Monthly Traffic Safety Analysis

404 CRASHES IN
WORCESTER, MA
JUNE 2023

All metrics benchmarked againstJune 2022

In June 2023, Worcester experienced 404 crashes, an increase of 9.78% from the 368 crashes reported in June 2022. Despite this rise in overall incidents, total injuries decreased by 27.4%, falling from 124 to 90. A notable year-over-year shift was the 100% increase in DUI-related crashes, rising from 2 to 4.

404

9.8%was 368

Total Crash Events

0

-100.0%was 1

Persons Killed

90

-27.4%was 124

Persons Injured

68

13.3%was 60

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. 68 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Worcester increased by 9.78% year-over-year, with 404 crashes in June 2023 compared to 368 in June 2022. Concurrently, total injuries saw a decrease of 27.4%, falling from 124 to 90. The city also saw a reduction in fatalities, from one in June 2022 to zero in June 2023.

68

Hit-and-Run Crashes — June 2023

13.3% vs prior (60)

Hit-and-run crashes increased by 8 incidents, from 60 in June 2022 to 68 in June 2023, representing a 13.3% rise. The hit-and-run rate also saw a slight increase, moving from 16.3% of total crashes in the prior period to 16.8% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

7

Pedestrians Injured

Prior: 2250.0%

2

Cyclists Injured

Prior: 3-33.3%

80

Motorists Injured

Prior: 119-32.8%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Wednesday in June 2022, which had 75 crashes, to Friday in June 2023, which recorded 82 crashes. Crashes on Wednesday decreased by 29.3%, from 75 to 53, while Friday crashes increased by 43.8%, from 57 to 82. The peak crash hour remained 4 PM in both periods, though the count decreased from 40 crashes in June 2022 to 34 crashes in June 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities decreased from 1 in June 2022 to 0 in June 2023, with no fatal crashes reported in the current period compared to 1 prior. While minor injuries decreased by 20.4% (from 54 to 43) and possible injuries decreased by 12.1% (from 33 to 29), serious injuries saw a 300% increase, rising from 2 to 8. The proportion of crashes resulting in no injury increased from 59.8% to 63.4%.

Outcome by Severity (Crash Events)

Serious Injury8serious injury crashes2%
300.0%prior 2
Minor Injury43minor injury crashes10.6%
-20.4%prior 54
Possible Injury29possible injury crashes7.2%
-12.1%prior 33
No Injury256no injury crashes63.4%
16.4%prior 220

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record

Top Contributing Factors

The most frequently cited contributing factor, 'No improper driving', increased by 10 crashes, from 129 to 139, representing a 7.75% rise. Conversely, 'Failed to yield right of way' crashes decreased by 12, from 32 to 20, a 37.5% reduction, and 'Followed too closely' incidents dropped by 13, from 29 to 16, a 44.8% decrease. Factors like 'Disregarded traffic signs, signals, road markings' and 'Inattention' increased significantly, by 66.7% (from 9 to 15) and 85.7% (from 7 to 13) respectively.

Officer-Reported Primary Contributing Cause

No improper driving139 (34.4%)7.8%prior 129
Failed to yield right of way20 (5%)-37.5%prior 32
Followed too closely16 (4%)-44.8%prior 29
Disregarded traffic signs, signals, road markings15 (3.7%)66.7%prior 9
Inattention13 (3.2%)85.7%prior 7
Made an improper turn8 (2%)
Failure to keep in proper lane or running off road6 (1.5%)-33.3%prior 9
Distracted6 (1.5%)
Other improper action6 (1.5%)
Fatigued/asleep5 (1.2%)0.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 302 in June 2022 to 273 in June 2023. Conversely, crashes during rainy conditions increased substantially, from 13 to 58 year-over-year. The number of crashes on wet road surfaces saw a significant increase of 47 incidents, rising from 21 to 68, while crashes on dry surfaces decreased by 16, from 337 to 321.

Weather

Clear214 (54.3%)
-13.7%prior 248
Clear/Clear59 (15.0%)
9.3%prior 54
Cloudy53 (13.5%)
82.8%prior 29
Cloudy/Rain25 (6.3%)
400.0%prior 5
Rain23 (5.8%)
Rain/Cloudy4 (1.0%)
Clear/Rain3 (0.8%)
Cloudy/Clear3 (0.8%)
Cloudy/Cloudy3 (0.8%)
Rain/Rain3 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash

Lighting

Daylight303 (76.9%)
12.6%prior 269
Dark - lighted roadway70 (17.8%)
-5.4%prior 74
Dark - roadway not lighted8 (2.0%)
Dusk6 (1.5%)
-25.0%prior 8
Dawn4 (1.0%)
Dark - unknown roadway lighting3 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field

Road Surface

Dry321 (81.7%)
-4.7%prior 337
Wet68 (17.3%)
223.8%prior 21
Reported but invalid2 (0.5%)
Snow1 (0.3%)
Other1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 7.32%, from 724 to 777. Analysis of person age distribution shows increases in crashes involving individuals aged 16-20 (from 68 to 89), 35-44 (from 116 to 147), and 65+ (from 59 to 85). Regarding vehicle makes, Toyota remained the most common, increasing from 139 to 149, while Nissan and Subaru vehicles involved in crashes saw notable increases of 51.2% (from 43 to 65) and 51.7% (from 29 to 44), respectively.

Top Vehicle Makes (777 vehicles)

1
TOYOTA149 (19.2%)
7.2%prior 139
2
HONDA85 (10.9%)
3.7%prior 82
3
FORD65 (8.4%)
-4.4%prior 68
4
NISSAN65 (8.4%)
51.2%prior 43
5
SUBARU44 (5.7%)
51.7%prior 29
6
CHEVROLET44 (5.7%)
-8.3%prior 48
7
JEEP39 (5%)
14.7%prior 34
8
HYUNDAI30 (3.9%)
20.0%prior 25
9
GMC17 (2.2%)
112.5%prior 8
10
LEXUS16 (2.1%)
166.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records

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

Sex Distribution (812 persons with recorded sex)

Male438 (53.9%)
16.5%prior 376
Female373 (45.9%)
15.8%prior 322
X / Unspecified1 (0.1%)
0.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes reported with a specified speed limit decreased slightly from 125 in June 2022 to 118 in June 2023. Crashes occurring in 30 mph zones decreased by 12.7%, from 71 to 62, while those in 50 mph zones increased by 15.4%, from 26 to 30. No fatal crashes were recorded within any specified speed limit zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-06-01 through 2023-06-30 (30 days)
  • Geographic scope: WORCESTER, MA
  • Total crash records analyzed: 404
  • Total persons involved: 960
  • Total vehicles involved: 777

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: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/worcester/june-2023-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 — June 2023 | ThatCarHitMe.com