ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PITTSFIELD, MA · APRIL 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/pittsfield/april-2025-report
Monthly Traffic Safety Analysis
70 CRASHES IN
PITTSFIELD, MA
APRIL 2025
Total crashes in PITTSFIELD, MA increased from 59 in April 2024 to 70 in April 2025, marking an 18.64% rise year-over-year. This period also saw a significant shift in outcomes, with fatalities increasing from 0 to 1. Concurrently, total injuries rose by 33.33%, from 12 to 16.
70
▲ 18.6%was 59
Total Crash Events
1
Persons Killed
16
▲ 33.3%was 12
Persons Injured
3
▲ 50.0%was 2
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. 2 crashes with unreported severity are 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 rise in crash incidents year-over-year in PITTSFIELD, MA. Total crashes increased by 11, from 59 in April 2024 to 70 in April 2025, representing an 18.64% increase. This increase was accompanied by a rise in both fatalities and injuries.
3
Hit-and-Run Crashes — April 2025
▲ 50.0% vs prior (2)
Hit-and-run crashes increased from 2 in April 2024 to 3 in April 2025. The hit-and-run rate also rose from 3.4% to 4.3% of all crashes, indicating an upward trend in such incidents.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Pedestrians Injured
1
Cyclists Injured
15
Motorists Injured
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 Friday, with 12 crashes in April 2024, to Wednesday, with 19 crashes in April 2025. Similarly, the peak hour for crashes moved from 5 PM (6 crashes) in the prior period to 4 PM (9 crashes) in the current period. Crashes on Wednesday saw a substantial increase from 8 to 19, while Friday crashes decreased from 12 to 8.
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
The most notable change in severity was the increase in fatal crashes from 0 in April 2024 to 1 in April 2025. The total number of injured persons increased from 12 to 16 year-over-year. While minor injuries (severity B) decreased from 7 to 5, possible injuries (severity C) more than doubled from 3 to 8.
Outcome by Severity (Crash Events)
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
Among contributing factors, 'Failed to yield right of way' saw the largest count increase, rising from 3 crashes in April 2024 to 9 crashes in April 2025, a 200% increase. 'No improper driving' increased from 15 to 19 crashes (26.7% increase), becoming the most frequent factor in the current period. Conversely, 'Inattention' crashes decreased from 15 to 13 (13.3% decrease), and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' was a factor in 3 crashes in the prior period but 0 in the current.
Officer-Reported Primary Contributing Cause
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
The current period saw a higher proportion of crashes occurring in clear weather and on dry roads, with clear weather crashes increasing from 36 to 56 and dry road crashes from 44 to 63. Adverse weather conditions like snow and ice, which were present in April 2024 (e.g., 3 snow/sleet weather crashes, 3 ice road surface crashes), were not recorded as factors in the current period. Crashes occurring in daylight increased from 42 to 55, while those in dark-lighted conditions decreased from 11 to 8.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 104 to 139, a 33.65% rise. Toyota vehicles involved in crashes doubled from 11 to 22, making it the top make in the current period, while Nissan involvement decreased from 15 to 8. The number of male persons involved increased from 70 to 80, and female persons from 45 to 64, with notable increases in the 16-20 (from 10 to 18) and 65+ (from 16 to 23) age groups.
Top Vehicle Makes (139 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records
21 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (144 persons with recorded sex)
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 35 mph speed zone decreased from 19 in April 2024 to 8 in April 2025, but this zone recorded the only fatal crash in the current period. Conversely, crashes in the 30 mph zone increased from 15 to 24, and in the 25 mph zone from 13 to 21. This indicates a shift in crash distribution, with more incidents occurring in lower speed limit areas in the current period, despite the fatal crash occurring in a 35 mph zone.
Fatal crashes by zone: 35 mph: 1 of 8 (12.5%)
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: PITTSFIELD, MA
- Total crash records analyzed: 70
- Total persons involved: 163
- Total vehicles involved: 139
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). "PITTSFIELD, 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/pittsfield/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-04-01 – 2025-04-30
Generated: June 21, 2026 · All rights reserved