Monthly Traffic Safety Analysis

11,386 CRASHES IN
MASSACHUSETTS, MA
JANUARY 2025

All metrics benchmarked againstJanuary 2024

In January 2025, there were 11,386 total crashes, an 11.5% decrease from the 12,858 crashes recorded in January 2024. Despite the overall drop in collisions, the number of fatalities increased from 28 to 31. A significant factor in the overall crash reduction appears to be a substantial decrease in crashes occurring on adverse road surfaces (snow, ice, wet, or slush), which fell from 5,967 incidents in the prior year to 3,260 in the current period.

11,386

-11.4%was 12,858

Total Crash Events

31

10.7%was 28

Persons Killed

3,274

2.0%was 3,209

Persons Injured

1,010

-7.1%was 1,087

Hit-and-Run Crashes

Note: "Persons Killed" (31) counts individual fatalities across all crash events. "Fatal" in the severity table below (31) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 480 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 2025-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Year-over-year, total traffic crashes in January saw a notable decrease of 11.5%, falling from 12,858 in 2024 to 11,386 in 2025. However, this downward trend in overall crashes did not extend to severity, as total fatalities rose by 10.7% (from 28 to 31) and total injuries saw a slight increase of 2.0% (from 3,209 to 3,274).

1,010

Hit-and-Run Crashes — January 2025

-7.1% vs prior (1,087)

The total number of hit-and-run crashes decreased from 1,087 in January 2024 to 1,010 in January 2025, a reduction of 7.1%. However, because total crashes fell by a larger margin, the hit-and-run rate—the proportion of all crashes that were hit-and-runs—actually increased. The rate rose from 8.5% in the prior year to 8.9% in the current period, indicating that hit-and-runs constituted a larger share of all crashes.

Vulnerable Road User Casualties

10

Pedestrians Killed

Prior: 911.1%

0

Cyclists Killed

Prior: 00.0%

21

Motorists Killed

Prior: 1910.5%

0

Other Killed

Prior: 00.0%

164

Pedestrians Injured

Prior: 14513.1%

33

Cyclists Injured

Prior: 3010.0%

3,057

Motorists Injured

Prior: 3,0281.0%

20

Other Injured

Prior: 6233.3%

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 patterns of crashes shifted significantly between the two periods. In January 2025, the peak day for crashes was Friday with 1,867 incidents, a change from January 2024 when Tuesday was the peak day with 2,551 crashes. The peak hour also changed, moving from the 5 p.m. evening commute in the prior year (1,077 crashes) to the 8 a.m. morning commute in the current year (908 crashes).

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

Although total crashes decreased, the severity of crashes increased year-over-year. The number of fatal crashes rose from 26 to 31, and the fatal crash rate increased from 0.20% to 0.27% of all crashes. Similarly, the count of serious injury crashes grew from 157 to 180, representing a proportional increase from 1.2% to 1.6% of all crashes. The proportion of crashes resulting in no injuries decreased from 75.2% to 73.7%.

Outcome by Severity (Crash Events)

Fatal31fatal crashes0.3%
19.2%prior 26
Serious Injury180serious injury crashes1.6%
14.6%prior 157
Minor Injury1,515minor injury crashes13.3%
3.4%prior 1,465
Possible Injury791possible injury crashes6.9%
-3.4%prior 819
No Injury8,389no injury crashes73.7%
-13.3%prior 9,671

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

While the top contributing factors remained consistent in ranking, their counts shifted year-over-year. The most significant change was in crashes attributed to "Driving too fast for conditions," which plummeted by 50.7% in count from 1,013 incidents in January 2024 to 499 in January 2025. Crashes involving "Inattention" also saw a decrease in count from 1,481 to 1,348. Conversely, crashes where a driver "Failed to yield right of way" saw a slight increase in count from 1,123 to 1,135.

Officer-Reported Primary Contributing Cause

No improper driving3,100 (27.2%)-13.9%prior 3,602
Inattention1,348 (11.8%)-9.0%prior 1,481
Failed to yield right of way1,135 (10%)1.1%prior 1,123
Followed too closely905 (7.9%)-8.1%prior 985
Driving too fast for conditions499 (4.4%)-50.7%prior 1,013
Failure to keep in proper lane or running off road474 (4.2%)-14.3%prior 553
Disregarded traffic signs, signals, road markings355 (3.1%)18.3%prior 300
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner294 (2.6%)-0.7%prior 296
Other improper action288 (2.5%)-14.8%prior 338
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway260 (2.3%)25.0%prior 208

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

Driving conditions in January 2025 were markedly different from the previous year, which corresponds with the overall drop in crashes. Crashes occurring on adverse road surfaces (snow, wet, ice, or slush) decreased substantially, from 5,967 incidents (46.4% of total) in 2024 to 3,260 (28.6% of total) in 2025. Consequently, crashes on dry roads increased in count from 6,593 to 7,867. A higher proportion of crashes occurred during daylight (58.1% vs 55.6%) in the current period.

