ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SOUTHBOROUGH, MA · JULY 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/southborough/july-2023-report
Monthly Traffic Safety Analysis
31 CRASHES IN
SOUTHBOROUGH, MA
JULY 2023
In July 2023, SOUTHBOROUGH experienced 31 total crashes, marking a 24% increase from the 25 crashes reported in July 2022. Total injuries rose significantly from 7 to 20 over the same period, indicating a substantial increase in injury severity outcomes.
31
▲ 24.0%was 25
Total Crash Events
0
Persons Killed
20
▲ 185.7%was 7
Persons Injured
3
▲ 200.0%was 1
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash activity in SOUTHBOROUGH shows an upward trend year-over-year, with total crashes increasing by 24% from 25 in July 2022 to 31 in July 2023. Concurrently, the number of persons injured in crashes rose sharply from 7 to 20, representing a 185.7% increase.
3
Hit-and-Run Crashes — July 2023
▲ 200.0% vs prior (1)
Hit-and-run incidents increased significantly year-over-year. The count of hit-and-run crashes rose from 1 in July 2022 to 3 in July 2023. This also led to an increase in the hit-and-run rate, which climbed from 4% in July 2022 to 9.7% in July 2023.
Vulnerable Road User Casualties
0
Motorists Killed
20
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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 year-over-year. While July 2022 saw Friday as the peak day with 6 crashes, July 2023 had two peak days, Sunday and Wednesday, each with 7 crashes. The peak hour for crashes also shifted slightly, moving from 4 PM with 5 crashes in July 2022 to 3 PM with 5 crashes in July 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution of crashes changed notably, with a substantial increase in injury-involved incidents. While both periods reported 1 serious injury, minor injuries increased from 3 in July 2022 to 10 in July 2023, and possible injuries remained stable at 1 for both periods. Consequently, crashes resulting in no injuries decreased from 20 (80% of crashes) in July 2022 to 18 (58.1% of crashes) in July 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Inattention' crashes increased by 3, from 4 in July 2022 to 7 in July 2023. Crashes attributed to 'Failure to keep in proper lane or running off road' also rose by 2, from 1 in July 2022 to 3 in July 2023. Conversely, 'Followed too closely' crashes decreased by 1, from 3 in July 2022 to 2 in July 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions saw some minor shifts year-over-year. Crashes under 'Daylight' conditions increased by 3, from 20 in July 2022 to 23 in July 2023. Additionally, July 2023 reported 3 crashes under 'Cloudy/Rain' conditions and 2 under 'Rain' conditions, categories not present in July 2022. Data for road surface conditions was not available for July 2022, preventing a comparison.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased slightly from 52 in July 2022 to 55 in July 2023. Among vehicle makes, FORD-involved crashes increased by 5 (from 5 to 10), and JEEP-involved crashes increased by 2 (from 2 to 4). Regarding person demographics, the 16-20 age group saw a significant increase in involvement, rising from 7 persons in July 2022 to 16 persons in July 2023.
Top Vehicle Makes (55 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (71 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes within speed limit zones show a notable shift towards higher speed zones. Crashes in the 50 mph zone increased by 6, from 7 in July 2022 to 13 in July 2023. Conversely, crashes in the 65 mph zone decreased by 2, from 7 in July 2022 to 5 in July 2023. No fatal crashes were recorded in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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: 2023-07-01 through 2023-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-07-01 through 2023-07-31 (31 days)
- Geographic scope: SOUTHBOROUGH, MA
- Total crash records analyzed: 31
- Total persons involved: 74
- Total vehicles involved: 55
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: July 2023." Published June 21, 2026. Reporting period: 2023-07-01 to 2023-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/southborough/july-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: 2023-07-01 – 2023-07-31
Generated: June 21, 2026 · All rights reserved