ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BERKLEY, MA · 2025
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/berkley/2025-annual-report
Yearly Traffic Safety Analysis
130 CRASHES IN
BERKLEY, MA
2025
In 2025, Berkley recorded 130 total traffic crashes, a 12.2% decrease from the 148 crashes reported in 2024. Despite the overall reduction in collisions, the total number of injuries rose by 37.5%, increasing from 40 in the prior year to 55 in the current year. This increase in injuries occurred while the number of fatalities remained constant at one for both periods.
130
▼ -12.2%was 148
Total Crash Events
1
Persons Killed
55
▲ 37.5%was 40
Persons Injured
7
▲ 16.7%was 6
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in traffic collisions in Berkley shows a decrease year-over-year, with total crashes falling by 12.2% from 148 in 2024 to 130 in 2025. However, this was accompanied by a significant 37.5% increase in the number of people injured, which grew from 40 to 55. The number of fatalities remained unchanged, with one death recorded in each period.
7
Hit-and-Run Crashes — 2025
▲ 16.7% vs prior (6)
The number of hit-and-run incidents in Berkley saw a slight increase, rising from 6 crashes in 2024 to 7 in 2025. The hit-and-run rate, which measures the proportion of total crashes that are hit-and-runs, also trended upwards. This rate increased from 4.1% in the prior period to 5.4% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
2
Pedestrians Injured
1
Cyclists Injured
52
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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 Berkley showed some consistency and some shifts year-over-year. The peak hour for collisions remained 7 AM in both 2025 and 2024, with 13 and 15 crashes respectively. While Tuesday was the peak day in 2024 with 30 crashes, in 2025 it shared the top spot with Monday, both days recording 25 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the number of fatal crashes remained constant at one for both years, the overall severity of crashes increased in 2025. The fatal crash rate rose slightly from 0.68 to 0.77 per 100 crashes. The proportion of collisions resulting in a serious injury more than doubled, increasing from 3.4% (5 crashes) in 2024 to 8.5% (11 crashes) in 2025. Consequently, the share of non-injury crashes decreased from 75.0% in the prior year to 64.6% in the current year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor in both periods was 'No improper driving,' with counts of 41 in 2025 and 45 in 2024. A significant year-over-year shift was observed in crashes attributed to 'Followed too closely,' which saw its count increase by 87.5% from 8 to 15. Conversely, crashes involving 'Driving too fast for conditions' saw a substantial decrease, falling from 12 incidents in 2024 to just 2 in 2025. Crashes related to driver fatigue also saw a notable increase, rising from 1 to 6.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In both 2025 and 2024, the majority of crashes occurred in clear weather on dry roads during daylight hours. However, there was a notable decrease in crashes under adverse conditions in 2025. Collisions on wet roads fell from 24 to 13, and crashes in rainy conditions dropped from 15 to 4. Similarly, the number of crashes occurring on unlit dark roadways decreased from 43 in 2024 to 28 in 2025.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
Toyota, Ford, and Honda were the top three vehicle makes involved in crashes in both periods, with Toyota leading each year despite its count decreasing from 47 to 38. The ranking of the top makes remained largely stable. Analysis of persons involved shows a shift in age demographics; the 26-34 age group became the most frequently involved group in 2025 with 50 individuals, up from 44 in the prior year. Notably, the number of persons aged 65 and older involved in crashes more than doubled, increasing from 12 in 2024 to 27 in 2025.
Top Vehicle Makes (219 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
20 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (240 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
In both 2025 and 2024, the highest number of crashes occurred in 65 mph speed zones, though the count in this zone decreased from 62 to 44. The second most frequent zone for crashes was 35 mph in both years, also seeing a reduction from 34 to 28 incidents. The single fatal crash in each year occurred within a 65 mph zone. The fatality rate within this specific speed zone increased from 1.6% of its crashes in 2024 to 2.3% in 2025.
Fatal crashes by zone: 65 mph: 1 of 44 (2.273%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: BERKLEY, MA
- Total crash records analyzed: 130
- Total persons involved: 264
- Total vehicles involved: 219
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). "BERKLEY, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/berkley/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved