ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BEVERLY, MA · SEPTEMBER 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/beverly/september-2024-report
Monthly Traffic Safety Analysis
41 CRASHES IN
BEVERLY, MA
SEPTEMBER 2024
In September 2024, Beverly experienced 41 crashes, marking a decrease of 12.77% compared to the 47 crashes recorded in September 2023. The most notable shift was a significant reduction in total injuries, which fell by 64.28% from 14 injuries in the prior period to 5 in the current period.
41
▼ -12.8%was 47
Total Crash Events
0
Persons Killed
5
▼ -64.3%was 14
Persons Injured
4
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Beverly showed a downward trend year-over-year, decreasing from 47 crashes in September 2023 to 41 crashes in September 2024. This represents a reduction of 6 crashes, or a 12.77% decline in total crashes.
4
Hit-and-Run Crashes — September 2024
▼ 0.0% vs prior (4)
The number of hit-and-run crashes remained consistent at 4 incidents in both September 2023 and September 2024. However, due to a decrease in total crashes, the hit-and-run rate increased from 8.5% in the prior period to 9.8% in the current period.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
4
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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 (13 crashes) in the prior period to Monday (10 crashes) in the current period. Similarly, the peak hour for crashes moved from 5 PM (7 crashes) in the prior year to 3 PM (5 crashes) in the current year, indicating a change in the temporal distribution of incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities in either period. Total injuries saw a substantial decrease, falling from 14 in September 2023 to 5 in September 2024. The proportion of crashes resulting in 'No Injury' increased significantly from 59.6% to 85.4% year-over-year, while 'Possible Injury' crashes decreased from 8 to 1.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw notable shifts in crash counts year-over-year. Crashes attributed to 'Failed to yield right of way' increased from 4 to 8, and 'Disregarded traffic signs, signals, road markings' rose from 1 to 5. Conversely, crashes involving 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 3 to 1, and 'Followed too closely' decreased from 3 to 0.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Regarding lighting conditions, crashes occurring in 'Daylight' decreased from 33 in the prior period to 30 in the current period. Crashes during 'Dusk' also decreased from 3 to 1. For road surface conditions, incidents on 'Dry' roads decreased by 3 (from 37 to 34), and on 'Wet' roads decreased by 1 (from 8 to 7).
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field
Vehicles & Demographics
The representation of vehicle makes in crashes saw shifts, with TOYOTA increasing from 6 to 12 and becoming the most frequently involved make. HONDA decreased from 13 to 10, and NISSAN decreased from 7 to 4. In terms of persons involved, the 21-25 age group saw a decrease from 11 to 3, while the 26-34 age group increased from 10 to 20, and the 65+ age group increased from 10 to 18.
Top Vehicle Makes (72 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records
14 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (78 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones, which had the highest count, decreased from 23 to 19. Incidents in 5 mph, 20 mph, and 55 mph zones also saw decreases. Conversely, crashes in 30 mph zones increased from 4 to 6. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-09-01 through 2024-09-30 (30 days)
- Geographic scope: BEVERLY, MA
- Total crash records analyzed: 41
- Total persons involved: 91
- Total vehicles involved: 72
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). "BEVERLY, MA Crash Intelligence Report: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/beverly/september-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: 2024-09-01 – 2024-09-30
Generated: June 21, 2026 · All rights reserved