in 38 Stabbed in an assault — 1 in 37 Vehicle theft — 1 in 34 Street robbery / mugging — 1 in 26 Wrongful conviction — 1 in 24 Drink spiking — 1 in 17 Protest under autocracy — 1 in 12 AMOC collapse — 1 in 20 Sting anaphylaxis — 1 in 50 Cat collar injury — 1 in 25 Fish bone injury — 1 in 68 Restaurant food poisoning — 1 in 58 Vegetarian deficiency — 1 in 25 Intimate deepfake — 1 in 25 Social media problematic use — 1 in 13 Infant fall — 1 in 100 Childbirth death (SSA) — 1 in 55 Co-sleeping death — 1 in 43 Toddler stair fall — 1 in 37 Play swing & slide injury — 1 in 33 Autism diagnosis — 1 in 31 C-section complications — 1 in 29 Toy injury requiring ER (child) — 1 in 21 Preeclampsia — 1 in 20 Severe birth tearing — 1 in 17 Gestational diabetes — 1 in 13 Child fall head injury — 1 in 12 Sports betting financial ruin — 1 in 100 Fighter pilot death — 1 in 48 Commercial fishing career death — 1 in 45 Logging career death — 1 in 34 Dying without heir — 1 in 33 Medical bankruptcy — 1 in 25 Compulsive buying disorder — 1 in 20 Rental listing scam loss — 1 in 20 Mortgage foreclosure — 1 in 14 Musculoskeletal LTD claim — 1 in 14 Day-trading losses — 1 in 13 Extremist govt catastrophe — 1 in 13 Hurricane home destruction — 1 in 17 LASIK complications — 1 in 1,000 Infant pool submersion — 1 in 800 MS — 1 in 769 Workplace fatality — 1 in 690 Typhoid fever — 1 in 654 Unsafe imported products — 1 in 565 Brain aneurysm — 1 in 400 COVID-19 — 1 in 400 Fireworks injury — 1 in 385 Sickle cell disease — 1 in 365 Counterfeit medicine — 1 in 361 Spinal cord injury — 1 in 313 Childhood cancer diagnosis — 1 in 285 Next pandemic death — 1 in 208 Dengue (travel) — 1 in 200 Skipping daily showers — 1 in 200 Not scrubbing feet — 1 in 200 Marrow donation risk — 1 in 167 Schizophrenia — 1 in 143 Accidental fall — 1 in 135 Parkinson's — 1 in 125 Sudden death during exercise — 1 in 123 Suicide (US) — 1 in 121 Opioid addiction — 1 in 114 Tuberculosis (global) — 1 in 108 Radon cancer — 1 in 435 Testicular cancer — 1 in 250 Cervical cancer — 1 in 167 Pancreatic cancer — 1 in 125 Pedestrian death — 1 in 806 Motorcycle crash — 1 in 694 Boating drowning — 1 in 685 Driver kills pedestrian — 1 in 552 Phone-distracted walking injury — 1 in 400 EV battery fire — 1 in 333 Cyclist killed by car — 1 in 196 Hand-held phone call + driving — 1 in 143 Petrol car fire — 1 in 125 Self-driving car fatality — 1 in 115 Car crash — 1 in 105 Firefighter duty death — 1 in 455 Police duty death — 1 in 313 Homicide — 1 in 287 Pig-butchering scam — 1 in 106 Extreme heat — 1 in 333 Climate change death — 1 in 204 Swallowed bee/wasp — 1 in 500 Bat bite & rabies — 1 in 238 Mosquito-borne disease — 1 in 190 Food poisoning (global) — 1 in 317 Solar panel fire — 1 in 667 Untreated childhood scoliosis — 1 in 1,000 Child window fall — 1 in 855 Walker stair fall — 1 in 625 Baby walker injury — 1 in 455 Maternal mortality — 1 in 272 Untreated childhood flat feet — 1 in 250 Maternal age & birth defects — 1 in 200 Child death (<18) — 1 in 143 Caving career death — 1 in 167 EMS duty death — 1 in 794 Civilian war casualty — 1 in 499 Soldier in combat — 1 in 270 Mining career death — 1 in 214 Gambling financial ruin — 1 in 159 Wildfire home destruction — 1 in 120 Lightning home fire — 1 in 105 Malaria (travel) — 1 in 10,000 Infection from shared drink — 1 in 10,000 Chagas disease — 1 in 8,475 Wild berry fox tapeworm — 1 in 8,475 Schistosomiasis death — 1 in 6,667 Sudden death (young adult) — 1 in 3,922 Unsafe wiring — 1 in 3,390 Sepsis from wound — 1 in 2,857 Anesthesia awareness — 1 in 2,500 