Monthly Traffic Safety Analysis

14 CRASHES IN
BERKLEY, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

Total crashes in BERKLEY, MA increased from 9 in February 2023 to 14 in February 2024, marking a 55.6% rise year-over-year. The most notable shift was this increase in overall crash incidents, despite a decrease in the total number of injuries.

14

55.6%was 9

Total Crash Events

0

Persons Killed

3

-25.0%was 4

Persons Injured

0

Fatal Crash Events

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in BERKLEY, MA saw a substantial increase, rising by 55.6% from 9 crashes in February 2023 to 14 crashes in February 2024. Despite this increase in crash volume, the total number of injuries decreased by 25%, from 4 injuries in the prior period to 3 in the current period. Fatalities remained at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

3

Motorists Injured

Prior: 4-25.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak day moving from Wednesday (3 crashes) in February 2023 to Tuesday (7 crashes) in February 2024. The peak crash hour also changed, with February 2023 seeing 2 crashes at 6 AM, while February 2024 recorded 3 crashes each at 5 PM and 6 PM. This indicates a shift in crash concentration from early morning to evening hours.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes increased, the number of injured persons decreased from 4 in February 2023 to 3 in February 2024, resulting in a lower injury rate per crash (44.4% in prior period vs. 21.4% in current period). In February 2023, 1 crash involved a Minor Injury, whereas in February 2024, 1 crash involved a Minor Injury and 2 crashes involved Possible Injuries. There were no fatal crashes or fatalities in either period.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes7.1%
0.0%prior 1
Possible Injury2possible injury crashes14.3%
No Injury11no injury crashes78.6%
57.1%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record

Top Contributing Factors

The factor 'No improper driving' remained the most frequently cited, increasing from 4 crashes in February 2023 to 5 crashes in February 2024. 'Followed too closely' also saw an increase, from 1 crash in the prior period to 2 crashes in the current period. Factors such as 'Driving too fast for conditions' (2 crashes) and 'Failed to yield right of way' (1 crash) were present in February 2023 but not in February 2024, while new factors like 'Inattention' and 'Distracted' each contributed to 1 crash in February 2024.

Officer-Reported Primary Contributing Cause

No improper driving5 (35.7%)
Followed too closely2 (14.3%)
History heart/epilepsy/fainting1 (7.1%)
Inattention1 (7.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (7.1%)
Over-correcting/over-steering1 (7.1%)
Distracted1 (7.1%)
Physical impairment1 (7.1%)
Fatigued/asleep1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 6 in February 2023 to 8 in February 2024, and those in 'Snow' conditions also rose from 2 to 4 crashes. For lighting conditions, crashes during 'Daylight' increased from 4 to 7, and those in 'Dark - roadway not lighted' conditions increased from 2 to 5. The number of crashes on 'Dry' road surfaces increased from 6 to 10, while crashes on 'Snow' surfaces remained consistent at 2 in both periods.

Weather

Clear8 (57.1%)
33.3%prior 6
Snow4 (28.6%)
Cloudy2 (14.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash

Lighting

Daylight7 (50.0%)
Dark - roadway not lighted5 (35.7%)
Dark - unknown roadway lighting1 (7.1%)
Dusk1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field

Road Surface

Dry10 (71.4%)
66.7%prior 6
Ice2 (14.3%)
Snow2 (14.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (19 vehicles)

1
HONDA6 (31.6%)
2
CHEVROLET3 (15.8%)
3
TOYOTA2 (10.5%)
4
HYUNDAI1 (5.3%)
5
JEEP1 (5.3%)
6
NISSAN1 (5.3%)
7
STRN1 (5.3%)
8
SUBARU1 (5.3%)
9
VOLKSWAGEN1 (5.3%)
10
CHRYSLER1 (5.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records

Sex Distribution (20 persons with recorded sex)

Male15 (75.0%)
150.0%prior 6
Female4 (20.0%)
-63.6%prior 11
X / Unspecified1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone increased from 4 in February 2023 to 6 in February 2024, representing the highest number of crashes in any single speed zone for the current period. Crashes in the 25 mph speed zone doubled from 1 to 2, and new crashes were recorded in the 20 mph (1 crash) and 30 mph (1 crash) zones in February 2024, which had no crashes in the prior period. The 35 mph and 40 mph zones maintained the same crash counts year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-02-01 through 2024-02-29 (29 days)
  • Geographic scope: BERKLEY, MA
  • Total crash records analyzed: 14
  • Total persons involved: 22
  • Total vehicles involved: 19

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: February 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/berkley/february-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

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Berkley, MA Crash Report — February 2024 | ThatCarHitMe.com