ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · EASTHAMPTON, MA · OCTOBER 2023
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/easthampton/october-2023-report
Monthly Traffic Safety Analysis
33 CRASHES IN
EASTHAMPTON, MA
OCTOBER 2023
In October 2023, EASTHAMPTON experienced 33 total crashes, an increase of 6.45% compared to the 31 crashes recorded in October 2022. Total injuries increased by 20%, rising from 5 to 6 individuals. The most notable shift was the doubling of crashes attributed to 'No improper driving' as a contributing factor, increasing from 8 to 16.
33
▲ 6.5%was 31
Total Crash Events
0
Persons Killed
6
▲ 20.0%was 5
Persons Injured
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 · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in EASTHAMPTON saw a slight increase year-over-year, with total crashes rising by 6.45% from 31 to 33. While total fatalities remained stable at zero in both periods, the number of injured persons increased by 20%, from 5 to 6. This indicates a minor upward trend in crash frequency and injury incidence.
1
Hit-and-Run Crashes — October 2023
▼ 0.0% vs prior (1)
The number of hit-and-run crashes remained stable at 1 in both October 2022 and October 2023. The hit-and-run rate experienced a slight decrease, moving from 3.2% in the prior period to 3% in the current period, primarily due to the overall increase in total crashes.
Vulnerable Road User Casualties
0
Motorists Killed
6
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Monday, with 7 crashes in October 2022, to Wednesday, with 8 crashes in October 2023. Similarly, the peak hour for crashes shifted from 6 PM (4 crashes) in the prior period to 3 PM (5 crashes) in the current period, indicating a change in the concentration of crash occurrences.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The distribution of crash severity showed some changes year-over-year. Crashes resulting in serious injuries (Severity A) decreased from 1 (3.2% of crashes) in October 2022 to 0 in October 2023. Crashes with minor injuries (Severity B) also decreased from 4 (12.9% of crashes) to 3 (9.1% of crashes), while crashes with possible injuries (Severity C) increased from 0 to 1 (3% of crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors saw significant shifts year-over-year. Crashes attributed to 'No improper driving' increased by 100% in count, rising from 8 to 16, and its share of crashes increased from 25.8% to 48.5%. Conversely, 'Inattention' decreased by 50% in count, from 6 to 3 crashes, with its share falling from 19.4% to 9.1%. 'Failed to yield right of way' also doubled in count, from 1 to 2 crashes, while the 'Distracted' factor, which accounted for 2 crashes in the prior period, was not recorded in the current period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under clear weather conditions increased from 21 to 24, while those in daylight increased from 21 to 25. The proportion of crashes on dry road surfaces also rose, from 71% (22 crashes) to 78.8% (26 crashes). This indicates a trend towards a higher proportion of crashes occurring under optimal weather, lighting, and road surface conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased slightly from 56 to 58. Among top vehicle makes, FORD involvement decreased by 7 vehicles, from 11 to 4, while SUBARU involvement increased by 7 vehicles, from 2 to 9. The age distribution of persons involved showed a notable increase in the 35-44 age group, rising from 4 to 14 persons, while the 55-64 age group decreased from 7 to 3 persons involved.
Top Vehicle Makes (58 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records
4 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (63 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones decreased by 5, from 11 to 6, between the two periods. In contrast, crashes in 30 mph zones increased by 3, from 7 to 10, and crashes in 35 mph zones increased by 4, from 7 to 11. Additionally, one crash occurred in a 65 mph zone in the current period, where none were recorded previously; no fatal crashes were reported in any speed zone in either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-10-01 through 2023-10-31 (31 days)
- Geographic scope: EASTHAMPTON, MA
- Total crash records analyzed: 33
- Total persons involved: 66
- Total vehicles involved: 58
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). "EASTHAMPTON, MA Crash Intelligence Report: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/easthampton/october-2023-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: 2023-10-01 – 2023-10-31
Generated: June 21, 2026 · All rights reserved