ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FRAMINGHAM, MA · SEPTEMBER 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/framingham/september-2022-report
Monthly Traffic Safety Analysis
142 CRASHES IN
FRAMINGHAM, MA
SEPTEMBER 2022
Total crashes in Framingham decreased from 158 in September 2021 to 142 in September 2022, representing a 10.1% reduction. Despite this decrease in overall crashes, total injuries saw a substantial increase of 427.3%, rising from 11 to 58. Fatalities decreased from 1 in September 2021 to 0 in September 2022.
142
▼ -10.1%was 158
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
58
▲ 427.3%was 11
Persons Injured
13
▼ -48.0%was 25
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash frequency in Framingham decreased by 10.1% year-over-year, with 142 crashes in September 2022 compared to 158 in September 2021. While total fatalities dropped from 1 to 0, total injuries experienced a significant increase of 427.3%, rising from 11 to 58. This suggests a trend of fewer but potentially more injurious crashes.
13
Hit-and-Run Crashes — September 2022
▼ -48.0% vs prior (25)
Hit-and-run crashes decreased by 48%, from 25 incidents in September 2021 to 13 in September 2022. Consequently, the hit-and-run rate also decreased from 15.8% to 9.2% of all crashes. This indicates a notable downward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
4
Pedestrians Injured
4
Cyclists Injured
50
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Wednesday (31 crashes) in September 2021 to Thursday (28 crashes) in September 2022. The peak hour also changed, moving from 7 AM (17 crashes) in the prior period to 5 PM (13 crashes) in the current period. These shifts indicate a change in the temporal distribution of crash occurrences.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities decreased from 1 in September 2021 to 0 in September 2022, resulting in a fatal crash rate reduction from 0.63% to 0%. Total injuries, however, increased dramatically from 11 to 58, a 427.3% rise. The proportion of crashes resulting in minor injuries (Severity B) increased from 3.2% to 16.2% of all crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, "No improper driving," remained constant at 35 crashes in both periods. "Followed too closely" crashes decreased from 18 to 14 (a 22.2% decrease in count), while "Failed to yield right of way" decreased from 17 to 15 crashes (an 11.8% decrease in count). "Disregarded traffic signs, signals, road markings" remained stable at 11 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in dry road conditions decreased from 136 in September 2021 to 123 in September 2022. Similarly, crashes in daylight conditions decreased from 110 to 100 year-over-year. The number of crashes in clear weather conditions also saw a slight decrease from 120 to 110 (combining Clear and Clear/Clear categories).
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 306 in September 2021 to 275 in September 2022. Toyota remained the top make involved in crashes, though its count decreased from 61 to 44 (a 27.8% decrease). Ford-involved crashes increased from 32 to 40 (a 25% increase), while Honda-involved crashes remained relatively stable (31 to 30).
Top Vehicle Makes (275 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records
24 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (317 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Person-level records linked to crash events
Speed Limit Zones
The total number of crashes with reported speed limits decreased from 57 in September 2021 to 24 in September 2022. Crashes in the 30 mph zone saw a significant reduction from 20 to 3, and crashes in the 65 mph zone decreased from 20 to 10. The prior period recorded one fatality in a 40 mph zone, whereas no fatalities were reported in any speed zone during the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-09-01 through 2022-09-30 (30 days)
- Geographic scope: FRAMINGHAM, MA
- Total crash records analyzed: 142
- Total persons involved: 342
- Total vehicles involved: 275
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). "FRAMINGHAM, MA Crash Intelligence Report: September 2022." Published June 21, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/september-2022-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: 2022-09-01 – 2022-09-30
Generated: June 21, 2026 · All rights reserved