Monthly Traffic Safety Analysis

51 CRASHES IN
SHREWSBURY, MA
SEPTEMBER 2023

All metrics benchmarked againstSeptember 2022

In September 2023, SHREWSBURY experienced a decrease in total crashes, with 51 incidents compared to 64 in September 2022, representing a 20.31% reduction. Total injuries saw a substantial decline, dropping by 60.87% from 23 to 9. This period also saw a notable shift in contributing factors, with 'Followed too closely' crashes increasing by 350% from 2 to 9 incidents.

51

-20.3%was 64

Total Crash Events

1

Persons Killed

9

-60.9%was 23

Persons Injured

2

-50.0%was 4

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2023-09-01 to 2023-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash data for September 2023 indicates a declining trend year-over-year, with total crashes decreasing by 20.31% from 64 to 51. Fatalities remained stable at 1 in both periods. Total injuries significantly decreased by 60.87%, falling from 23 in September 2022 to 9 in September 2023.

2

Hit-and-Run Crashes — September 2023

-50.0% vs prior (4)

Hit-and-run crashes decreased by 50% year-over-year, falling from 4 incidents in September 2022 to 2 in September 2023. Consequently, the hit-and-run rate decreased from 6.3% to 3.9% of total crashes.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Motorists Killed

Prior: 1-100.0%

0

Pedestrians Injured

Prior: 00.0%

9

Motorists Injured

Prior: 23-60.9%

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 patterns for crashes shifted between the two periods. In September 2023, the peak day for crashes was Friday with 12 incidents, a change from September 2022 where Sunday was the peak day with 15 crashes. The peak hour also shifted from 6 p.m. with 8 crashes in the prior period to 5 p.m. with 10 crashes 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

The fatal crash rate slightly increased from 1.56% in September 2022 to 1.96% in September 2023, with 1 fatal crash recorded in both periods. Crashes resulting in possible injury decreased notably from 11 (17.2% of total crashes) to 4 (7.8% of total crashes). Minor injury crashes maintained the same proportion of total crashes at 7.8% in both periods.

Outcome by Severity (Crash Events)

Fatal1fatal crashes2%
0.0%prior 1
Minor Injury4minor injury crashes7.8%
-20.0%prior 5
Possible Injury4possible injury crashes7.8%
-63.6%prior 11
No Injury41no injury crashes80.4%
-12.8%prior 47

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

Among contributing factors, 'Followed too closely' crashes increased significantly from 2 in the prior period to 9 in the current period, a 350% increase in count. Conversely, crashes attributed to 'No improper driving' decreased by 42.86% from 14 to 8 incidents. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' also saw a substantial decrease in count, falling by 80% from 5 to 1 crash.

Officer-Reported Primary Contributing Cause

Followed too closely9 (17.6%)
No improper driving8 (15.7%)-42.9%prior 14
Inattention5 (9.8%)
Disregarded traffic signs, signals, road markings3 (5.9%)
Distracted3 (5.9%)
Failed to yield right of way3 (5.9%)-40.0%prior 5
Failure to keep in proper lane or running off road2 (3.9%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (3.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2%)-80.0%prior 5
Over-correcting/over-steering1 (2%)

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

The number of crashes occurring in 'Daylight' conditions decreased from 42 to 38 year-over-year. Crashes under 'Dark - lighted roadway' conditions also decreased from 13 to 8. There was a slight increase in crashes on 'Wet' road surfaces, rising from 11 to 14 incidents.

Weather

Clear36 (70.6%)
-10.0%prior 40
Cloudy/Rain6 (11.8%)
Rain5 (9.8%)
0.0%prior 5
Cloudy2 (3.9%)
-60.0%prior 5
Clear/Clear1 (2.0%)
-88.9%prior 9
Rain/Cloudy1 (2.0%)

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

Lighting

Daylight38 (74.5%)
-9.5%prior 42
Dark - lighted roadway8 (15.7%)
-38.5%prior 13
Dark - roadway not lighted2 (3.9%)
Dark - unknown roadway lighting2 (3.9%)
Dawn1 (2.0%)

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

Road Surface

Dry37 (72.5%)
-27.5%prior 51
Wet14 (27.5%)
27.3%prior 11

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 115 to 97 year-over-year. Among top vehicle makes, TOYOTA saw a decrease in involvement from 23 to 13 vehicles, while JEEP involvement increased from 2 to 7 vehicles. The age group 45-54 experienced the largest decrease in persons involved, dropping from 29 to 19, and female involvement decreased from 70 to 47 persons.

Top Vehicle Makes (97 vehicles)

1
HONDA13 (13.4%)
-7.1%prior 14
2
TOYOTA13 (13.4%)
-43.5%prior 23
3
SUBARU8 (8.2%)
14.3%prior 7
4
NISSAN8 (8.2%)
33.3%prior 6
5
JEEP7 (7.2%)
6
FORD7 (7.2%)
16.7%prior 6
7
VOLKSWAGEN3 (3.1%)
8
CHEVROLET3 (3.1%)
-40.0%prior 5
9
GMC3 (3.1%)
10
KIA3 (3.1%)

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

Sex Distribution (120 persons with recorded sex)

Male73 (60.8%)
-6.4%prior 78
Female47 (39.2%)
-32.9%prior 70

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 40 mph speed zones increased from 6 to 9 incidents year-over-year. Conversely, crashes in 45 mph zones decreased from 8 to 4, and those in 65 mph zones decreased from 7 to 4. In the prior period, 1 fatal crash occurred in a 30 mph zone, whereas no fatal crashes were recorded within the listed speed zones in the current 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: SHREWSBURY, MA
  • Total crash records analyzed: 51
  • Total persons involved: 123
  • Total vehicles involved: 97

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: 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/shrewsbury/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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Shrewsbury, MA Crash Report — September 2023 | ThatCarHitMe.com