Monthly Traffic Safety Analysis

379 CRASHES IN
WORCESTER, MA
JULY 2023

All metrics benchmarked againstJuly 2022

In July 2023, the city of WORCESTER experienced 379 total crashes, a 2.43% increase compared to 370 crashes in July 2022. A notable shift was the 100% decrease in total fatalities, from 4 in July 2022 to 0 in July 2023. Total injuries increased by 33.96%, from 106 to 142.

379

2.4%was 370

Total Crash Events

0

-100.0%was 4

Persons Killed

142

34.0%was 106

Persons Injured

80

11.1%was 72

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash frequency in WORCESTER saw a slight increase, with total crashes rising by 2.43% from 370 in July 2022 to 379 in July 2023. Concurrently, total fatalities decreased significantly by 100%, from 4 to 0, while total injuries increased by 33.96%, from 106 to 142.

80

Hit-and-Run Crashes — July 2023

11.1% vs prior (72)

Hit-and-run crashes increased by 11.11% year-over-year, rising from 72 incidents in July 2022 to 80 in July 2023. Consequently, the hit-and-run rate increased from 19.5% to 21.1% of all crashes, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 4-100.0%

6

Pedestrians Injured

Prior: 3100.0%

3

Cyclists Injured

Prior: 30.0%

133

Motorists Injured

Prior: 9934.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. In July 2022, Friday was the peak day for crashes with 77 incidents, whereas in July 2023, Monday and Wednesday shared the peak with 63 crashes each. The peak crash hour also shifted, moving from 1 PM with 36 crashes in July 2022 to 12 PM and 3 PM with 30 crashes each in July 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes changed significantly, with fatal crashes decreasing by 100% from 3 in July 2022 to 0 in July 2023. Serious injury crashes increased by 180% from 5 to 14, and minor injury crashes increased by 56.76% from 37 to 58. Conversely, possible injury crashes decreased by 15.15% from 33 to 28.

Outcome by Severity (Crash Events)

Serious Injury14serious injury crashes3.7%
180.0%prior 5
Minor Injury58minor injury crashes15.3%
56.8%prior 37
Possible Injury28possible injury crashes7.4%
-15.2%prior 33
No Injury229no injury crashes60.4%
1.8%prior 225

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Most severe injury per crash record

Top Contributing Factors

No improper driving remained the most common contributing factor, increasing by 6.56% from 122 crashes in July 2022 to 130 in July 2023. Crashes attributed to Followed too closely decreased by 29.17% from 24 to 17, while Disregarded traffic signs, signals, road markings increased by 12.5% from 16 to 18. Notably, crashes involving Driving too fast for conditions saw a 400% increase, rising from 1 to 5.

Officer-Reported Primary Contributing Cause

No improper driving130 (34.3%)6.6%prior 122
Disregarded traffic signs, signals, road markings18 (4.7%)12.5%prior 16
Failed to yield right of way18 (4.7%)-10.0%prior 20
Followed too closely17 (4.5%)-29.2%prior 24
Inattention10 (2.6%)-9.1%prior 11
Distracted8 (2.1%)14.3%prior 7
Failure to keep in proper lane or running off road6 (1.6%)-40.0%prior 10
Driving too fast for conditions5 (1.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner5 (1.3%)-44.4%prior 9
Made an improper turn3 (0.8%)-66.7%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in Wet road surface conditions significantly increased by 350%, from 14 in July 2022 to 63 in July 2023. This correlates with a substantial increase in Rain weather conditions, which rose by 480% from 5 to 29. Crashes occurring in Dark - lighted roadway conditions also increased by 39.34%, from 61 to 85.

Weather

Clear227 (61.4%)
-13.4%prior 262
Clear/Clear57 (15.4%)
0.0%prior 57
Rain29 (7.8%)
480.0%prior 5
Cloudy24 (6.5%)
4.3%prior 23
Cloudy/Rain15 (4.1%)
Cloudy/Cloudy3 (0.8%)
Rain/Rain3 (0.8%)
Clear/Cloudy3 (0.8%)
Unknown/Unknown2 (0.5%)
Clear/Rain2 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Weather condition at time of crash

Lighting

Daylight260 (70.1%)
-7.8%prior 282
Dark - lighted roadway85 (22.9%)
39.3%prior 61
Dark - roadway not lighted10 (2.7%)
100.0%prior 5
Dusk7 (1.9%)
16.7%prior 6
Dark - unknown roadway lighting6 (1.6%)
Dawn3 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Lighting condition field

Road Surface

Dry306 (82.9%)
-11.3%prior 345
Wet63 (17.1%)
350.0%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased slightly from 729 to 733. While Toyota, Honda, and Ford remained the top three vehicle makes involved, Nissan saw an 18.6% increase in involvement, rising from 43 to 51. The age group 26-34 experienced a 37.23% increase in persons involved in crashes, from 137 to 188, while the 0-15 age group saw a 26.83% decrease, from 41 to 30.

Top Vehicle Makes (733 vehicles)

1
TOYOTA135 (18.4%)
-6.3%prior 144
2
HONDA89 (12.1%)
-3.3%prior 92
3
FORD70 (9.5%)
-2.8%prior 72
4
NISSAN51 (7%)
18.6%prior 43
5
CHEVROLET46 (6.3%)
-6.1%prior 49
6
SUBARU31 (4.2%)
-8.8%prior 34
7
JEEP29 (4%)
70.6%prior 17
8
HYUNDAI23 (3.1%)
-25.8%prior 31
9
KIA14 (1.9%)
-17.6%prior 17
10
ACURA13 (1.8%)
62.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Vehicle unit records

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

Sex Distribution (730 persons with recorded sex)

Male417 (57.1%)
13.3%prior 368
Female313 (42.9%)
8.7%prior 288

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased by 11.27% from 71 to 79, while crashes in 35 mph zones rose by 33.33% from 9 to 12. Crashes in 65 mph zones also increased by 75%, from 4 to 7. Notably, the single fatal crash in a 65 mph zone in July 2022 was not observed in July 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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: 2023-07-01 through 2023-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-07-01 through 2023-07-31 (31 days)
  • Geographic scope: WORCESTER, MA
  • Total crash records analyzed: 379
  • Total persons involved: 892
  • Total vehicles involved: 733

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: July 2023." Published June 21, 2026. Reporting period: 2023-07-01 to 2023-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/worcester/july-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 — July 2023 | ThatCarHitMe.com