ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SOUTHBOROUGH, MA · NOVEMBER 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/southborough/november-2024-report
Monthly Traffic Safety Analysis
35 CRASHES IN
SOUTHBOROUGH, MA
NOVEMBER 2024
In November 2024, SOUTHBOROUGH experienced 35 total crashes, a slight increase from the 34 crashes reported in November 2023, representing a 2.9% rise. The most significant year-over-year shift was in total injuries, which saw a 250% increase from 4 injuries in the prior period to 14 injuries in the current period.
35
▲ 2.9%was 34
Total Crash Events
0
Persons Killed
14
▲ 250.0%was 4
Persons Injured
1
▼ -50.0%was 2
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in SOUTHBOROUGH showed a slight upward trend, with total crashes increasing from 34 to 35, a 2.9% rise year-over-year. This was accompanied by a substantial increase in total injuries, which rose from 4 to 14, marking a 250% increase.
1
Hit-and-Run Crashes — November 2024
▼ -50.0% vs prior (2)
Hit-and-run incidents decreased in November 2024 compared to the prior year. The number of hit-and-run crashes fell from 2 to 1, and the associated hit-and-run rate decreased from 5.9% to 2.9% of total crashes.
Vulnerable Road User Casualties
0
Motorists Killed
14
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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 between the two periods. The peak day for crashes moved from Wednesday with 12 crashes in November 2023 to Thursday with 9 crashes in November 2024. Similarly, the peak crash hour changed from 2 p.m. with 3 crashes in the prior year to 7 a.m. with 7 crashes in the current year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The distribution of crash severity showed an increase in injury crashes year-over-year. While serious injury crashes remained at 1 in both periods, minor injury crashes increased from 2 in November 2023 to 7 in November 2024. The proportion of crashes resulting in no injury decreased from 88.2% to 74.3% of total crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw changes in count year-over-year. 'No improper driving' decreased from 16 crashes to 11 crashes, while 'Inattention' decreased from 6 crashes to 4 crashes. Conversely, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from 1 crash to 3 crashes, and 'Followed too closely' remained constant at 3 crashes in both periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Regarding crash conditions, the number of crashes occurring in 'Clear' weather remained stable at 26 in both periods. Crashes on 'Wet' road surfaces increased significantly from 1 in November 2023 to 9 in November 2024, while 'Dry' road crashes decreased from 29 to 26. Crashes during 'Daylight' conditions increased from 18 to 20, and 'Dark - lighted roadway' crashes remained at 8.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 57 in November 2023 to 60 in November 2024, a 5.3% rise. The top vehicle makes shifted, with Honda becoming the most frequent make in November 2024 (12 vehicles) compared to Toyota in November 2023 (12 vehicles). There was a notable increase in persons aged 21-25 involved in crashes, rising from 4 to 15, and a decrease in those aged 45-54, from 17 to 12.
Top Vehicle Makes (60 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records
1 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (81 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crash distribution across speed zones shifted year-over-year. Crashes in 50 mph zones significantly increased from 6 in November 2023 to 15 in November 2024. Conversely, crashes in 65 mph zones decreased from 9 to 3, and 35 mph zones saw a decrease from 4 to 2 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-11-01 through 2024-11-30 (30 days)
- Geographic scope: SOUTHBOROUGH, MA
- Total crash records analyzed: 35
- Total persons involved: 83
- Total vehicles involved: 60
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). "SOUTHBOROUGH, MA Crash Intelligence Report: November 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/southborough/november-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: 2024-11-01 – 2024-11-30
Generated: June 21, 2026 · All rights reserved