ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FRAMINGHAM, MA · OCTOBER 2024
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/october-2024-report
Monthly Traffic Safety Analysis
141 CRASHES IN
FRAMINGHAM, MA
OCTOBER 2024
In October 2024, Framingham experienced 141 total crashes, an increase from the 135 crashes recorded in October 2023, representing a 4.44% rise. The most notable shift was the increase in total fatalities, which rose from 0 in the prior period to 1 in the current period. Total injuries also increased from 35 to 42 year-over-year.
141
▲ 4.4%was 135
Total Crash Events
1
Persons Killed
42
▲ 20.0%was 35
Persons Injured
20
▲ 5.3%was 19
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. 9 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for Framingham indicates a slight upward trend year-over-year, with total crashes increasing from 135 in October 2023 to 141 in October 2024. This represents a 4.44% increase in the total number of reported crashes for the month.
20
Hit-and-Run Crashes — October 2024
▲ 5.3% vs prior (19)
Hit-and-run crashes increased slightly from 19 in October 2023 to 20 in October 2024. The corresponding hit-and-run rate also saw a minor increase, moving from 14.1% to 14.2%. This indicates a relatively stable trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
1
Pedestrians Injured
4
Cyclists Injured
35
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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 Tuesday, with 28 crashes in October 2023, to Friday, with 26 crashes in October 2024. Similarly, the peak hour for crashes moved from 7 PM, which saw 12 incidents in the prior period, to 5 PM, which recorded 13 incidents in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes increased from 0 in October 2023 to 1 in October 2024. Serious injury crashes also rose from 1 (0.7% share of crashes) to 3 (2.1% share of crashes) year-over-year. Minor injury crashes saw a slight decrease in count from 21 to 19, while possible injury crashes increased from 6 to 11.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Followed too closely' saw a significant increase in count, rising from 12 crashes to 20 crashes, a 66.7% change. Conversely, 'Failed to yield right of way' decreased from 24 crashes to 18 crashes, a 25% change in count. The factor 'No improper driving' also saw a slight increase from 35 to 38 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on dry road surfaces increased from 103 to 135, while crashes on wet road surfaces significantly decreased from 30 to 5. Incidents during clear weather conditions (Clear/Clear and Clear combined) rose from 99 to 124, whereas those in rainy conditions (Rain/Rain and Rain combined) decreased from 21 to 3. Crashes in daylight increased from 73 to 90, while those in dark-lighted roadway conditions decreased from 45 to 35.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Road surface condition field
Vehicles & Demographics
Toyota remained the most frequently involved vehicle make, with its count increasing from 34 to 63 vehicles. Ford involvement decreased from 33 to 22 vehicles, while Nissan increased from 13 to 21. In terms of persons involved, the 21-25 age group saw a decrease from 42 to 32, while the 65+ age group experienced a notable increase from 21 to 36.
Top Vehicle Makes (275 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Vehicle unit records
39 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (311 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed limit zone decreased from 10 in October 2023 to 4 in October 2024. Conversely, crashes in the 65 mph speed limit zone increased from 8 to 13 during the same period. The 30 mph and 50 mph speed zones maintained consistent crash counts of 8 and 2, respectively, across both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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: 2024-10-01 through 2024-10-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-10-01 through 2024-10-31 (31 days)
- Geographic scope: FRAMINGHAM, MA
- Total crash records analyzed: 141
- Total persons involved: 350
- 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: October 2024." Published June 21, 2026. Reporting period: 2024-10-01 to 2024-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/october-2024-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: 2024-10-01 – 2024-10-31
Generated: June 21, 2026 · All rights reserved