Oakville Vehicle Thefts Stats and Maps
This dashboard provides a focused look at nearly 900 vehicle theft incidents reported in Oakville between mid-2024 and early-2026. It highlights where stolen vehicles are most frequently reported, seasonal trends, and the times of day when thefts are most likely to occur.
- Vehicle theft is consistent year-round, averaging roughly 40–60 incidents per month.
- Industrial and arterial roads such as WyeCroft Rd and Winston Park Dr see the highest theft volumes.
- Summer months show increased activity, with July and August together accounting for over 13% of cases.
- Early morning hours (5–8 AM) are the highest-risk period, suggesting overnight thefts.
- Daytime thefts are less common, indicating reduced risk during business and commuting hours.

Statistics & Charts
Summary
This dataset captures approximately 880 vehicle theft incidents reported in Oakville over the past year and a half. It focuses specifically on stolen vehicles, highlighting where thefts most often occur, how activity changes month to month, and which times of day present the highest risk.
Geographic Distribution
Temporal Trends
Time of Day
Search
| Case Number | Location | Incident Date | Street Name |
|---|---|---|---|
| 202600002064 | NORTH SERVICE RD W | 2026-01-03 08:57:13 | NORTH SERVICE RD W |
| 202500381338 | ROCKINGHAM DR | 2025-12-25 12:20:07 | ROCKINGHAM DR |
| 202500352640 | MAYFAIR RD | 2025-11-24 09:05:00 | MAYFAIR RD |
| 202500363623 | DUNDAS ST E | 2025-12-06 15:41:00 | DUNDAS ST E |
| 202500332774 | SOUTH SERVICE RD W | 2025-10-23 20:55:00 | SOUTH SERVICE RD W |
| 202500360895 | NINTH LI | 2025-10-11 14:30:00 | NINTH LI |
| 202500353499 | AGRAM DR | 2025-11-25 07:22:00 | AGRAM DR |
| 202500382842 | BRONTE RD | 2025-12-27 01:00:00 | BRONTE RD |
| 202500385058 | CROSS AV | 2025-12-27 12:00:00 | CROSS AV |
| 202500350469 | ROSEMOUNT CR | 2025-11-21 07:50:00 | ROSEMOUNT CR |
| 202500329250 | BRIDGE RD | 2025-10-30 07:33:00 | BRIDGE RD |
| 202500342495 | MAYLA DR | 2025-11-13 02:15:00 | MAYLA DR |
| 202500342570 | NAPIER CR | 2025-11-13 08:06:00 | NAPIER CR |
| 202500381418 | BRANT ST | 2025-12-25 00:49:00 | BRANT ST |
| 202500352941 | DUNEDIN RD | 2025-11-24 18:42:00 | DUNEDIN RD |
| 202500380590 | STALYBRIDGE DR | 2025-12-24 10:08:00 | STALYBRIDGE DR |
| 202500358326 | SHEDDON AV | 2025-11-29 22:00:00 | SHEDDON AV |
| 202500366516 | TRAFALGAR RD | 2025-12-09 08:00:00 | TRAFALGAR RD |
| 202500342516 | OVERFIELD RD | 2025-11-13 00:50:00 | OVERFIELD RD |
| 202500350101 | GRAND BV | 2025-11-21 13:41:00 | GRAND BV |
| 883 rows found, showing 20. | |||
About This Dataset
This dataset consists of approximately 883 reported vehicle thefts across Oakville, offering a targeted view of property crime affecting residents and businesses. Unlike broader crime summaries, this data concentrates solely on stolen vehicle incidents.
Geographically, thefts tend to cluster along industrial and mixed-use corridors such as WyeCroft Rd, Winston Park Dr, and Speers Rd. These areas often contain large parking lots, commercial fleets, or commuter parking, which may increase opportunity for theft.
From a time-based perspective, vehicle theft remains relatively steady throughout the year, averaging around 40–55 cases per month. Summer months—particularly July and August—stand out as the busiest period, while winter months are slightly lower but still consistent.
Time-of-day patterns show a strong early-morning concentration. Most thefts are reported between 5:00 AM and 8:00 AM, indicating vehicles are commonly taken overnight and discovered later in the morning rather than during active daytime hours.
Overall, this dataset highlights persistent vehicle theft risk across Oakville, with clear geographic and temporal patterns that can help inform prevention strategies and targeted patrol efforts.
Dataset Information
| Subject | Safety |
|---|---|
| Jurisdiction | Town of Oakville, Province of Ontario |
| Data Provider | Halton Regional Police Service, City of Oakville |
| Source | https://portal-exploreoakville.opendata.arcgis.com/ |
| Attribution | - |