Heat stroke (outdoor) — 1 in 1,905 House fire — 1 in 1,818 Rabies from dogs — 1 in 1,449 Drowning — 1 in 1,379 Shallow-water diving SCI — 1 in 1,111 Choking — 1 in 1,099 EVALI vaping hospitalization — 1 in 1,064 Betel nut cancer — 1 in 1,290 Blood clot (flight) — 1 in 4,651 Killing a cyclist — 1 in 3,937 Teen road-crash death — 1 in 3,030 Child rear bike seat — 1 in 2,500 Child without restraint — 1 in 2,000 Fatal police encounter — 1 in 4,739 Honor killing — 1 in 2,381 Intimate-partner homicide — 1 in 1,767 Hurricane — 1 in 8,929 Drought famine death — 1 in 6,536 Blizzard death — 1 in 4,367 Earthquake — 1 in 3,802 Dog chocolate death — 1 in 2,000 Food poisoning (US) — 1 in 1,862 Fish mercury — 1 in 1,695 Phone/laptop battery fire — 1 in 1,136 SIDS — 1 in 7,143 Laundry pod ingestion — 1 in 6,494 Untreated infant hip dysplasia — 1 in 5,000 Pool drowning — 1 in 2,299 War (civilian) — 1 in 2,000 Fatal bee/wasp sting — 1 in 76,923 Anesthesia death — 1 in 50,000 Dog hot car death — 1 in 41,667 Anaphylaxis — 1 in 27,548 Chiropractic neck manipulation — 1 in 16,667 CO poisoning — 1 in 14,006 Hepatitis A (travel) — 1 in 12,500 Skipping allergy immunotherapy — 1 in 11,111 Acrylamide & cancer — 1 in 16,667 Bus crash — 1 in 100,000 Plane crash — 1 in 58,824 Child pedestrian (residential) — 1 in 45,455 Railroad crossing death — 1 in 20,704 Child bike trailer — 1 in 14,286 Acid attack — 1 in 89,286 Terrorism — 1 in 77,519 Child stranger abduction — 1 in 38,760 Stranger kidnapping — 1 in 35,211 Dowry death — 1 in 13,158 Accidental gun death — 1 in 11,299 Wildfire — 1 in 100,000 Tornado — 1 in 80,645 Tsunami — 1 in 52,632 Ocean drowning — 1 in 29,155 Flood — 1 in 20,202 Landslide death — 1 in 18,416 Supervolcano eruption — 1 in 12,376 Crocodile attack — 1 in 84,746 Bee sting — 1 in 78,927 Fatal scorpion sting — 1 in 26,110 Plastic container leaching — 1 in 16,949 Infant in car seat — 1 in 64,935 Bouncer chair fall — 1 in 60,606 Toddler choking — 1 in 50,000 Unsupervised infant choking — 1 in 50,000 Magnet ingestion — 1 in 12,048 Snorkeling death — 1 in 21,739 Pet in transport — 1 in 20,000 Landmine or UXO injury — 1 in 14,728 Vaccine reaction — 1 in 763,359 Aluminum & Alzheimer's — 1 in 169,492 Residential gas leak — 1 in 140,845 Child hot car death — 1 in 102,041 Glyphosate & cancer — 1 in 1,000,000 Teflon cookware cancer — 1 in 169,492 Roller coaster injury — 1 in 312,500 Cruise ship accident — 1 in 188,679 Ferry sinking — 1 in 133,333 Turbulence injury — 1 in 114,943 School shooting — 1 in 192,308 Mass shooting — 1 in 113,636 Nuclear accident — 1 in 833,333 Avalanche — 1 in 210,526 Lightning — 1 in 209,205 Snake bite — 1 in 884,956 Spider bite — 1 in 833,333 Hippo attack — 1 in 564,972 Dog bite — 1 in 142,045 Pesticide residue — 1 in 1,000,000 Dirty can illness — 1 in 200,000 PLA bioplastic harm — 1 in 169,492 Charger left plugged in — 1 in 200,000 Infant swing death — 1 in 714,286 Child blind cord strangulation — 1 in 416,667 Child plastic bag suffocation — 1 in 263,158 Button battery — 1 in 250,000 Inclined sleeper death — 1 in 238,095 Elevator/escalator death — 1 in 188,324 Japanese encephalitis (travel) — 1 in 2,000,000 Kid + front airbag — 1 in 10,000,000 Asteroid impact — 1 in 1,351,351 Banana spider eggs — 1 in 10,000,000 Shark attack — 1 in 5,681,818 Bear attack — 1 in 3,787,879 Wild berry poisoning — 1 in 2,222,222 Space debris hits property — 1 in 10,000,000 Piranha attack — 1 in 135,135,135 Phone at gas pump — 1 in 1,000,000,000 Phone on plane — 1 in 1,000,000,000 Alien contact — 1 in 169,491,525
Lottery jackpot 1 in 95,238