Monthly Traffic Safety Analysis

406 CRASHES IN
WORCESTER, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, WORCESTER, MA experienced 406 crashes, a notable decrease from the 516 crashes recorded in November 2024. This represents a 21.3% reduction in total crashes year-over-year. The most significant shift was a 30.5% decrease in total injuries, falling from 174 to 121.

406

-21.3%was 516

Total Crash Events

0

Persons Killed

121

-30.5%was 174

Persons Injured

75

-23.5%was 98

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 30 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in WORCESTER, MA are trending downwards, with a substantial decrease of 110 crashes from 516 in November 2024 to 406 in November 2025. This marks a 21.3% reduction in total crash incidents year-over-year. Similarly, total injuries saw a significant decline, decreasing by 53, or 30.5%, over the same period.

75

Hit-and-Run Crashes — November 2025

-23.5% vs prior (98)

Hit-and-run crashes decreased from 98 in November 2024 to 75 in November 2025, a reduction of 23 incidents. The hit-and-run crash rate also slightly declined from 19% in the prior period to 18.5% in the current period, indicating a marginal downward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

10

Pedestrians Injured

Prior: 16-37.5%

6

Cyclists Injured

Prior: 60.0%

104

Motorists Injured

Prior: 151-31.1%

1

Other Injured

Prior: 10.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year, with the peak day moving from Friday, which had 95 crashes in the prior period, to Wednesday, with 73 crashes in the current period. The peak hour for crashes also changed, shifting from 5 PM with 55 crashes in November 2024 to 6 PM with 38 crashes in November 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both November 2024 and November 2025, indicating no change in the fatal crash rate. However, total injuries decreased by 30.5%, from 174 to 121, year-over-year. Serious injuries fell from 11 to 9, minor injuries from 70 to 53, and possible injuries from 47 to 30, while the share of no-injury crashes increased from 66.5% to 70%.

Outcome by Severity (Crash Events)

Serious Injury9serious injury crashes2.2%
-18.2%prior 11
Minor Injury53minor injury crashes13.1%
-24.3%prior 70
Possible Injury30possible injury crashes7.4%
-36.2%prior 47
No Injury284no injury crashes70%
-17.2%prior 343

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' decreased by 50 crashes, from 198 to 148, a 25.3% reduction in count. Conversely, 'Failed to yield right of way' crashes increased by 13, from 18 to 31, marking a 72.2% increase in count. Crashes attributed to 'Inattention' also saw a significant decrease, falling by 10 from 21 to 11, a 47.6% reduction in count.

Officer-Reported Primary Contributing Cause

No improper driving148 (36.5%)-25.3%prior 198
Failed to yield right of way31 (7.6%)72.2%prior 18
Followed too closely29 (7.1%)11.5%prior 26
Disregarded traffic signs, signals, road markings18 (4.4%)-28.0%prior 25
Failure to keep in proper lane or running off road13 (3.2%)8.3%prior 12
Inattention11 (2.7%)-47.6%prior 21
Made an improper turn6 (1.5%)-14.3%prior 7
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner5 (1.2%)
Exceeded authorized speed limit5 (1.2%)-28.6%prior 7
Wrong side or wrong way4 (1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 312 in the prior period to 218 in the current period, a reduction of 94 crashes. Similarly, crashes on dry road surfaces fell by 66, from 408 to 342, and crashes on wet road surfaces decreased by 34, from 85 to 51. Crashes in daylight conditions also saw a decrease, dropping from 289 to 207.

Weather

Clear218 (55.1%)
-30.1%prior 312
Clear/Clear74 (18.7%)
-12.9%prior 85
Cloudy38 (9.6%)
35.7%prior 28
Rain31 (7.8%)
-6.1%prior 33
Clear/Cloudy13 (3.3%)
160.0%prior 5
Cloudy/Cloudy8 (2.0%)
Clear/Unknown3 (0.8%)
Rain/Rain3 (0.8%)
-72.7%prior 11
Rain/Cloudy2 (0.5%)
-66.7%prior 6
Cloudy/Clear2 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Daylight207 (52.4%)
-28.4%prior 289
Dark - lighted roadway162 (41.0%)
-10.0%prior 180
Dusk13 (3.3%)
-23.5%prior 17
Dark - roadway not lighted8 (2.0%)
60.0%prior 5
Dark - unknown roadway lighting4 (1.0%)
Dawn1 (0.3%)
-88.9%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry342 (86.8%)
-16.2%prior 408
Wet51 (12.9%)
-40.0%prior 85
Sand, mud, dirt, oil, gravel1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased by 237, from 1035 in November 2024 to 798 in November 2025. Among top vehicle makes, TOYOTA involvement decreased by 42 (from 211 to 169), HONDA by 45 (from 138 to 93), and FORD by 14 (from 93 to 79). All age groups saw a reduction in person involvement, with the 26-34 age group experiencing the largest decrease of 64 persons, from 220 to 156.

Top Vehicle Makes (798 vehicles)

1
TOYOTA169 (21.2%)
-19.9%prior 211
2
HONDA93 (11.7%)
-32.6%prior 138
3
FORD79 (9.9%)
-15.1%prior 93
4
CHEVROLET59 (7.4%)
20.4%prior 49
5
NISSAN44 (5.5%)
-32.3%prior 65
6
SUBARU38 (4.8%)
-24.0%prior 50
7
JEEP32 (4%)
-25.6%prior 43
8
HYUNDAI22 (2.8%)
-51.1%prior 45
9
VOLKSWAGEN17 (2.1%)
88.9%prior 9
10
MERCEDES-BENZ15 (1.9%)
-37.5%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

177 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (791 persons with recorded sex)

Male464 (58.7%)
-19.3%prior 575
Female324 (41.0%)
-32.9%prior 483
X / Unspecified3 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones saw a substantial increase, rising from 132 in November 2024 to 311 in November 2025, an increase of 179 crashes. Conversely, crashes in 30 mph zones decreased significantly by 236, from 263 to 27. All speed zones continued to report zero fatal crashes in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-11-01 through 2025-11-30 (30 days)
  • Geographic scope: WORCESTER, MA
  • Total crash records analyzed: 406
  • Total persons involved: 966
  • Total vehicles involved: 798

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: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/worcester/november-2025-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

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Worcester, MA Crash Report — November 2025 | ThatCarHitMe.com