Monthly Traffic Safety Analysis

65 CRASHES IN
SHREWSBURY, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

Total crashes in Shrewsbury increased by 27.45%, from 51 in September 2023 to 65 in September 2024. The most notable year-over-year shift was a 100% decrease in total fatalities, from 1 in the prior period to 0 in the current period. This occurred despite an increase in overall crash incidents and injuries.

65

27.5%was 51

Total Crash Events

0

-100.0%was 1

Persons Killed

16

77.8%was 9

Persons Injured

6

200.0%was 2

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a rise in crash incidents year-over-year, with total crashes increasing by 14, representing a 27.45% increase. Conversely, total fatalities decreased by 1, marking a 100% reduction.

6

Hit-and-Run Crashes — September 2024

200.0% vs prior (2)

Hit-and-run crashes increased by 4, from 2 in September 2023 to 6 in September 2024. This resulted in the hit-and-run rate rising from 3.9% of all crashes in the prior period to 9.2% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 977.8%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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 Friday with 12 incidents in September 2023 to Saturday with 17 incidents in September 2024. The peak hour for crashes also changed, moving from 5 PM with 10 incidents in the prior period to 3 PM with 7 incidents in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased by 100%, with 0 fatalities reported in September 2024 compared to 1 in September 2023. Total injuries increased by 77.78%, from 9 in the prior period to 16 in the current period. The share of crashes resulting in minor injuries rose from 7.8% to 12.3%, and possible injuries from 7.8% to 9.2%.

Outcome by Severity (Crash Events)

Minor Injury8minor injury crashes12.3%
100.0%prior 4
Possible Injury6possible injury crashes9.2%
50.0%prior 4
No Injury49no injury crashes75.4%
19.5%prior 41

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

The number of crashes attributed to 'No improper driving' increased significantly from 8 in the prior period to 19 in the current period, a change of 11 crashes. Crashes due to 'Failed to yield right of way' increased by 4, from 3 to 7, while 'Inattention' increased by 2, from 5 to 7. 'Followed too closely' remained constant at 9 crashes in both periods.

Officer-Reported Primary Contributing Cause

No improper driving19 (29.2%)137.5%prior 8
Followed too closely9 (13.8%)0.0%prior 9
Inattention7 (10.8%)40.0%prior 5
Failed to yield right of way7 (10.8%)
Physical impairment3 (4.6%)
Made an improper turn2 (3.1%)
Disregarded traffic signs, signals, road markings2 (3.1%)
Other improper action2 (3.1%)
Over-correcting/over-steering2 (3.1%)
Distracted1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions (including Clear/Clear) increased from 37 in the prior period to 54 in the current period. Conversely, crashes in rainy conditions (including Cloudy/Rain, Rain/Rain, Rain/Cloudy) decreased from 12 to 6. Crashes on dry road surfaces increased from 37 to 57, while those on wet surfaces decreased from 14 to 5.

Weather

Clear36 (55.4%)
0.0%prior 36
Clear/Clear18 (27.7%)
Cloudy4 (6.2%)
Cloudy/Rain3 (4.6%)
-50.0%prior 6
Rain/Rain3 (4.6%)
Cloudy/Cloudy1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight50 (76.9%)
31.6%prior 38
Dark - lighted roadway8 (12.3%)
0.0%prior 8
Dark - roadway not lighted4 (6.2%)
Dawn2 (3.1%)
Dusk1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry57 (89.1%)
54.1%prior 37
Wet5 (7.8%)
-64.3%prior 14
Ice1 (1.6%)
Other1 (1.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 25, from 97 to 122. Toyota saw a substantial increase in involvement, from 13 vehicles in the prior period to 31 in the current period, becoming the top make. The 21-25, 26-34, 35-44, and 55-64 age groups all saw increases in person involvement, with the 21-25 age group increasing from 10 to 24 persons and the 35-44 age group increasing from 19 to 31 persons. The number of females involved in crashes increased from 47 to 70.

Top Vehicle Makes (122 vehicles)

1
TOYOTA31 (25.4%)
138.5%prior 13
2
HONDA13 (10.7%)
0.0%prior 13
3
FORD12 (9.8%)
71.4%prior 7
4
NISSAN9 (7.4%)
12.5%prior 8
5
SUBARU7 (5.7%)
-12.5%prior 8
6
HYUNDAI6 (4.9%)
7
BMW6 (4.9%)
8
KIA4 (3.3%)
9
JEEP4 (3.3%)
-42.9%prior 7
10
MERCEDES-BENZ4 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

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

Sex Distribution (144 persons with recorded sex)

Male74 (51.4%)
1.4%prior 73
Female70 (48.6%)
48.9%prior 47

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph zones increased from 4 to 7, and in 35 mph zones from 3 to 5. Crashes in 40 mph zones decreased from 9 to 5, while 45 mph zones saw an increase from 4 to 6 crashes. The number of crashes in 65 mph zones remained stable at 4 for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: SHREWSBURY, MA
  • Total crash records analyzed: 65
  • Total persons involved: 162
  • Total vehicles involved: 122

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 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/shrewsbury/september-2024-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 2024 | ThatCarHitMe.com