Monthly Traffic Safety Analysis

60 CRASHES IN
SHREWSBURY, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

In October 2023, Shrewsbury experienced 60 crashes, a 14.3% decrease compared to the 70 crashes recorded in October 2022. The most notable year-over-year shift was the absence of fatalities in October 2023, down from one fatality in the prior year. Total injuries also decreased from 15 to 12 over the same period.

60

-14.3%was 70

Total Crash Events

0

-100.0%was 1

Persons Killed

12

-20.0%was 15

Persons Injured

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crash incidents year-over-year for October. Total crashes fell by 10, representing a 14.3% reduction, while total injuries decreased by 3, a 20% drop. Fatalities saw a 100% reduction, moving from one in October 2022 to zero in October 2023.

4

Hit-and-Run Crashes — October 2023

0.0% vs prior (4)

The number of hit-and-run crashes remained constant at 4 in both October 2022 and October 2023. However, due to a decrease in overall crashes, the hit-and-run rate slightly increased from 5.7% in October 2022 to 6.7% in October 2023.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

12

Motorists Injured

Prior: 15-20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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 slightly, with both Thursday and Monday recording the highest number of crashes at 11 in October 2023, whereas Thursday and Tuesday were the peak days with 15 crashes each in October 2022. The peak hour for crashes shifted from 5 PM with 8 crashes in October 2022 to 4 PM with 11 crashes in October 2023. Crashes on Tuesdays decreased significantly from 15 to 9.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution saw a positive change, with no fatal crashes in October 2023 compared to one fatal crash (1.4% of total crashes) in October 2022. Minor injury crashes decreased from 8 (11.4% share) to 4 (6.7% share), while possible injury crashes increased from 3 (4.3% share) to 5 (8.3% share). Additionally, crashes resulting in no injury increased from 77.1% to 81.7% of all crashes.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.7%
Minor Injury4minor injury crashes6.7%
-50.0%prior 8
Possible Injury5possible injury crashes8.3%
66.7%prior 3
No Injury49no injury crashes81.7%
-9.3%prior 54

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' decreased by 6 crashes, from 20 to 14. 'Inattention' crashes increased by 5, from 4 to 9, moving from the third most common factor to the second. 'Followed too closely' also saw a notable increase of 6 crashes, from 2 to 8, rising in rank from sixth to third.

Officer-Reported Primary Contributing Cause

No improper driving14 (23.3%)-30.0%prior 20
Inattention9 (15%)
Followed too closely8 (13.3%)
Failed to yield right of way6 (10%)-25.0%prior 8
Disregarded traffic signs, signals, road markings4 (6.7%)
Failure to keep in proper lane or running off road3 (5%)
Glare1 (1.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.7%)
Visibility obstructed1 (1.7%)
Exceeded authorized speed limit1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in clear weather increased from 55.7% (39 crashes) in October 2022 to 73.3% (44 crashes) in October 2023, while crashes in adverse weather conditions like rain decreased. Crashes on wet road surfaces saw a significant reduction, dropping from 22 (31.4% of total) to 10 (16.7% of total). The proportion of crashes occurring during daylight hours slightly decreased from 70% to 65%.

Weather

Clear44 (73.3%)
12.8%prior 39
Cloudy5 (8.3%)
0.0%prior 5
Cloudy/Rain3 (5.0%)
-62.5%prior 8
Clear/Cloudy2 (3.3%)
Rain/Cloudy2 (3.3%)
Rain1 (1.7%)
-83.3%prior 6
Cloudy/Cloudy1 (1.7%)
Clear/Rain1 (1.7%)
Clear/Clear1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight39 (65.0%)
-20.4%prior 49
Dark - lighted roadway11 (18.3%)
-21.4%prior 14
Dusk5 (8.3%)
Dark - unknown roadway lighting2 (3.3%)
Dawn2 (3.3%)
Dark - roadway not lighted1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry49 (83.1%)
2.1%prior 48
Wet10 (16.9%)
-54.5%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

Toyota remained the most frequently involved make with 21 vehicles in both periods. Honda increased its involvement from 11 vehicles to 16, while Chevrolet decreased from 16 to 5. In terms of age distribution among persons involved, the 45-54 age group saw a decrease from 29 to 16 individuals, and the 65+ age group increased from 12 to 19 individuals.

Top Vehicle Makes (113 vehicles)

1
TOYOTA21 (18.6%)
0.0%prior 21
2
HONDA16 (14.2%)
45.5%prior 11
3
FORD10 (8.8%)
-28.6%prior 14
4
NISSAN9 (8%)
50.0%prior 6
5
JEEP8 (7.1%)
60.0%prior 5
6
SUBARU5 (4.4%)
-54.5%prior 11
7
CHEVROLET5 (4.4%)
-68.8%prior 16
8
HYUNDAI4 (3.5%)
9
MAZDA4 (3.5%)
-20.0%prior 5
10
VOLKSWAGEN3 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

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

Sex Distribution (134 persons with recorded sex)

Male75 (56.0%)
-11.8%prior 85
Female59 (44.0%)
-14.5%prior 69

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 8 to 5, and in the 35 mph zone from 3 to 1. Conversely, crashes in the 40 mph zone increased from 7 to 9. Notably, the single fatal crash in October 2022 occurred in a 55 mph zone, a speed zone that had no recorded crashes in October 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: SHREWSBURY, MA
  • Total crash records analyzed: 60
  • Total persons involved: 137
  • Total vehicles involved: 113

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). "SHREWSBURY, MA Crash Intelligence Report: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/shrewsbury/october-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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Shrewsbury, MA Crash Report — October 2023 | ThatCarHitMe.com