Monthly Traffic Safety Analysis

10,672 CRASHES IN
MASSACHUSETTS, MA
JULY 2025

All metrics benchmarked againstJuly 2024

In July 2025, there were 10,672 total crashes, a 1.5% increase from the 10,519 crashes recorded in July 2024. During this period, total fatalities rose from 34 to 35, and total injuries increased by 3.2% from 3,699 to 3,817. A notable year-over-year change was the 7.3% increase in hit-and-run incidents, which rose from 981 to 1,053.

10,672

1.5%was 10,519

Total Crash Events

35

2.9%was 34

Persons Killed

3,817

3.2%was 3,699

Persons Injured

1,053

7.3%was 981

Hit-and-Run Crashes

Note: "Persons Killed" (35) counts individual fatalities across all crash events. "Fatal" in the severity table below (32) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 465 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data from July indicates a slight upward trend compared to the same month last year. Total crashes increased by 1.5%, rising from 10,519 in July 2024 to 10,672 in July 2025. Similarly, the number of people injured grew by 3.2%, and the number of fatalities increased from 34 to 35.

1,053

Hit-and-Run Crashes — July 2025

7.3% vs prior (981)

Hit-and-run incidents increased in both count and as a proportion of total crashes compared to the previous year. The number of hit-and-run crashes rose by 7.3%, from 981 in July 2024 to 1,053 in July 2025. This pushed the hit-and-run rate up from 9.3% to 9.9% of all crashes, indicating an upward trend for this type of incident.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 30.0%

0

Cyclists Killed

Prior: 1-100.0%

32

Motorists Killed

Prior: 306.7%

0

Other Killed

Prior: 00.0%

103

Pedestrians Injured

Prior: 9113.2%

168

Cyclists Injured

Prior: 15012.0%

3,497

Motorists Injured

Prior: 3,4142.4%

49

Other Injured

Prior: 4411.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two periods. While the peak hour for crashes remained 4 p.m. in both July 2024 (871 crashes) and July 2025 (945 crashes), the peak day of the week shifted from Monday (1,844 crashes) to Tuesday (1,845 crashes). Notably, Thursday crashes increased significantly from 1,299 in the prior year to 1,841 in the current period, becoming the second-busiest day for collisions.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The overall severity of crashes showed a slight increase year-over-year. The proportion of fatal crashes remained stable at 0.3% for both periods, with the count of fatal incidents rising from 31 to 32. Crashes resulting in serious injuries increased from 235 (a 2.2% share) to 251 (a 2.4% share), and minor injury crashes grew from 1,665 (a 15.8% share) to 1,796 (a 16.8% share).

Severity is per crash event (most severe injury). 32 fatal crash events resulted in 35 persons killed.

Outcome by Severity (Crash Events)

Fatal32fatal crashes0.3%
3.2%prior 31
Serious Injury251serious injury crashes2.4%
6.8%prior 235
Minor Injury1,796minor injury crashes16.8%
7.9%prior 1,665
Possible Injury747possible injury crashes7%
-5.6%prior 791
No Injury7,381no injury crashes69.2%
0.6%prior 7,335

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes remained consistent year-over-year, with 'Inattention' (1,559 crashes), 'Failed to yield right of way' (1,215 crashes), and 'Followed too closely' (1,028 crashes) ranking as the top driver-related causes in July 2025. The count of crashes attributed to 'Failed to yield right of way' increased by 6.9% from 1,137 in the prior year. In contrast, crashes where a driver was 'Distracted' decreased in count by 14.2%, falling from 254 incidents to 218.

Officer-Reported Primary Contributing Cause

No improper driving2,526 (23.7%)3.1%prior 2,451
Inattention1,559 (14.6%)2.4%prior 1,523
Failed to yield right of way1,215 (11.4%)6.9%prior 1,137
Followed too closely1,028 (9.6%)-1.0%prior 1,038
Failure to keep in proper lane or running off road546 (5.1%)9.4%prior 499
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner373 (3.5%)5.7%prior 353
Disregarded traffic signs, signals, road markings354 (3.3%)9.9%prior 322
Other improper action334 (3.1%)4.7%prior 319
Distracted218 (2%)-14.2%prior 254
Made an improper turn160 (1.5%)-7.0%prior 172

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained largely stable compared to the previous year, with the vast majority of incidents occurring in favorable conditions. In July 2025, 90.4% of crashes happened on dry roads and 78.9% occurred in daylight, proportions nearly identical to July 2024 (89.9% and 79.4%, respectively). The share of crashes occurring in clear weather conditions increased from 79.3% in the prior year to 83.4% in the current period.

