Monthly Traffic Safety Analysis

20 CRASHES IN
BERLIN, MA
APRIL 2025

All metrics benchmarked againstApril 2024

Total crashes in BERLIN, MA for April 2025 increased to 20, an 81.82% rise from the 11 crashes recorded in April 2024. This significant increase in overall crash volume is the most notable year-over-year shift, with a substantial rise in crashes attributed to factors like 'Failure to keep in proper lane or running off road'.

20

81.8%was 11

Total Crash Events

0

Persons Killed

3

50.0%was 2

Persons Injured

0

-100.0%was 1

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 · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant increase in crashes year-over-year, with total crashes rising from 11 in April 2024 to 20 in April 2025. This represents an 81.82% increase in crash incidents for the month.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

3

Motorists Injured

Prior: 250.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Tuesday in April 2024 (4 crashes) to Saturday in April 2025 (4 crashes). Similarly, the peak crash hour moved from 1 PM in April 2024 (2 crashes) to 7 PM in April 2025 (2 crashes), indicating a shift in when crashes are most frequent.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both April 2024 and April 2025. Total injuries increased by 50%, from 2 in April 2024 to 3 in April 2025. While April 2024 reported 1 serious injury crash, April 2025 reported 3 possible injury crashes, with no serious injuries recorded in the current period.

Outcome by Severity (Crash Events)

Possible Injury3possible injury crashes15%
No Injury16no injury crashes80%
128.6%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Failure to keep in proper lane or running off road' saw a 250% increase, rising from 2 crashes in April 2024 to 7 crashes in April 2025, making it the top factor. 'No improper driving' crashes increased by 200%, from 1 to 3, and 'Distracted' crashes doubled from 1 to 2. Conversely, 'Followed too closely' crashes decreased by 50%, from 2 to 1. Factors like 'Inattention' and 'Driving too fast for conditions' were present in April 2025 with 1 crash each, but not in the prior period.

Officer-Reported Primary Contributing Cause

Failure to keep in proper lane or running off road7 (35%)
No improper driving3 (15%)
Distracted2 (10%)
Followed too closely1 (5%)
Inattention1 (5%)
Failed to yield right of way1 (5%)
Driving too fast for conditions1 (5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 6 in April 2024 to 13 in April 2025, and crashes on dry road surfaces rose from 9 to 16 during the same period. Crashes during daylight hours also increased from 10 to 13. There was a notable increase in crashes under dark conditions, from 1 in April 2024 to 5 in April 2025.

Weather

Clear9 (45.0%)
50.0%prior 6
Clear/Clear4 (20.0%)
Cloudy2 (10.0%)
Cloudy/Snow1 (5.0%)
Snow/Other1 (5.0%)
Snow/Snow1 (5.0%)
Clear/Unknown1 (5.0%)
Cloudy/Rain1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash

Lighting

Daylight13 (65.0%)
30.0%prior 10
Dark - unknown roadway lighting3 (15.0%)
Dark - roadway not lighted2 (10.0%)
Dusk2 (10.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field

Road Surface

Dry16 (80.0%)
77.8%prior 9
Wet2 (10.0%)
Ice1 (5.0%)
Slush1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (29 vehicles)

1
HONDA4 (13.8%)
2
NISSAN3 (10.3%)
3
LEXUS3 (10.3%)
4
HINO2 (6.9%)
5
SUBARU2 (6.9%)
6
DODGE2 (6.9%)
7
TOYOTA2 (6.9%)
8
MNNI1 (3.4%)
9
RAM1 (3.4%)
10
VOLKSWAGEN1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records

Sex Distribution (32 persons with recorded sex)

Male18 (56.3%)
50.0%prior 12
Female14 (43.8%)
55.6%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone increased from 1 in April 2024 to 4 in April 2025, while those in the 35 mph zone rose from 2 to 5. Crashes in the 65 mph zone also saw an increase from 2 to 5. A crash in the 5 mph zone was reported in April 2025, where none were reported in the prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-04-01 through 2025-04-30 (30 days)
  • Geographic scope: BERLIN, MA
  • Total crash records analyzed: 20
  • Total persons involved: 32
  • Total vehicles involved: 29

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). "BERLIN, MA Crash Intelligence Report: April 2025." Published June 21, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/berlin/april-2025-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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Berlin, MA Crash Report — April 2025 | ThatCarHitMe.com