ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BEVERLY, MA · MARCH 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/beverly/march-2023-report
Monthly Traffic Safety Analysis
44 CRASHES IN
BEVERLY, MA
MARCH 2023
In March 2023, BEVERLY experienced 44 crashes, a slight increase from 43 crashes in March 2022, representing a 2.3% rise. While total crashes saw a minor uptick, total injuries decreased by 36.4%, falling from 11 to 7. The most notable shift was a significant reduction in hit-and-run incidents, which dropped from 6 to 2.
44
▲ 2.3%was 43
Total Crash Events
0
Persons Killed
7
▼ -36.4%was 11
Persons Injured
2
▼ -66.7%was 6
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. 9 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the number of crashes in BEVERLY saw a slight increase of 2.3% year-over-year, rising from 43 in March 2022 to 44 in March 2023. Fatalities remained stable at zero in both periods. However, total injuries decreased by 36.4%, indicating a positive trend in injury reduction.
2
Hit-and-Run Crashes — March 2023
▼ -66.7% vs prior (6)
Hit-and-run crashes significantly decreased from 6 incidents in March 2022 to 2 incidents in March 2023, representing a 66.7% reduction. Consequently, the hit-and-run rate saw a substantial drop from 14% to 4.5% year-over-year. This indicates a positive downward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Motorists Killed
7
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Wednesday in both periods, with 10 crashes each. However, the peak hour for crashes shifted from 5 PM with 7 crashes in March 2022 to 10 AM with 6 crashes in March 2023. This suggests a change in the most crash-prone time of day.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both March 2022 and March 2023. Total injuries decreased from 11 to 7, a 36.4% reduction year-over-year. Minor injury crashes (severity B) decreased from 5 (11.6% share) to 2 (4.5% share), while crashes with no injury (severity O) increased from 25 (58.1% share) to 29 (65.9% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'Failed to yield right of way,' increased from 6 crashes in March 2022 to 8 crashes in March 2023, a 33.3% increase in count. 'Inattention' decreased from 7 crashes to 5 crashes, a 28.6% decrease in count. 'No improper driving' remained consistent with 7 crashes in both periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear/Clear' weather conditions decreased slightly from 28 to 26 year-over-year. Crashes during 'Daylight' decreased from 37 to 33, while those in 'Dark - lighted roadway' doubled from 4 to 8. Crashes on 'Dry' road surfaces increased from 32 to 36, while crashes on 'Wet' surfaces decreased from 7 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field
Vehicles & Demographics
The age group 16-20 saw an increase in persons involved from 6 in March 2022 to 10 in March 2023. Conversely, the 35-44 age group experienced a notable decrease from 15 to 6 persons involved. Ford remained the most frequently involved vehicle make, increasing from 9 to 10 vehicles, while Nissan dropped from 8 to 5 vehicles involved.
Top Vehicle Makes (76 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records
20 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (68 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones increased from 18 in March 2022 to 21 in March 2023. A significant increase was observed in 55 mph zones, rising from 1 crash to 7 crashes year-over-year. Crashes in 10 mph zones decreased from 6 to 2, and no fatalities were reported in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-03-01 through 2023-03-31 (31 days)
- Geographic scope: BEVERLY, MA
- Total crash records analyzed: 44
- Total persons involved: 90
- Total vehicles involved: 76
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: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/beverly/march-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: 2023-03-01 – 2023-03-31
Generated: June 21, 2026 · All rights reserved