Weather

Clear7,208 (68.4%)
-6.4%prior 7,700
Clear/Clear1,692 (16.1%)
164.8%prior 639
Cloudy502 (4.8%)
-44.0%prior 897
Rain313 (3.0%)
-17.4%prior 379
Clear/Cloudy150 (1.4%)
-9.1%prior 165
Cloudy/Rain124 (1.2%)
-23.5%prior 162
Rain/Cloudy109 (1.0%)
91.2%prior 57
Clear/Other98 (0.9%)
0.0%prior 98
Clear/Unknown86 (0.8%)
-19.6%prior 107
Cloudy/Cloudy75 (0.7%)
53.1%prior 49

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Weather condition at time of crash

Lighting

Daylight8,426 (79.9%)
0.9%prior 8,349
Dark - lighted roadway1,302 (12.4%)
4.5%prior 1,246
Dark - roadway not lighted363 (3.4%)
-8.3%prior 396
Dusk267 (2.5%)
19.2%prior 224
Dawn116 (1.1%)
-24.7%prior 154
Dark - unknown roadway lighting52 (0.5%)
8.3%prior 48
Other16 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Lighting condition field

Road Surface

Dry9,651 (92.0%)
2.0%prior 9,465
Wet794 (7.6%)
-10.5%prior 887
Sand, mud, dirt, oil, gravel26 (0.2%)
52.9%prior 17
Other10 (0.1%)
Water (standing, moving)4 (0.0%)
Snow1 (0.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Road surface condition field

Vehicles & Demographics

The top five vehicle makes involved in crashes—Toyota, Honda, Ford, Chevrolet, and Nissan—remained unchanged in their rankings from the previous year. Analysis of the age distribution of persons involved in crashes reveals a notable shift in the 65+ age group. The number of individuals in this demographic involved in crashes increased by 11.6%, from 2,757 in July 2024 to 3,076 in July 2025, making it the third-largest group involved, up from fifth-largest in the prior year.

Top Vehicle Makes (20,266 vehicles)

1
TOYOTA3,308 (16.3%)
1.1%prior 3,272
2
HONDA2,609 (12.9%)
7.1%prior 2,436
3
FORD2,066 (10.2%)
1.5%prior 2,035
4
CHEVROLET1,429 (7.1%)
0.8%prior 1,418
5
NISSAN1,124 (5.5%)
-1.1%prior 1,137
6
JEEP934 (4.6%)
-2.3%prior 956
7
SUBARU785 (3.9%)
-5.0%prior 826
8
HYUNDAI771 (3.8%)
5.3%prior 732
9
KIA507 (2.5%)
7.0%prior 474
10
GMC450 (2.2%)
6.4%prior 423

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Vehicle unit records

2,820 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (22,336 persons with recorded sex)

Male12,828 (57.4%)
2.0%prior 12,571
Female9,498 (42.5%)
2.3%prior 9,287
X / Unspecified10 (0.0%)
66.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Person-level records linked to crash events

Speed Limit Zones

A notable shift occurred in the distribution of crashes by speed limit, with a 16.7% increase in incidents within 25 mph zones, rising from 2,246 to 2,621 year-over-year. In contrast, crashes in 30 mph and 35 mph zones saw a decrease. The location of fatal crashes also shifted toward higher speed zones; in July 2024, the most fatalities occurred in 30 mph (8 deaths) and 35 mph (9 deaths) zones, whereas in July 2025, 40 mph and 65 mph zones each recorded 6 fatalities.

Fatal crashes by zone: 25 mph: 4 of 2,621 (0.153%) · 30 mph: 4 of 2,686 (0.149%) · 35 mph: 4 of 1,254 (0.319%) · 40 mph: 6 of 790 (0.759%) · 45 mph: 4 of 342 (1.17%) · 50 mph: 2 of 236 (0.847%) · 55 mph: 1 of 413 (0.242%) · 65 mph: 6 of 631 (0.951%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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: 2025-07-01 through 2025-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-07-01 through 2025-07-31 (31 days)
  • Geographic scope: massachusetts, MA
  • Total crash records analyzed: 10,672
  • Total persons involved: 25,369
  • Total vehicles involved: 20,266

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: July 2025." Published June 21, 2026. Reporting period: 2025-07-01 to 2025-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/july-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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