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YEAR-OVER-YEAR CRASH REPORT · MILFORD, MA · FEBRUARY 2023
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/milford/february-2023-report
Monthly Traffic Safety Analysis
72 CRASHES IN
MILFORD, MA
FEBRUARY 2023
In Milford, total crashes decreased by 20.9% year-over-year, from 91 crashes in February 2022 to 72 crashes in February 2023. A significant shift was the emergence of one fatal crash and one fatality in the current period, compared to zero in the prior period. Despite the overall decrease in crashes, the presence of a fatal incident marks a critical change in the safety landscape.
72
▼ -20.9%was 91
Total Crash Events
1
Persons Killed
15
Persons Injured
7
▼ -22.2%was 9
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Milford saw a downward trend, decreasing by 20.9% from 91 crashes in February 2022 to 72 crashes in February 2023. However, this period also marked a concerning increase in crash severity, with one fatality recorded compared to none in the previous year. Total injuries remained stable at 15 for both periods.
7
Hit-and-Run Crashes — February 2023
▼ -22.2% vs prior (9)
The number of hit-and-run crashes decreased from 9 in February 2022 to 7 in February 2023. Correspondingly, the hit-and-run rate saw a slight decrease from 9.9% to 9.7% of total crashes. This indicates a minor downward trend in both the count and proportion of hit-and-run incidents.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
0
Pedestrians Injured
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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 notably year-over-year. The peak day for crashes moved from Sunday, with 22 incidents in February 2022, to Friday, with 16 incidents in February 2023. Similarly, the peak crash hour shifted from 6 PM (11 crashes) in the prior period to 3 PM (9 crashes) in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity saw a critical change, with one fatal crash and one fatality recorded in February 2023, compared to zero in February 2022. Total injuries remained constant at 15 for both periods. The proportion of minor injury crashes slightly decreased from 12.1% (11 crashes) to 11.1% (8 crashes), while possible injury crashes maintained a count of 4, increasing their share from 4.4% to 5.6%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors showed significant year-over-year shifts in count. Crashes attributed to 'Inattention' increased by 20% from 15 to 18, becoming the top factor. Conversely, 'No improper driving' decreased by 41.2% from 17 to 10, and 'Driving too fast for conditions' decreased by 66.7% from 12 to 4. 'Failed to yield right of way' saw a substantial 80% decrease in count, falling from 15 to 3 incidents.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in adverse weather conditions generally decreased year-over-year. Crashes during 'Snow' weather conditions dropped from 18 to 4, and those on 'Snow' road surfaces decreased from 13 to 6. Crashes on 'Ice' road surfaces, which accounted for 17 incidents in the prior period, were not recorded in the current period, indicating a shift towards fewer crashes in these challenging conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field
Vehicles & Demographics
The age distribution of persons involved in crashes saw notable changes, with the '0-15' age group increasing from 5 to 15, and the '65+' age group rising from 9 to 23. Conversely, the '16-20' age group decreased from 18 to 8, and the '26-34' age group saw a significant reduction from 50 to 21. TOYOTA remained the top vehicle make involved in crashes, increasing from 21 to 29, while HONDA decreased from 20 to 12.
Top Vehicle Makes (130 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (142 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone decreased from 52 to 37, and those in the 65 mph zone decreased from 10 to 8. The 25 mph zone experienced a decrease in total crashes from 11 to 7, but notably, this zone recorded one fatal crash in February 2023, whereas no fatal crashes occurred in any speed zone in February 2022. Crashes in the 40 mph zone, with 10 incidents, were present in the current period but not explicitly listed in the prior period's top speed limits.
Fatal crashes by zone: 25 mph: 1 of 7 (14.286%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-02-01 through 2023-02-28 (28 days)
- Geographic scope: MILFORD, MA
- Total crash records analyzed: 72
- Total persons involved: 157
- Total vehicles involved: 130
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). "MILFORD, MA Crash Intelligence Report: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milford/february-2023-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: 2023-02-01 – 2023-02-28
Generated: June 21, 2026 · All rights reserved