Yearly Traffic Safety Analysis

411 CRASHES IN
STURBRIDGE, MA
2025

All metrics benchmarked against2024

In 2025, Sturbridge recorded 411 total vehicle crashes, a 13.3% decrease from the 474 crashes in 2024. Despite the overall decline in collisions, the most significant year-over-year change was the emergence of fatal incidents, with four fatalities recorded in 2025 compared to zero in the prior year.

411

-13.3%was 474

Total Crash Events

4

Persons Killed

184

6.4%was 173

Persons Injured

17

13.3%was 15

Hit-and-Run Crashes

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 5 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic collisions in Sturbridge are trending downward, with total crashes falling by 13.3% from 474 to 411. However, the severity of these crashes has increased. Total injuries rose by 6.4% from 173 to 184, and the number of fatalities increased from zero to four.

17

Hit-and-Run Crashes — 2025

13.3% vs prior (15)

The number of hit-and-run incidents increased from 15 in 2024 to 17 in 2025. As a percentage of total collisions, the hit-and-run rate also trended upward, rising from 3.2% to 4.1% year-over-year. This indicates a slight increase in both the absolute count and the relative frequency of these events.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

4

Motorists Killed

Prior: 0%

4

Pedestrians Injured

Prior: 1300.0%

3

Cyclists Injured

Prior: 250.0%

177

Motorists Injured

Prior: 1704.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained consistent year-over-year. Friday was the peak day for crashes in both 2025 and 2024, with 77 incidents recorded in each period. Similarly, the 5 p.m. hour was the peak time for collisions in both years, although the number of crashes during this hour decreased from 44 to 35.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased notably from the prior year. Four fatal crashes occurred in 2025, whereas none were recorded in 2024. The proportion of crashes involving an injury grew from 24.4% in 2024 to 29.4% in 2025, driven by a higher share of both serious injury (from 0.8% to 2.4%) and minor injury (from 15.8% to 21.9%) incidents.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1%
Serious Injury10serious injury crashes2.4%
150.0%prior 4
Minor Injury90minor injury crashes21.9%
20.0%prior 75
Possible Injury17possible injury crashes4.1%
-54.1%prior 37
No Injury285no injury crashes69.3%
-19.7%prior 355

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

While the top contributing factors remained similar, their prevalence shifted. Crashes attributed to 'Followed too closely' decreased by 43.3% in count, from 90 incidents in 2024 to 51 in 2025, dropping it from the top-ranked factor to the third. Conversely, crashes involving 'Failed to yield right of way' increased in count from 61 to 66. 'No improper driving' was the most cited category in 2025 with 90 incidents, a slight increase from 87 in the prior year.

Officer-Reported Primary Contributing Cause

No improper driving90 (21.9%)3.4%prior 87
Failed to yield right of way66 (16.1%)8.2%prior 61
Followed too closely51 (12.4%)-43.3%prior 90
Inattention48 (11.7%)2.1%prior 47
Driving too fast for conditions25 (6.1%)-26.5%prior 34
Failure to keep in proper lane or running off road20 (4.9%)-44.4%prior 36
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner12 (2.9%)-33.3%prior 18
Made an improper turn11 (2.7%)37.5%prior 8
Fatigued/asleep10 (2.4%)100.0%prior 5
Visibility obstructed10 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions were broadly similar between the two periods. The proportion of crashes occurring in daylight (68.1% in 2025 vs. 65.6% in 2024) and on dry roads (75.2% vs. 76.2%) remained stable. Crashes during adverse weather like rain or snow accounted for approximately 16% of all incidents in both years, indicating no significant shift in the impact of environmental conditions on crash frequency.

Weather

Clear231 (56.5%)
-27.8%prior 320
Clear/Clear58 (14.2%)
262.5%prior 16
Cloudy30 (7.3%)
-16.7%prior 36
Rain18 (4.4%)
-33.3%prior 27
Snow14 (3.4%)
-44.0%prior 25
Cloudy/Rain12 (2.9%)
20.0%prior 10
Rain/Cloudy6 (1.5%)
Cloudy/Cloudy5 (1.2%)
Snow/Sleet, hail (freezing rain or drizzle)5 (1.2%)
Rain/Rain4 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight280 (68.3%)
-10.0%prior 311
Dark - lighted roadway57 (13.9%)
-21.9%prior 73
Dark - roadway not lighted43 (10.5%)
-21.8%prior 55
Dusk16 (3.9%)
-5.9%prior 17
Dawn12 (2.9%)
20.0%prior 10
Dark - unknown roadway lighting1 (0.2%)
-85.7%prior 7
Other1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry309 (75.6%)
-14.4%prior 361
Wet66 (16.1%)
13.8%prior 58
Snow23 (5.6%)
-28.1%prior 32
Ice6 (1.5%)
-57.1%prior 14
Slush3 (0.7%)
-57.1%prior 7
Other2 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes saw some shifts, with Toyota's involvement decreasing from 138 to 101 vehicles, though it remained the top make. Demographically, the share of persons aged 16-20 involved in crashes decreased from 12.7% to 9.3% of the total. In contrast, the share of persons aged 65 and older increased from 12.4% to 14.1%.

Top Vehicle Makes (743 vehicles)

1
TOYOTA101 (13.6%)
-26.8%prior 138
2
FORD91 (12.2%)
11.0%prior 82
3
HONDA67 (9%)
8.1%prior 62
4
CHEVROLET53 (7.1%)
-17.2%prior 64
5
SUBARU48 (6.5%)
-5.9%prior 51
6
NISSAN47 (6.3%)
-7.8%prior 51
7
HYUNDAI34 (4.6%)
-10.5%prior 38
8
JEEP24 (3.2%)
-44.2%prior 43
9
VOLKSWAGEN24 (3.2%)
100.0%prior 12
10
GMC14 (1.9%)
-26.3%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (911 persons with recorded sex)

Male543 (59.6%)
-11.0%prior 610
Female368 (40.4%)
-20.0%prior 460

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

While the total number of crashes decreased across most speed zones, all four fatal crashes in 2025 occurred in zones with posted speed limits of 45 mph or higher. In 2024, there were no fatalities in any speed zone. The proportion of crashes in higher-speed zones (45 mph and above) was stable at around 48% in both years, but the consequences of these crashes became more severe in the current period.

Fatal crashes by zone: 45 mph: 1 of 51 (1.961%) · 50 mph: 1 of 54 (1.852%) · 55 mph: 1 of 17 (5.882%) · 65 mph: 1 of 75 (1.333%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: STURBRIDGE, MA
  • Total crash records analyzed: 411
  • Total persons involved: 974
  • Total vehicles involved: 743

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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/sturbridge/2025-annual-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 — 2025 | ThatCarHitMe.com