Stone (Stafford) Crime Rate November 2025 | Monthly Statistics

In November 2025, Stone (Stafford) recorded a crime rate of 5.0 per 1,000 residents, 31.5% below the UK average of 7.3. This stark contrast highlights the area’s relative safety compared to national trends, though the crime profile reveals a pronounced imbalance between violent and property crimes. Violent crimes accounted for 42.5% of all incidents, significantly outpacing property crimes, which made up 29.1% of the total. This dominance of violent crime, particularly violence and sexual offences, suggests potential local factors influencing crime patterns, such as the area’s compact built-up nature, which may concentrate incidents in specific locations. Seasonal context, including November’s shorter daylight hours and events like Bonfire Night, may contribute to this dynamic, as reduced visibility and community gatherings could create conditions conducive to certain types of crime. However, the area’s overall stability is evident in its consistent low crime rate, which aligns with its small population and limited spatial spread of incidents. The breakdown also shows that property crimes, while lower than violent crimes, remain below UK averages, with shoplifting and anti-social behaviour being the most common property-related and non-violent offences, respectively. This combination of factors illustrates a community that, while experiencing some spikes in specific crime types, maintains a generally secure environment relative to larger urban centres. The seasonal nature of November, with its mix of commercial activity and community events, may further explain the fluctuation in crime types, as seen in the sharp rise in bicycle theft and robbery cases linked to Black Friday shopping. These trends underscore the importance of targeted local strategies to address specific vulnerabilities while maintaining the broader stability observed in the area.

November 2025 marked a significant shift in crime dynamics, with violent crimes accounting for 42.5% of all incidents compared to 29.9% in October. This increase in violent crime, particularly violence and sexual offences, was accompanied by an 18% deficit against the UK average for this category. Meanwhile, property crimes remained below UK levels, though bicycle theft rose sharply by 100% from zero to one incident. The month also witnessed a 57.1% decline in drug-related offences, likely reflecting seasonal changes in illicit activity patterns. For residents, the 100% increase in robbery cases, though still minimal in absolute terms, highlights the need for vigilance during peak shopping periods like Black Friday. The decrease in public order offences by 10% may indicate improved community engagement or enforcement during November’s shorter daylight hours. Other crime and robbery both increased by 100% from zero to one incident, a change that, while statistically significant, may be influenced by the unique dynamics of the month’s calendar, including Bonfire Night and the start of the festive shopping season.

Stone (Stafford) saw an 11.1% decrease in its crime rate from 5.7 to 5.0 per 1,000 residents in November 2025 compared to October, a trend consistent with the built-up area’s compact nature. The daily crime count of 3 incidents averaged over 30 days highlights the concentrated population density, where 1 crime occurred for roughly every 199 residents during the month. This exposure rate, when scaled against the area’s population of 17,276, suggests a relatively stable environment compared to larger urban centres. The decline aligns with seasonal factors, including shorter daylight hours and events like Bonfire Night, which may reduce opportunities for certain crimes. However, the consistent daily crime count remains a critical metric for local authorities, particularly during peak shopping periods like Black Friday, which saw a 100% increase in robbery cases despite the overall rate remaining low. This balance between stability and isolated spikes underscores the need for targeted monitoring in specific contexts.