Yearly Traffic Safety Analysis

92 CRASHES IN
MERRIMAC, MA
2025

All metrics benchmarked against2024

In Merrimac, total traffic crashes increased by 13.6% from 81 in 2024 to 92 in 2025. While overall crashes and injuries rose, the most significant year-over-year shift was a substantial decrease in DUI-related crashes, which fell from 7 incidents to just 1.

92

13.6%was 81

Total Crash Events

0

Persons Killed

26

36.8%was 19

Persons Injured

4

33.3%was 3

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. 3 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

The overall trend shows an increase in traffic collisions year-over-year. Total crashes rose from 81 to 92, a 13.6% increase. Concurrently, the number of individuals injured in these incidents increased by 36.8%, from 19 people in 2024 to 26 in 2025.

4

Hit-and-Run Crashes — 2025

33.3% vs prior (3)

Hit-and-run incidents saw a slight increase, rising from 3 crashes in 2024 to 4 in 2025. The corresponding hit-and-run rate, which measures the proportion of total crashes that are hit-and-runs, also trended up slightly from 3.7% in the prior period to 4.3% in the current period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

25

Motorists Injured

Prior: 1931.6%

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

A notable shift occurred in the timing of crashes between the two periods. The peak day for collisions moved from Saturday (19 crashes) in 2024 to Wednesday (27 crashes) in 2025. The peak hour also changed, shifting from the 9 p.m. hour in the prior year (7 crashes) to the 12 p.m. hour in the current year (11 crashes).

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

No fatal crashes were recorded in either 2024 or 2025. However, the severity of crashes increased, with the total number of injuries rising from 19 to 26. The count of serious injury crashes increased from 1 to 2, and minor injury crashes rose from 14 to 19. Consequently, crashes resulting in any injury made up 30.4% of all collisions in 2025, up from a 22.2% share in 2024.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes2.2%
100.0%prior 1
Minor Injury19minor injury crashes20.7%
35.7%prior 14
Possible Injury4possible injury crashes4.3%
100.0%prior 2
No Injury64no injury crashes69.6%
1.6%prior 63

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 "No improper driving" remained the most cited factor in both periods, its count increased from 29 to 33. The most significant change was in crashes attributed to "Inattention," which tripled in count from 3 incidents in 2024 to 9 in 2025. In contrast, crashes related to "Driving too fast for conditions" saw a decrease in count from 8 to 6 incidents year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving33 (35.9%)13.8%prior 29
Inattention9 (9.8%)
Driving too fast for conditions6 (6.5%)-25.0%prior 8
Failed to yield right of way6 (6.5%)
Failure to keep in proper lane or running off road6 (6.5%)0.0%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (4.3%)
Followed too closely3 (3.3%)
Glare3 (3.3%)
Other improper action3 (3.3%)
Fatigued/asleep3 (3.3%)

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

Crashes in daylight conditions increased from 46 to 57 year-over-year, and collisions on dry roads rose from 58 to 70. While most crashes in both periods occurred in clear weather on dry roads, the number of crashes during snowy conditions also saw a slight increase from 4 to 6 incidents.

Weather

Clear41 (44.6%)
-10.9%prior 46
Clear/Clear12 (13.0%)
Cloudy12 (13.0%)
33.3%prior 9
Snow6 (6.5%)
Clear/Other5 (5.4%)
Rain3 (3.3%)
Clear/Cloudy2 (2.2%)
Cloudy/Cloudy2 (2.2%)
Snow/Cloudy1 (1.1%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.1%)

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

Lighting

Daylight57 (62.0%)
23.9%prior 46
Dark - roadway not lighted16 (17.4%)
-15.8%prior 19
Dark - lighted roadway12 (13.0%)
0.0%prior 12
Dawn4 (4.3%)
Dusk2 (2.2%)
Other1 (1.1%)

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

Road Surface

Dry70 (76.1%)
20.7%prior 58
Wet9 (9.8%)
-18.2%prior 11
Snow7 (7.6%)
16.7%prior 6
Ice4 (4.3%)
-20.0%prior 5
Slush2 (2.2%)

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 three vehicle makes involved in crashes—Honda, Ford, and Toyota—remained consistent across both years. A significant demographic change was observed in the age of persons involved in crashes; the 16-20 age group's involvement more than doubled, increasing from 14 individuals in 2024 to 29 in 2025. Conversely, involvement for the 21-25 age group decreased from 20 to 11 individuals.

Top Vehicle Makes (131 vehicles)

1
HONDA17 (13%)
6.3%prior 16
2
FORD15 (11.5%)
50.0%prior 10
3
TOYOTA12 (9.2%)
33.3%prior 9
4
JEEP11 (8.4%)
120.0%prior 5
5
CHEVROLET8 (6.1%)
-11.1%prior 9
6
MAZDA6 (4.6%)
7
NISSAN6 (4.6%)
-25.0%prior 8
8
BMW5 (3.8%)
9
HYUNDAI4 (3.1%)
-33.3%prior 6
10
SUBARU4 (3.1%)
-50.0%prior 8

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

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

Sex Distribution (155 persons with recorded sex)

Male82 (52.9%)
7.9%prior 76
Female73 (47.1%)
55.3%prior 47

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

The distribution of crashes across various speed zones remained largely proportional to the prior year, with no fatal crashes reported in any zone for either period. Minor increases were seen in several zones, consistent with the overall rise in crashes, such as in 65 mph zones (from 37 to 39 crashes) and 25 mph zones (from 7 to 10 crashes).

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: MERRIMAC, MA
  • Total crash records analyzed: 92
  • Total persons involved: 168
  • Total vehicles involved: 131

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). "MERRIMAC, 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/merrimac/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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Merrimac, MA Crash Report — 2025 | ThatCarHitMe.com