ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BEVERLY, 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/beverly/october-2024-report
Monthly Traffic Safety Analysis
55 CRASHES IN
BEVERLY, MA
OCTOBER 2024
In October 2024, Beverly experienced 55 crashes, a 27.9% increase compared to the 43 crashes recorded in October 2023. Total injuries saw a significant rise, increasing by 171.4% from 7 in the prior year to 19 in the current period. This marks a notable upward trend in both crash frequency and injury severity year-over-year.
55
▲ 27.9%was 43
Total Crash Events
0
Persons Killed
19
▲ 171.4%was 7
Persons Injured
7
▲ 75.0%was 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. 1 crash with unreported severity is 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 activity in Beverly showed an upward trend year-over-year, with total crashes increasing by 27.9% from 43 in October 2023 to 55 in October 2024. Total injuries also rose substantially, from 7 in the prior period to 19 in the current period, representing a 171.4% increase. Fatalities remained at zero in both periods.
7
Hit-and-Run Crashes — October 2024
▲ 75.0% vs prior (4)
Hit-and-run crashes increased by 75% year-over-year, rising from 4 incidents in October 2023 to 7 in October 2024. Correspondingly, the hit-and-run rate increased from 9.3% of total crashes in the prior period to 12.7% in the current period, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
0
Other Killed
1
Pedestrians Injured
17
Motorists Injured
1
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 temporal patterns of crashes shifted year-over-year. The peak day for crashes moved from Sunday, with 11 crashes in October 2023, to Wednesday, with 16 crashes in October 2024. The peak hour for crashes also shifted slightly from 4 p.m. in October 2023 to 3 p.m. in October 2024, with both hours recording 7 crashes.
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
While there were no fatalities in either period, total injuries increased by 171.4%, rising from 7 in October 2023 to 19 in October 2024. Serious injuries (Severity A) increased from 0 to 2, and minor injuries (Severity B) increased from 1 to 5, a 400% change in count. Crashes resulting in possible injury (Severity C) also rose from 5 to 7, a 40% change in count.
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
Contributing factors saw notable shifts year-over-year. Crashes attributed to 'Followed too closely' increased significantly from 1 in October 2023 to 7 in October 2024, a 600% change in count. Conversely, crashes where 'Failed to yield right of way' was a factor decreased from 11 in the prior period to 6 in the current period, a 45.5% change in count. Additionally, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' appeared as a contributing factor for 5 crashes in the current period, not being listed in the prior period's factors.
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 wet road surfaces decreased from 9 in October 2023 to 5 in October 2024, representing a 44.4% decrease in count. Daylight crashes increased from 27 to 42, while crashes in dark-lighted roadway conditions slightly decreased from 11 to 10. The proportion of crashes occurring in clear weather conditions remained dominant in both periods.
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
The total number of vehicles involved in crashes increased by 22.6%, from 84 in October 2023 to 103 in October 2024. Toyota and Honda vehicles saw significant increases in crash involvement, with Toyota increasing from 8 to 17 (a 112.5% change in count) and Honda from 7 to 15 (a 114.3% change in count). These shifts resulted in Toyota and Honda becoming the top two vehicle makes involved in crashes, displacing Ford.
Top Vehicle Makes (103 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (121 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 occurring in 25 mph speed zones decreased from 25 in October 2023 to 21 in October 2024, a 16% change in count. Conversely, crashes in 55 mph speed zones doubled, increasing from 2 to 4. Crashes in 15 mph zones also saw a 200% increase, rising from 1 to 3.
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: BEVERLY, MA
- Total crash records analyzed: 55
- Total persons involved: 166
- Total vehicles involved: 103
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: 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/beverly/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