Monthly Traffic Safety Analysis

35 CRASHES IN
STURBRIDGE, MA
JANUARY 2025

All metrics benchmarked againstJanuary 2024

In January 2025, STURBRIDGE, MA experienced a significant decrease in total crashes, falling by 38.6% from 57 crashes in January 2024 to 35 crashes. This period saw a notable reduction in speeding-related crashes, which dropped from 22 to 6. Total injuries also decreased by 60.7%, from 28 to 11, with no fatalities reported in either period.

35

-38.6%was 57

Total Crash Events

0

Persons Killed

11

-60.7%was 28

Persons Injured

0

-100.0%was 1

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 · 2025-01-01 to 2025-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in STURBRIDGE, MA showed a downward trend in January 2025 compared to the previous year. Total crashes decreased by 38.6%, from 57 to 35, while total injuries fell by 60.7%, from 28 to 11. Fatalities remained at zero in both periods, indicating a general improvement in safety outcomes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

11

Motorists Injured

Prior: 28-60.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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; January 2024's peak day was Sunday with 18 crashes, whereas January 2025's peak day moved to Saturday with 9 crashes. Similarly, the peak crash hour shifted from 5 PM (8 crashes) in January 2024 to 6 PM (5 crashes) in January 2025. Crashes on Sundays saw a substantial decrease from 18 to 3, while Saturday crashes increased from 3 to 9.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity distributions changed, with no fatalities in either period. Serious injury (A) crashes, which were absent in January 2024, accounted for 2 crashes (5.7% share) in January 2025. Minor injury (B) crashes decreased from 10 (17.5% share) to 3 (8.6% share), and possible injury (C) crashes decreased from 6 (10.5% share) to 2 (5.7% share).

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes5.7%
Minor Injury3minor injury crashes8.6%
-70.0%prior 10
Possible Injury2possible injury crashes5.7%
-66.7%prior 6
No Injury27no injury crashes77.1%
-34.1%prior 41

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record

Top Contributing Factors

Contributing factors saw shifts, with 'Driving too fast for conditions' decreasing significantly from 16 crashes in January 2024 to 5 crashes in January 2025. 'No improper driving' crashes also decreased from 14 to 8 crashes year-over-year. 'Followed too closely' remained constant at 5 crashes in both periods, while 'Exceeded authorized speed limit' decreased from 4 to 1 crash.

Officer-Reported Primary Contributing Cause

No improper driving8 (22.9%)-42.9%prior 14
Driving too fast for conditions5 (14.3%)-68.8%prior 16
Followed too closely5 (14.3%)0.0%prior 5
Failed to yield right of way3 (8.6%)
Inattention3 (8.6%)
Over-correcting/over-steering2 (5.7%)
Failure to keep in proper lane or running off road2 (5.7%)
Distracted1 (2.9%)
Exceeded authorized speed limit1 (2.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Adverse weather conditions contributed to fewer crashes in January 2025 compared to the prior year. Crashes during 'Snow' weather decreased from 20 to 5, and crashes on 'Snow' road surfaces decreased from 22 to 9. Conversely, crashes in 'Clear' weather increased from 20 to 22, and on 'Dry' road surfaces increased from 17 to 26, despite an overall reduction in total crashes.

Weather

Clear22 (62.9%)
10.0%prior 20
Snow5 (14.3%)
-75.0%prior 20
Clear/Clear3 (8.6%)
Other1 (2.9%)
Snow/Blowing sand, snow1 (2.9%)
Snow/Cloudy1 (2.9%)
Clear/Severe crosswinds1 (2.9%)
Cloudy/Snow1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash

Lighting

Daylight17 (48.6%)
-39.3%prior 28
Dark - lighted roadway9 (25.7%)
-35.7%prior 14
Dawn4 (11.4%)
Dark - roadway not lighted3 (8.6%)
-80.0%prior 15
Dusk2 (5.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field

Road Surface

Dry26 (74.3%)
52.9%prior 17
Snow9 (25.7%)
-59.1%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 86 in January 2024 to 54 in January 2025. The top vehicle make involved shifted, with TOYOTA being most frequent in January 2024 (13 vehicles) and FORD in January 2025 (8 vehicles). All age groups saw a decrease in persons involved, with the 16-20 age group experiencing the largest drop from 25 to 7 persons.

Top Vehicle Makes (54 vehicles)

1
FORD8 (14.8%)
-27.3%prior 11
2
HYUNDAI6 (11.1%)
3
SUBARU6 (11.1%)
-14.3%prior 7
4
HONDA4 (7.4%)
-50.0%prior 8
5
CHEVROLET4 (7.4%)
-20.0%prior 5
6
NISSAN3 (5.6%)
-57.1%prior 7
7
JEEP3 (5.6%)
8
TOYOTA3 (5.6%)
-76.9%prior 13
9
MERCEDES-BENZ2 (3.7%)
10
RAM2 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records

Sex Distribution (66 persons with recorded sex)

Male45 (68.2%)
-35.7%prior 70
Female21 (31.8%)
-52.3%prior 44

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone decreased substantially from 18 in January 2024 to 8 in January 2025. Crashes in the 40 mph zone also saw a significant reduction, falling from 10 to 2. The 30 mph zone experienced a decrease from 12 to 8 crashes, while the 50 mph zone saw a slight increase from 4 to 5 crashes. No fatal crashes were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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: 2025-01-01 through 2025-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-01-31 (31 days)
  • Geographic scope: STURBRIDGE, MA
  • Total crash records analyzed: 35
  • Total persons involved: 67
  • Total vehicles involved: 54

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). "STURBRIDGE, MA Crash Intelligence Report: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/sturbridge/january-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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Sturbridge, MA Crash Report — January 2025 | ThatCarHitMe.com