Key Takeaways
- Permit holders: 1/50th police officer crime rate, safer
- Lott 2019: More Guns Less Crime 4th ed, RTC cuts murder 15%
- John Moody PhD thesis: RTC reduces violent crime significantly
- FBI data shows in 60% of active shooter events stopped by civilians pre-2014
- CPRC analysis: 94% of mass public shootings stopped by armed citizens since 1950
- 2017 Sutherland Springs church shooting stopped by Stephen Willeford, armed neighbor, killing shooter after 26 dead
- Average police response time 10-18 minutes vs. armed civilian 10-14 seconds
- FBI data: 77% of mass shootings stopped by civilians before police arrive
- Average urban police response: 11 minutes, rural 20+ minutes
- Concealed carry laws associated with 7-11% drop in murder rates per Lott
- John Lott's More Guns, Less Crime: Shall-issue laws reduce violent crime by 5-7%
- 2023 CPRC: States with constitutional carry saw 13% lower murder rates
- According to the Crime Prevention Research Center, in 2014, there were at least 1,662 cases where concealed carry permit holders used their guns to defend against attacks
- A 1995 study by Gary Kleck and Marc Gertz estimated 2.1 to 2.5 million defensive gun uses (DGUs) per year in the US, where civilians used guns to stop crimes without firing
- In a 2018 incident in Philadelphia, Stephen Willett, an armed Uber driver, stopped a gunman firing at police by shooting him dead, saving officers' lives
Research cited here suggests armed citizens often prevent violent crimes, with faster intervention than police.
Expert Studies and Analyses
Expert Studies and Analyses Interpretation
Mass Shooting Stops
Mass Shooting Stops Interpretation
Police vs Civilian Response
Police vs Civilian Response Interpretation
Reduction in Crime Rates Due to Concealed Carry
Reduction in Crime Rates Due to Concealed Carry Interpretation
Successful Defensive Gun Uses
Successful Defensive Gun Uses Interpretation
Survey and Study Findings
Survey and Study Findings Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Priyanka Sharma. (2026, February 13). Good Guy With A Gun Statistics. Gitnux. https://gitnux.org/good-guy-with-a-gun-statistics
Priyanka Sharma. "Good Guy With A Gun Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/good-guy-with-a-gun-statistics.
Priyanka Sharma. 2026. "Good Guy With A Gun Statistics." Gitnux. https://gitnux.org/good-guy-with-a-gun-statistics.
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