Exploring theft trends in Victoria using CSA (2016–2025) and SEIFA 2021 data
29-10-2025
In the last ten years, theft has grown faster than any other type of crime in Victoria.
While other offences have stayed steady, theft keeps rising, especially in cities and busy regional areas.
Many people think that poorer areas have more theft, but the data tells a more complex story.
This project looks at how theft has changed over time, where it happens most, and how it links to social and economic conditions.
This project uses two main data sources:
(Sources: Crime Statistics Agency Victoria, 2025; Australian Bureau of Statistics SEIFA 2021.)
The chart shows how property and deception offences dominate Victoria’s crime profile, consistently outnumbering every other category across 2016–2025. Then, after a decline through 2020–2022 which may likely due to COVID-19 restrictions, offences surged again, reaching a decade high in 2025.
This pattern frames the next part of the story:
Why are property and deception offences rising so strongly compared with other crimes?
The figure breaks down Property and Deception Offences into their key subdivisions from 2016 to 2025. The thick line represents the division total, while the thinner lines show each offence category.
Theft (B40) stands out as the dominant driver of this division, far exceeding burglary, property damage, and deception across all years. This indicates that fluctuations in total property crime are largely shaped by changes in theft.
To understand where these thefts are occurring, the next section explores regional differences across Victoria’s Local Government Areas.
The interactive map highlights clear geographic variation in theft across Victoria.
Urban LGAs, especially Melbourne, Port Phillip, and Maribyrnong, record the highest incident rates—often exceeding 2,000 thefts per 100,000 people.
Regional centres such as Ballarat and Latrobe also stand out, indicating that theft is not solely a metropolitan issue.
These spatial differences raise an important question for the next section:
Do areas facing greater socio-economic disadvantage experience higher theft rates?
(Use search box to find the LGA more easier)
Does disadvantage explain theft rates?
This chart combine two datasets which are the 2025 theft rates from the Crime Statistics Agency and the 2021 SEIFA disadvantage scores from the ABS. Each dot shows a local government area (LGA) in Victoria. The position of the dot tells us the area’s level of disadvantage (left is more disadvantaged) and its theft rate (higher is more theft). The colour of each dot shows how disadvantaged the area is, from dark (more disadvantaged) to light (less disadvantaged).
I made this plot to see whether disadvantaged areas tend to have more theft. The result shows only a weak relationship where places with higher theft are not always the most disadvantaged. For example, Melbourne and Yarra have high theft rates but are not very disadvantaged.
This indicates that the rise in theft we saw earlier is not just about poverty or disadvantage, but may also relate to urban density and more opportunities for theft in big cities.
Ballarat has recorded higher theft rates than the Victorian average across 2016–2025, reaching almost 4,300 thefts per 100,000 people in 2025. Although Ballarat’s SEIFA score (Decile 6) places it in the mid-range for socio-economic conditions, its theft rate remains among the highest in the state.
This maybe indicates that other factors, such as tourism, retail areas, and population turnover, may have a stronger influence than disadvantage alone because It may shows how each community’s context matters when we interpret Victoria’s crime patterns.
Discussion
The analysis shows that theft (B40) is the key driver of Victoria’s recent rise in property and deception offences. The increase is most visible in urban areas such as Melbourne, Yarra, and Ballarat, where population density and economic activity create more opportunities for theft. In contrast, the relationship between disadvantage (SEIFA IRSD) and theft is weak, suggesting that social disadvantage alone does not explain where theft occurs most. Instead, local context and urban dynamics, such as retail activity, mobility, and tourism, appear to play a stronger role.
Key Takeaways
Limitations