Monthly Traffic Safety Analysis

59 CRASHES IN
SHREWSBURY, MA
FEBRUARY 2025

All metrics benchmarked againstFebruary 2024

Total crashes decreased slightly from 60 in February 2024 to 59 in February 2025, representing a 1.7% reduction. The most notable shift was a significant increase in crashes occurring in 65 mph speed zones, rising from 2 to 8 crashes.

59

-1.7%was 60

Total Crash Events

0

Persons Killed

7

-22.2%was 9

Persons Injured

6

-14.3%was 7

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Shrewsbury experienced a slight decrease year-over-year, falling from 60 crashes in February 2024 to 59 crashes in February 2025. This represents a 1.7% reduction in total crashes for the month.

6

Hit-and-Run Crashes — February 2025

-14.3% vs prior (7)

Hit-and-run crashes decreased from 7 in February 2024 to 6 in February 2025. Consequently, the hit-and-run rate also saw a decrease, falling from 11.7% to 10.2% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 9-22.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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, with the peak day moving from Wednesday in February 2024 (11 crashes) to Thursday in February 2025 (13 crashes). The peak hour also changed significantly, shifting from 8 p.m. (6 crashes) in the prior period to 11 a.m. (9 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

No fatal crashes were recorded in either February 2024 or February 2025. Total injuries decreased from 9 in February 2024 to 7 in February 2025, a 22.2% reduction. Minor injuries increased from 3 to 5, while possible injuries decreased from 4 to 1.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes8.5%
66.7%prior 3
Possible Injury1possible injury crashes1.7%
-75.0%prior 4
No Injury49no injury crashes83.1%
-3.9%prior 51

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Driving too fast for conditions" increased from 0 in February 2024 to 4 in February 2025. Crashes involving "Failed to yield right of way" also saw a substantial increase, rising from 1 to 5. Conversely, crashes attributed to "Followed too closely" decreased from 7 to 3, a 57.1% reduction in count.

Officer-Reported Primary Contributing Cause

No improper driving21 (35.6%)-4.5%prior 22
Inattention5 (8.5%)-16.7%prior 6
Failed to yield right of way5 (8.5%)
Driving too fast for conditions4 (6.8%)
Followed too closely3 (5.1%)-57.1%prior 7
Disregarded traffic signs, signals, road markings1 (1.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.7%)
Visibility obstructed1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 44 in February 2024 to 30 in February 2025, while crashes during snow conditions increased from 2 to 4. On road surfaces, dry condition crashes decreased from 51 to 35, whereas crashes on snow-covered roads increased from 3 to 11, and on wet roads from 2 to 8.

Weather

Clear30 (50.8%)
-31.8%prior 44
Clear/Clear8 (13.6%)
14.3%prior 7
Cloudy5 (8.5%)
Snow4 (6.8%)
Snow/Sleet, hail (freezing rain or drizzle)4 (6.8%)
Snow/Snow2 (3.4%)
Rain/Sleet, hail (freezing rain or drizzle)1 (1.7%)
Rain/Snow1 (1.7%)
Sleet, hail (freezing rain or drizzle)/Rain1 (1.7%)
Rain1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash

Lighting

Daylight40 (69.0%)
14.3%prior 35
Dark - lighted roadway9 (15.5%)
-40.0%prior 15
Dark - roadway not lighted6 (10.3%)
Dawn1 (1.7%)
Dark - unknown roadway lighting1 (1.7%)
Dusk1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field

Road Surface

Dry35 (59.3%)
-31.4%prior 51
Snow11 (18.6%)
Wet8 (13.6%)
Ice3 (5.1%)
Slush2 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 107 in February 2024 to 103 in February 2025. Toyota remained the top make, increasing from 14 to 16 vehicles, while Nissan vehicles involved decreased from 10 to 5. The 0-15 age group saw a decrease in persons involved from 16 to 6, and the 16-20 age group decreased from 19 to 6.

Top Vehicle Makes (103 vehicles)

1
TOYOTA16 (15.5%)
14.3%prior 14
2
FORD12 (11.7%)
20.0%prior 10
3
HONDA10 (9.7%)
42.9%prior 7
4
JEEP9 (8.7%)
-10.0%prior 10
5
CHEVROLET7 (6.8%)
0.0%prior 7
6
SUBARU6 (5.8%)
20.0%prior 5
7
NISSAN5 (4.9%)
-50.0%prior 10
8
MERCEDES-BENZ4 (3.9%)
9
BMW4 (3.9%)
10
KIA4 (3.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records

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

Sex Distribution (112 persons with recorded sex)

Male63 (56.3%)
-21.3%prior 80
Female49 (43.8%)
-14.0%prior 57

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 65 mph speed zones increased significantly from 2 in February 2024 to 8 in February 2025. Meanwhile, crashes in 40 mph zones decreased from 10 to 7. Crashes in 30 mph zones slightly increased from 6 to 7.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-02-01 through 2025-02-28 (28 days)
  • Geographic scope: SHREWSBURY, MA
  • Total crash records analyzed: 59
  • Total persons involved: 123
  • Total vehicles involved: 103

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: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/shrewsbury/february-2025-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 — February 2025 | ThatCarHitMe.com