Weather

Clear6,637 (59.2%)
12.2%prior 5,917
Clear/Clear1,394 (12.4%)
169.1%prior 518
Snow845 (7.5%)
-44.0%prior 1,510
Cloudy712 (6.4%)
-50.5%prior 1,439
Rain344 (3.1%)
-49.0%prior 675
Clear/Cloudy164 (1.5%)
7.2%prior 153
Snow/Snow120 (1.1%)
0.0%prior 120
Clear/Other91 (0.8%)
16.7%prior 78
Cloudy/Cloudy89 (0.8%)
-1.1%prior 90
Clear/Unknown81 (0.7%)
-10.0%prior 90

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

Lighting

Daylight6,619 (58.9%)
-7.4%prior 7,145
Dark - lighted roadway2,980 (26.5%)
-17.9%prior 3,631
Dark - roadway not lighted801 (7.1%)
-23.7%prior 1,050
Dusk401 (3.6%)
-9.9%prior 445
Dawn315 (2.8%)
8.2%prior 291
Dark - unknown roadway lighting108 (1.0%)
-4.4%prior 113
Other9 (0.1%)
-67.9%prior 28

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

Road Surface

Dry7,867 (70.4%)
19.3%prior 6,593
Snow1,288 (11.5%)
-46.9%prior 2,424
Wet1,244 (11.1%)
-47.9%prior 2,387
Ice650 (5.8%)
-16.2%prior 776
Slush78 (0.7%)
-79.5%prior 380
Other26 (0.2%)
44.4%prior 18
Sand, mud, dirt, oil, gravel23 (0.2%)
-41.0%prior 39
Water (standing, moving)2 (0.0%)
-91.3%prior 23

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

Vehicles & Demographics

The demographic profile of vehicles involved in crashes remained largely stable year-over-year. The top five most frequently involved vehicle makes—Toyota, Honda, Ford, Chevrolet, and Nissan—retained their rankings in both January 2024 and January 2025, with counts for each decreasing in line with the overall drop in crashes. The age distribution of persons involved in crashes also showed little change, though there was a slight proportional increase in individuals aged 65 and older, from 9.8% of the total in the prior year to 10.4% in the current year.

Top Vehicle Makes (20,875 vehicles)

1
TOYOTA3,587 (17.2%)
-4.9%prior 3,771
2
HONDA2,648 (12.7%)
-9.7%prior 2,932
3
FORD2,222 (10.6%)
-8.2%prior 2,421
4
CHEVROLET1,426 (6.8%)
-11.6%prior 1,614
5
NISSAN1,336 (6.4%)
-9.8%prior 1,481
6
JEEP976 (4.7%)
-9.6%prior 1,080
7
SUBARU946 (4.5%)
-0.5%prior 951
8
HYUNDAI882 (4.2%)
-3.8%prior 917
9
KIA528 (2.5%)
-9.1%prior 581
10
GMC428 (2.1%)
-14.7%prior 502

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

2,624 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (22,611 persons with recorded sex)

Male13,116 (58.0%)
-8.3%prior 14,296
Female9,487 (42.0%)
-7.2%prior 10,224
X / Unspecified8 (0.0%)
-42.9%prior 14

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

Crash distribution across speed zones shifted towards lower-speed urban roads. Crashes in 25 mph zones increased in count from 2,431 to 2,853, while collisions in 65 mph zones decreased from 913 to 568. Despite fewer crashes in high-speed zones, the number of fatal crashes within them increased; the 65 mph zone saw fatal crashes rise from 2 to 7. This resulted in a significantly higher fatal crash rate for the 65 mph zone, which jumped from 0.22% in the prior year to 1.23% in the current year.

Fatal crashes by zone: 15 mph: 1 of 182 (0.549%) · 25 mph: 7 of 2,853 (0.245%) · 30 mph: 6 of 2,993 (0.2%) · 35 mph: 3 of 1,479 (0.203%) · 40 mph: 4 of 808 (0.495%) · 60 mph: 1 of 31 (3.226%) · 65 mph: 7 of 568 (1.232%)

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: massachusetts, MA
  • Total crash records analyzed: 11,386
  • Total persons involved: 25,479
  • Total vehicles involved: 20,875

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). "massachusetts, 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/statewide/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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Massachusetts (Statewide) Crash Report — January 2025 | ThatCarHitMe.com