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·Reported stolen watch stats are based on the Alpha Hands stolen watch registry, which contains over 10k pieces, watch safekeeping info from surveys on IG and forums, and a bit of other info from the DoJ.
Buy safe
Stay safe
Keep your watches safe
oh, caveats on the data at bottom.
Top manufacturers
Rolex: 31%
Breguet: 14%
Breitling: 4%
TAG Heuer: 4%
Top locations
United States: 88%
UK: 5%
Netherlands: 2%
Italy: 1%
Where watches are kept
Bank safe deposit box: 50%
Hidden/sock drawer: 30%
Heavy home safe/TL-15+: 13%
Lightweight home safe: 7%
How watches are insured
Individually insured/personal articles: 44%
None/you live dangerously: 39%
Renters/homeowners: 11%
Blanket policy: 6%
For watches stolen while out of the house (*very few responses to date)
Violent theft or threat of: 40%
Non-violent/grab-and-run: 30%
Didn’t know until later/pickpocket: 30%
Other information
When reading data 'property crime/theft’ (larceny) generally indicates there is no force or threat of force. ‘Robbery’ includes the use or threat of force. ‘Burglaries’ refer to entering a building with intent to commit a crime.
For the United States [1]
- Seasonal patterns do exist for burglaries; lowest burglary rates are in winter, followed by spring and then fall
- Robbery rates do not have seasonal variations
I will continue to aggregate more information, particularly:
- Breakdown of theft/robbery circumstances (in shipping, from home (and if in safe/type if so), while traveling, violent/non-violent, etc.). For those that have inquired, I have not been able to find statistics on the times when a thief is in a home and violence/threat is used to have the homeowner open a safe
- Locations
- If any other questions, let me know!
Caveats
Data are *wildly* dependent on a number of factors, including the sources from which I’ve aggregated (manufacturer, location, language...), the subset/demographics of individuals reporting, value of watch, pieces of information reported, etc. As an example, to date I have had much more success in the United States obtaining data from different sources, which is seen the SKU location mix. Hopefully I can get this to normalize over time.
Statistics on manufacturer/location are on are based upon quantity of watches (not total value or the number of thefts/robberies, in the case when more than one watch was stolen in an event). Survey responses have low response rates and are not particularly meaningful.
[1] https://www.bjs.gov/content/pub/pdf/spcvt.pdf
Buy safe
Stay safe
Keep your watches safe
oh, caveats on the data at bottom.
Top manufacturers
Rolex: 31%
Breguet: 14%
Breitling: 4%
TAG Heuer: 4%
Top locations
United States: 88%
UK: 5%
Netherlands: 2%
Italy: 1%
Where watches are kept
Bank safe deposit box: 50%
Hidden/sock drawer: 30%
Heavy home safe/TL-15+: 13%
Lightweight home safe: 7%
How watches are insured
Individually insured/personal articles: 44%
None/you live dangerously: 39%
Renters/homeowners: 11%
Blanket policy: 6%
For watches stolen while out of the house (*very few responses to date)
Violent theft or threat of: 40%
Non-violent/grab-and-run: 30%
Didn’t know until later/pickpocket: 30%
Other information
When reading data 'property crime/theft’ (larceny) generally indicates there is no force or threat of force. ‘Robbery’ includes the use or threat of force. ‘Burglaries’ refer to entering a building with intent to commit a crime.
For the United States [1]
- Seasonal patterns do exist for burglaries; lowest burglary rates are in winter, followed by spring and then fall
- Robbery rates do not have seasonal variations
I will continue to aggregate more information, particularly:
- Breakdown of theft/robbery circumstances (in shipping, from home (and if in safe/type if so), while traveling, violent/non-violent, etc.). For those that have inquired, I have not been able to find statistics on the times when a thief is in a home and violence/threat is used to have the homeowner open a safe
- Locations
- If any other questions, let me know!
Caveats
Data are *wildly* dependent on a number of factors, including the sources from which I’ve aggregated (manufacturer, location, language...), the subset/demographics of individuals reporting, value of watch, pieces of information reported, etc. As an example, to date I have had much more success in the United States obtaining data from different sources, which is seen the SKU location mix. Hopefully I can get this to normalize over time.
Statistics on manufacturer/location are on are based upon quantity of watches (not total value or the number of thefts/robberies, in the case when more than one watch was stolen in an event). Survey responses have low response rates and are not particularly meaningful.
[1] https://www.bjs.gov/content/pub/pdf/spcvt.pdf
