ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MILTON, MA · 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/milton/2025-annual-report
Yearly Traffic Safety Analysis
709 CRASHES IN
MILTON, MA
2025
In 2025, Milton recorded 709 total vehicle crashes, a marginal decrease from the 711 crashes reported in 2024. While the overall crash volume remained stable, the most notable year-over-year shift was a 22.3% decrease in the total number of people injured, which fell from 381 to 296. Over the same period, total fatalities increased from 3 to 4.
709
▼ -0.3%was 711
Total Crash Events
4
▲ 33.3%was 3
Persons Killed
296
▼ -22.3%was 381
Persons Injured
88
▲ 27.5%was 69
Hit-and-Run Crashes
Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 29 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 number of crashes in Milton was stable year-over-year, decreasing by just two incidents from 711 in 2024 to 709 in 2025. Despite this stability, the outcomes of these crashes showed a positive trend, with total injuries dropping by 22.3% from 381 to 296. However, total fatalities increased from three in the prior year to four in the current year.
88
Hit-and-Run Crashes — 2025
▲ 27.5% vs prior (69)
Hit-and-run incidents showed a clear upward trend. The total number of hit-and-run crashes rose from 69 in 2024 to 88 in 2025, a 27.5% increase in count. As a result, the hit-and-run rate, which measures the proportion of all crashes that are hit-and-runs, increased from 9.7% in 2024 to 12.4% in 2025.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Cyclists Killed
3
Motorists Killed
2
Pedestrians Injured
4
Cyclists Injured
290
Motorists Injured
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 showed some shifts between the two years. In 2024, Friday was the definitive peak day with 130 crashes, whereas in 2025, both Monday and Friday shared the top spot with 113 crashes each. The peak hour for collisions also shifted later in the evening, moving from 4 PM (56 crashes) in 2024 to 6 PM (49 crashes) in 2025.
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
The severity profile of crashes changed between the two periods, with the share of non-injury crashes increasing from 60.6% to 64.5%. The fatal crash rate decreased from 0.42% (3 crashes) in 2024 to 0.28% (2 crashes) in 2025. The proportion of crashes resulting in any level of injury declined from 36.3% to 31.2%, driven primarily by a reduction in the share of 'Minor Injury' incidents.
Severity is per crash event (most severe injury). 2 fatal crash events resulted in 4 persons killed.
Outcome by Severity (Crash Events)
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
The leading contributing factors for crashes saw notable changes in count year-over-year. The number of crashes attributed to 'Followed too closely' decreased by 32.3%, from 127 incidents in 2024 to 86 in 2025. Conversely, crashes where 'Failed to yield right of way' was a factor increased in count by 25.9% from 54 to 68. Crashes involving 'Inattention' also saw a 30.4% decrease in count, from 69 to 48.
Officer-Reported Primary Contributing Cause
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
While most crashes in both years occurred in clear weather on dry roads, there was a discernible shift in lighting conditions. The proportion of crashes occurring during daylight hours decreased from 62.4% in 2024 to 57.3% in 2025. Concurrently, the share of incidents that happened on a lighted roadway after dark increased from 25.3% to 31.0% of all crashes.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
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—Toyota, Honda, and Ford—maintained their rankings in both 2024 and 2025, with the count of Toyotas increasing from 216 to 249. An analysis of persons involved shows the most-represented age group shifted from 35-44 year-olds in 2024 to 26-34 year-olds in 2025. The number of individuals aged 65 and older involved in crashes also grew from 160 to 207.
Top Vehicle Makes (1,391 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
180 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,570 persons with recorded sex)
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 55 mph speed zone was the site of the most crashes in both periods, though the count within this zone decreased from 191 in 2024 to 146 in 2025. In 2024, fatal crashes were recorded in 35 mph and 45 mph zones. In 2025, the one fatal crash with a recorded speed limit occurred in a 45 mph zone, indicating a shift in where fatal incidents happened.
Fatal crashes by zone: 45 mph: 1 of 17 (5.882%)
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: MILTON, MA
- Total crash records analyzed: 709
- Total persons involved: 1,789
- Total vehicles involved: 1,391
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). "MILTON, 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/milton/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved