ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FREETOWN, MA · 2022
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/freetown/2022-annual-report
Yearly Traffic Safety Analysis
234 CRASHES IN
FREETOWN, MA
2022
Total crashes in Freetown rose from 218 in 2021 to 234 in 2022, a 7.3% increase. While total fatalities doubled from one to two, the number of persons injured in crashes saw a significant year-over-year decrease of 39.0%, falling from 77 to 47. This decline in injuries occurred despite the growth in overall crash volume.
234
▲ 7.3%was 218
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
47
▼ -39.0%was 77
Persons Injured
10
Hit-and-Run Crashes
Note: "Persons Killed" (2) 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. 7 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall crash trend in Freetown from 2021 to 2022 shows a 7.3% increase in total collisions, rising from 218 to 234. Despite this increase and a doubling of fatalities from one to two, the total number of injuries reported decreased by 39.0%. This indicates that while crashes became more frequent, they were less likely to result in injury.
10
Hit-and-Run Crashes — 2022
▼ 0.0% vs prior (10)
The total number of hit-and-run crashes remained unchanged at 10 incidents in both 2021 and 2022. Due to the overall increase in total crashes, the hit-and-run rate saw a slight decrease, from 4.6% of all crashes in 2021 to 4.3% in 2022. This indicates a stable trend in the absolute count of these incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
2
Motorists Killed
1
Pedestrians Injured
46
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal crash patterns shifted between the two periods. In 2022, the peak day for crashes was Monday with 45 incidents, and the peak hour was 7 a.m. with 21 incidents. This contrasts with 2021, when the peak day was Tuesday with 34 crashes and the peak time was later in the day at 3 p.m. with 16 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes shifted year-over-year. While the number of fatal crashes doubled from one to two, the overall proportion of crashes involving any injury (serious, minor, or possible) decreased from 26.7% of all crashes in 2021 to 16.7% in 2022. Correspondingly, crashes resulting in no injuries increased their share of the total from 67.9% in 2021 to 79.5% in 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
A comparison of contributing factors shows a significant rise in crashes attributed to "Driving too fast for conditions," with the count increasing by 150% from 6 in 2021 to 15 in 2022. Similarly, the count of crashes involving "Failed to yield right of way" rose from 7 to 15. The most cited factor in both years, "No improper driving," remained relatively stable with 68 incidents in 2021 and 70 in 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
While most crash conditions remained proportionally stable, there was a notable increase in incidents occurring during adverse weather. Crashes in the rain more than doubled in count from 10 in 2021 to 24 in 2022. This corresponds with an increase in crashes on wet road surfaces, which rose from 30 to 42 incidents year-over-year. Crashes in daylight and on dry roads remained the most common scenarios in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained consistent, with Toyota, Ford, and Honda being the most frequent in both 2021 and 2022. An analysis of person demographics shows a notable increase in the involvement of the 55-64 age group, which grew from representing 6.6% of persons in 2021 to 10.3% in 2022. Conversely, the 16-20 age group's share of involvement decreased from 11.3% to 9.1%.
Top Vehicle Makes (344 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
31 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (372 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of fatal crashes across speed zones changed between periods. In 2021, the single fatal crash occurred in a 40 mph zone, whereas in 2022, both fatal crashes took place in a 65 mph zone. The total number of crashes in the 65 mph zone remained stable (72 in 2021 vs. 74 in 2022). There was also a notable increase in crashes within 30 mph zones, which rose from 35 incidents to 44.
Fatal crashes by zone: 65 mph: 2 of 74 (2.703%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: FREETOWN, MA
- Total crash records analyzed: 234
- Total persons involved: 407
- Total vehicles involved: 344
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). "FREETOWN, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/freetown/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved