ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BEVERLY, MA · 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/2023-annual-report
Yearly Traffic Safety Analysis
540 CRASHES IN
BEVERLY, MA
2023
In 2023, Beverly recorded 540 total crashes, a 2.5% decrease from the 554 crashes reported in 2022. Total injuries also saw a decline, from 138 to 116, a 15.9% reduction. The most significant change was the reduction in traffic fatalities, with zero recorded in 2023 compared to one in the prior year.
540
▼ -2.5%was 554
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
116
▼ -15.9%was 138
Persons Injured
42
▼ -23.6%was 55
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. 91 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Beverly showed a slight downward trend year-over-year, decreasing by 2.5% from 554 incidents in 2022 to 540 in 2023. The number of people injured in these crashes also decreased by 15.9%, from 138 to 116. This indicates a modest improvement in overall road safety metrics compared to the previous year.
42
Hit-and-Run Crashes — 2023
▼ -23.6% vs prior (55)
Hit-and-run incidents in Beverly decreased in 2023 compared to the prior year. The total number of hit-and-run crashes fell from 55 in 2022 to 42 in 2023, a reduction of 23.6%. Consequently, the hit-and-run rate, representing the proportion of all crashes that were hit-and-runs, also declined from 9.9% to 7.8%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
7
Pedestrians Injured
3
Cyclists Injured
104
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in Beverly saw some shifts between 2022 and 2023. The peak day for crashes moved from Friday (95 crashes) in 2022 to Wednesday (99 crashes) in 2023. The evening commute remains the most hazardous time, with the peak hour shifting slightly later from 4 PM in 2022 (51 crashes) to 5 PM in 2023 (53 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity in Beverly improved in 2023, with zero fatal crashes compared to one in 2022. The overall proportion of crashes resulting in any injury also declined, from 21.1% of all crashes in 2022 to 17.0% in 2023. Specifically, crashes classified as 'Minor Injury' and 'Possible Injury' saw their share of total incidents decrease, while 'Serious Injury' crashes remained stable at 0.9% of the total in both years.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes in Beverly remained consistent, with 'Failed to yield right of way' and 'Inattention' following 'No improper driving' in both years. However, the count for 'Failed to yield right of way' increased by 15.6%, from 64 incidents in 2022 to 74 in 2023. Conversely, crashes attributed to 'Inattention' decreased by 17.4% (from 46 to 38), and incidents related to 'Disregarded traffic signs, signals, road markings' fell by 50% from 26 to 13.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The environmental conditions during crashes remained largely consistent between 2022 and 2023. In both periods, approximately 77% of crashes occurred on dry roads and about 67% happened during daylight hours. Crashes on wet road surfaces accounted for 17.4% of the total in 2023, nearly identical to the 17.5% recorded in 2022, suggesting that changes in overall crash numbers are not strongly linked to year-over-year variations in conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
In 2023, Toyota and Honda were tied as the most common vehicle makes involved in crashes, with 128 vehicles each, representing an increase for both brands over 2022. Ford, the third most common make, saw its involvement decrease from 99 vehicles in 2022 to 79 in 2023. Demographically, there was a decrease in the number of people involved in crashes across most age brackets, most notably a 22% reduction for the 26-34 age group (from 179 to 139 persons).
Top Vehicle Makes (982 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
247 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (962 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes by speed limit showed mixed changes. While the 25 mph zone remained the location for the highest number of crashes, incidents in this zone decreased from 295 in 2022 to 278 in 2023. Conversely, crashes in 30 mph zones increased from 102 to 115, and incidents in 55 mph zones rose from 28 to 45. The single fatal crash in 2022 occurred in a 25 mph zone, while 2023 saw no fatalities in any speed zone.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: BEVERLY, MA
- Total crash records analyzed: 540
- Total persons involved: 1,197
- Total vehicles involved: 982
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/beverly/2023-annual-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved