Monthly Traffic Safety Analysis

58 CRASHES IN
WESTBOROUGH, MA
SEPTEMBER 2023

All metrics benchmarked againstSeptember 2022

Total crashes in WESTBOROUGH, MA decreased by 7.9% from 63 in September 2022 to 58 in September 2023. While overall crash numbers saw a slight reduction, a significant decrease was observed in speeding-related crashes, which dropped from 10 to 2 incidents. Hit-and-run crashes also saw a notable decline, decreasing from 4 to 1.

58

-7.9%was 63

Total Crash Events

0

Persons Killed

15

-6.3%was 16

Persons Injured

1

-75.0%was 4

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a slight decrease in crash incidents year-over-year, with total crashes falling from 63 in September 2022 to 58 in September 2023, representing a 7.9% reduction. Similarly, total injuries decreased by 6.25%, from 16 to 15, over the same period. Fatalities remained at zero for both months.

1

Hit-and-Run Crashes — September 2023

-75.0% vs prior (4)

Hit-and-run crashes saw a significant decrease year-over-year, dropping from 4 incidents in September 2022 to 1 incident in September 2023. Consequently, the hit-and-run rate decreased from 6.3% to 1.7% of total crashes, indicating a downward trend in such incidents.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 0%

12

Motorists Injured

Prior: 16-25.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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 between the two periods. The peak day for crashes moved from Wednesday with 13 incidents in September 2022 to Thursday with 14 incidents in September 2023. The peak hour for crashes also shifted, occurring at 7 PM with 7 incidents in the prior period, and at 2 PM with 8 incidents in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either September 2022 or September 2023. Serious injuries decreased from 2 (3.2% of crashes) in the prior period to 1 (1.7% of crashes) in the current period. Minor injuries also saw a reduction in count from 9 to 5, while possible injuries slightly increased from 2 to 3.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.7%
-50.0%prior 2
Minor Injury5minor injury crashes8.6%
-44.4%prior 9
Possible Injury3possible injury crashes5.2%
50.0%prior 2
No Injury49no injury crashes84.5%
2.1%prior 48

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors saw shifts in their counts year-over-year. Crashes attributed to 'Followed too closely' increased from 10 to 13 (a 30% increase in count), and 'Failed to yield right of way' crashes increased from 6 to 10 (a 66.7% increase in count). Conversely, 'Driving too fast for conditions' saw a substantial decrease in count, from 9 to 2, and 'No improper driving' decreased from 11 to 8 crashes.

Officer-Reported Primary Contributing Cause

Followed too closely13 (22.4%)30.0%prior 10
Inattention12 (20.7%)20.0%prior 10
Failed to yield right of way10 (17.2%)66.7%prior 6
No improper driving8 (13.8%)-27.3%prior 11
Failure to keep in proper lane or running off road3 (5.2%)-40.0%prior 5
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (3.4%)
Driving too fast for conditions2 (3.4%)-77.8%prior 9
Made an improper turn1 (1.7%)
Disregarded traffic signs, signals, road markings1 (1.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions slightly decreased from 42 to 41, while crashes in adverse weather (non-clear) decreased from 20 to 17. Similarly, crashes in daylight conditions decreased from 44 to 42, and those in dark or low light conditions decreased from 19 to 16. The number of crashes on wet road surfaces remained constant at 18 for both periods.

Weather

Clear41 (70.7%)
-2.4%prior 42
Cloudy/Rain9 (15.5%)
Rain5 (8.6%)
-44.4%prior 9
Cloudy2 (3.4%)
-60.0%prior 5
Rain/Cloudy1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Weather condition at time of crash

Lighting

Daylight42 (72.4%)
-4.5%prior 44
Dark - lighted roadway6 (10.3%)
0.0%prior 6
Dark - roadway not lighted4 (6.9%)
-50.0%prior 8
Dusk4 (6.9%)
Dawn2 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Lighting condition field

Road Surface

Dry40 (69.0%)
-11.1%prior 45
Wet18 (31.0%)
0.0%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 119 in September 2022 to 117 in September 2023. Toyota remained a top vehicle make but saw its involvement decrease from 23 to 18 vehicles, while Honda involvement increased from 9 to 13 vehicles. Among persons involved, the 16-20 age group experienced a notable increase from 6 to 14 persons, whereas the 65+ age group saw a decrease from 17 to 8 persons.

Top Vehicle Makes (117 vehicles)

1
TOYOTA18 (15.4%)
-21.7%prior 23
2
HONDA13 (11.1%)
44.4%prior 9
3
FORD12 (10.3%)
-14.3%prior 14
4
JEEP11 (9.4%)
5
NISSAN7 (6%)
40.0%prior 5
6
GMC5 (4.3%)
7
BMW5 (4.3%)
8
MERCEDES-BENZ4 (3.4%)
9
FREIGHTLINER4 (3.4%)
10
CHEVROLET4 (3.4%)
-20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Vehicle unit records

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

Sex Distribution (138 persons with recorded sex)

Male73 (52.9%)
9.0%prior 67
Female65 (47.1%)
-4.4%prior 68

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 65 mph speed zones decreased from 21 to 14, while crashes in 30 mph speed zones increased from 15 to 20. Crashes in 45 mph speed zones also decreased from 10 to 7. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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: 2023-09-01 through 2023-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-09-01 through 2023-09-30 (30 days)
  • Geographic scope: WESTBOROUGH, MA
  • Total crash records analyzed: 58
  • Total persons involved: 143
  • Total vehicles involved: 117

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). "WESTBOROUGH, MA Crash Intelligence Report: September 2023." Published June 21, 2026. Reporting period: 2023-09-01 to 2023-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/westborough/september-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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Westborough, MA Crash Report — September 2023 | ThatCarHitMe.com