ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PITTSFIELD, MA · FEBRUARY 2026
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/february-2026-report
Monthly Traffic Safety Analysis
75 CRASHES IN
PITTSFIELD, MA
FEBRUARY 2026
Total crashes in February 2026 increased slightly to 75, up from 74 in February 2025, representing a 1.35% rise. The most significant shift was in crash outcomes, with total fatalities increasing from 0 to 1 and total injuries rising from 9 to 27, a 200% increase year-over-year.
75
▲ 1.4%was 74
Total Crash Events
1
Persons Killed
27
▲ 200.0%was 9
Persons Injured
7
▲ 40.0%was 5
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 · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash incidents in PITTSFIELD, MA show a slightly rising trend, with total crashes increasing from 74 in February 2025 to 75 in February 2026. This represents a 1.35% increase in the number of crashes.
7
Hit-and-Run Crashes — February 2026
▲ 40.0% vs prior (5)
Hit-and-run crashes increased from 5 incidents in February 2025 to 7 in February 2026. This resulted in the hit-and-run rate rising from 6.8% to 9.3% of all crashes, indicating an upward trend in these types of incidents.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
3
Pedestrians Injured
1
Cyclists Injured
23
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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 Wednesday (14 crashes) in February 2025 to Tuesday (17 crashes) in February 2026. The peak hour remained consistent at 4 PM for both periods, with 10 crashes recorded at that time in both February 2025 and February 2026.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity saw a notable increase, with fatal crashes rising from 0 in February 2025 to 1 in February 2026. Total injuries also surged from 9 to 27, marking a 200% increase year-over-year. The proportion of crashes resulting in no injury decreased from 79.7% (59 crashes) in the prior period to 69.3% (52 crashes) in the current period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Failed to yield right of way' saw a significant increase, rising from 5 crashes in February 2025 to 11 crashes in February 2026, a 120% increase in count. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' also increased substantially from 1 crash to 4 crashes, a 300% increase in count. Conversely, 'Followed too closely' decreased from 5 crashes to 2 crashes, a 60% decrease in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 37 to 49, while those in snowy conditions decreased from 13 to 4. Road surface conditions also showed a shift, with crashes on dry roads increasing from 38 to 54, and crashes on icy roads significantly decreasing from 12 to 1. Crashes during daylight hours increased from 49 to 54, while those at dusk decreased from 5 to 2.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 141 in February 2025 to 147 in February 2026, a 4.3% rise. Toyota remained the most involved make, with its count increasing from 19 to 30. Ford also saw increased involvement, rising from 12 to 19, while Chevrolet's involvement decreased from 15 to 7.
Top Vehicle Makes (147 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Vehicle unit records
21 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (151 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones decreased from 30 in February 2025 to 21 in February 2026. Crashes in 35 mph zones saw a slight increase from 18 to 19, with the only fatal crash in the current period occurring within a 35 mph zone. Additionally, crashes in 25 mph zones increased from 11 to 14.
Fatal crashes by zone: 35 mph: 1 of 19 (5.263%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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: 2026-02-01 through 2026-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-02-01 through 2026-02-28 (28 days)
- Geographic scope: PITTSFIELD, MA
- Total crash records analyzed: 75
- Total persons involved: 172
- Total vehicles involved: 147
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: February 2026." Published June 21, 2026. Reporting period: 2026-02-01 to 2026-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/pittsfield/february-2026-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: 2026-02-01 – 2026-02-28
Generated: June 21, 2026 · All rights reserved