ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PITTSFIELD, MA · JANUARY 2024
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/january-2024-report
Monthly Traffic Safety Analysis
77 CRASHES IN
PITTSFIELD, MA
JANUARY 2024
Total crashes in Pittsfield, MA increased from 65 in January 2023 to 77 in January 2024, an 18.5% rise year-over-year. The most notable shift was a significant decrease in pedestrian crashes, which fell from 6 in the prior period to 1 in the current period.
77
▲ 18.5%was 65
Total Crash Events
1
Persons Killed
17
▼ -10.5%was 19
Persons Injured
1
Fatal Crash Events
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in Pittsfield increased year-over-year, with total crashes rising by 12, from 65 in January 2023 to 77 in January 2024, representing an 18.5% increase. Total fatalities remained stable at 1 in both periods, while total injuries decreased from 19 to 17, a 10.5% reduction.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
16
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · 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 14 crashes in January 2023 to Sunday with 18 crashes in January 2024, representing a six-fold increase for Sundays. The peak crash hour also moved from 4 PM with 6 crashes in the prior period to 1 PM with 8 crashes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at 1 in both January 2023 and January 2024, resulting in a slight decrease in the fatal crash rate from 1.54% to 1.3% due to the increased total crash count. Serious injury crashes (Severity A) increased from 0 in January 2023 to 2 in January 2024, while possible injury crashes (Severity C) decreased from 6 to 2.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, "No improper driving," saw a slight decrease from 15 crashes in January 2023 to 14 crashes in January 2024. "Inattention" crashes increased by 4, from 7 to 11, and "Disregarded traffic signs, signals, road markings" crashes saw a notable increase of 6, from 3 to 9. Conversely, "Failed to yield right of way" crashes decreased by 4, from 9 to 5.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather conditions increased from 37 to 39, while crashes in "Snow" conditions rose from 6 to 11, and "Cloudy" conditions increased from 5 to 12. Crashes during "Daylight" hours significantly increased from 33 to 49, whereas those in "Dark - lighted roadway" decreased from 24 to 20. On road surfaces, crashes on "Snow" surfaces notably increased from 8 to 23, while those on "Ice" surfaces decreased from 4 to 1.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 28, from 110 in January 2023 to 138 in January 2024. Toyota, Subaru, and Nissan all saw increased involvement, with Toyota rising from 21 to 28, Subaru from 7 to 14, and Nissan from 6 to 14. Among persons involved, the 0-15 age group saw a decrease from 12 to 8, and the 65+ age group decreased from 19 to 12.
Top Vehicle Makes (138 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Vehicle unit records
18 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (157 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Person-level records linked to crash events
Speed Limit Zones
The number of crashes in 25 mph zones remained stable at 12 in both periods, with one fatal crash recorded in this zone each year. Crashes in 30 mph zones increased from 22 in January 2023 to 34 in January 2024, while crashes in 35 mph zones slightly decreased from 21 to 19.
Fatal crashes by zone: 25 mph: 1 of 12 (8.333%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · 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: 2024-01-01 through 2024-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-01-31 (31 days)
- Geographic scope: PITTSFIELD, MA
- Total crash records analyzed: 77
- Total persons involved: 170
- Total vehicles involved: 138
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: January 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/pittsfield/january-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-01-01 – 2024-01-31
Generated: June 21, 2026 · All rights reserved