ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WORCESTER, MA · 2023
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/worcester/2023-annual-report
Yearly Traffic Safety Analysis
5,175 CRASHES IN
WORCESTER, MA
2023
In 2023, Worcester recorded 5,175 traffic crashes, an 8.7% increase from the 4,763 crashes reported in 2022. Despite the overall rise in collisions, the number of fatalities saw a notable decrease, dropping from 15 in the prior year to 7 in the current year. Conversely, crashes involving serious injuries nearly doubled from 55 to 106.
5,175
▲ 8.7%was 4,763
Total Crash Events
7
▼ -53.3%was 15
Persons Killed
1,470
▲ 14.5%was 1,284
Persons Injured
1,082
▲ 19.2%was 908
Hit-and-Run Crashes
Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 803 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crashes in Worcester trended upward year-over-year. The total number of crashes increased by 412, from 4,763 in 2022 to 5,175 in 2023, representing an 8.7% rise. The number of people injured also increased by 14.5%, from 1,284 to 1,470.
1,082
Hit-and-Run Crashes — 2023
▲ 19.2% vs prior (908)
Hit-and-run incidents increased from 2022 to 2023 in both volume and rate. The total count of hit-and-run crashes rose from 908 to 1,082. The hit-and-run rate, as a percentage of total crashes, also trended upward, increasing from 19.1% in 2022 to 20.9% in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
7
Motorists Killed
0
Other Killed
68
Pedestrians Injured
25
Cyclists Injured
1,370
Motorists Injured
7
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between the two periods. While Friday remained the peak day for crashes in both years, with counts increasing from 745 to 823, the peak hour for collisions moved later in the day. In 2022, the peak was 2 p.m. (393 crashes), whereas in 2023 it shifted to the 5 p.m. evening commute hour (461 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, the number of fatalities decreased from 15 in 2022 to 7 in 2023. Consequently, the fatal crash rate per 1000 crashes fell from 2.7 to 1.4. In contrast, the count of serious injury crashes rose substantially from 55 to 106, with their share of all crashes increasing from 1.2% in 2022 to 2.0% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors saw shifts in both count and ranking. The count of crashes attributed to 'Failed to yield right of way' increased from 289 to 310, moving it from the third to the second most frequent factor. Conversely, crashes involving 'Followed too closely' decreased in count from 306 to 243, causing it to drop from the second to the third-ranked position year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on wet roads increased in both number and proportion, rising from 616 incidents (12.9% of total) in 2022 to 853 (16.5% of total) in 2023. Regarding lighting, crashes during daylight hours decreased as a share of the total, from 66.6% to 62.9%, while incidents on dark but lighted roadways increased from 1,200 to 1,437.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
Vehicle and person demographics remained largely consistent year-over-year. The top five vehicle makes involved in crashes were identical in both periods: Toyota, Honda, Ford, Nissan, and Chevrolet. The age distribution of persons involved also showed minimal change; for example, the 26-34 age group was the largest cohort in both 2022 and 2023, accounting for 17.4% of individuals in both years.
Top Vehicle Makes (10,179 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
2,215 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (10,165 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes became more concentrated in the 30 mph speed zone, with incidents increasing from 887 in 2022 to 1,018 in 2023. The number of fatal crashes within this specific zone also doubled from 2 to 4. In contrast, crashes in the 65 mph zone decreased from 124 to 117, with fatalities in that zone dropping from 1 to 0.
Fatal crashes by zone: 30 mph: 4 of 1,018 (0.393%) · 50 mph: 1 of 322 (0.311%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: Arcgis_yearly Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: WORCESTER, MA
- Total crash records analyzed: 5,175
- Total persons involved: 12,516
- Total vehicles involved: 10,179
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "WORCESTER, MA Crash Intelligence Report: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/worcester/2023-annual-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved