ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · EASTHAMPTON, MA · 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/easthampton/2024-annual-report
Yearly Traffic Safety Analysis
265 CRASHES IN
EASTHAMPTON, MA
2024
In 2024, Easthampton recorded 265 total vehicle crashes, a 12.8% decrease from the 304 crashes reported in 2023. While overall collisions declined, the number of crashes involving a suspected drunk driver increased significantly. Crashes attributed to driving under the influence rose from 12 in the prior period to 21 in the current period, a 75% year-over-year increase.
265
▼ -12.8%was 304
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
60
▲ 1.7%was 59
Persons Injured
16
▲ 45.5%was 11
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. 8 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 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in traffic crashes in Easthampton shows a year-over-year decline. Total crashes fell from 304 in 2023 to 265 in 2024, representing a 12.8% reduction. Despite this decrease in total incidents, the number of resulting injuries remained stable, with 60 in the current period compared to 59 in the prior period, while fatalities dropped from one to zero.
16
Hit-and-Run Crashes — 2024
▲ 45.5% vs prior (11)
Hit-and-run incidents increased in both count and as a percentage of total crashes. The number of hit-and-run crashes rose from 11 in 2023 to 16 in 2024, a 45.5% increase. Consequently, the hit-and-run rate climbed from 3.6% of all crashes in the prior period to 6.0% in the current period, indicating a rising trend for this type of incident.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
59
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2024, Friday was the most frequent day for crashes with 43 incidents, a change from 2023 when Tuesday saw the highest volume at 52 crashes. The peak hour for collisions also shifted slightly, moving from the 4 p.m. hour (30 crashes) in the prior year to the 5 p.m. hour (28 crashes) in the current year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity improved year-over-year, with fatal crashes decreasing from one in 2023 to zero in 2024. The number of crashes resulting in serious injuries also fell slightly from 4 to 3. The proportion of crashes involving minor injuries increased from a 10.2% share to an 11.3% share of all incidents, while the share of non-injury crashes remained stable at approximately 80% in both periods.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent year-over-year, with 'No improper driving' and 'Inattention' being the top two cited causes in both periods. The count for 'Inattention' as a factor decreased from 53 crashes in 2023 to 48 in 2024, a 9.4% drop in count. Similarly, incidents involving 'Failed to yield right of way' and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' both saw a 25% decrease in count, dropping from 16 to 12 crashes each.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in both periods predominantly occurred in clear weather on dry roads during daylight hours. The proportion of crashes on dry road surfaces was unchanged at 79.6% year-over-year. However, there was a shift in lighting conditions, with the share of crashes in 'Daylight' decreasing from 73.7% to 69.1%, while those in 'Dark - lighted roadway' conditions increased from 20.1% to 23.8%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes showed a consistent pattern, with Toyota, Ford, and Honda being the top three in both years. The number of Toyotas involved decreased from 108 to 74, while the count for Fords remained unchanged at 63. The age distribution of persons involved in crashes also remained stable, with the 26-34 age group being the largest cohort in both 2023 (106 persons) and 2024 (91 persons).
Top Vehicle Makes (492 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
76 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (496 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained largely consistent year-over-year. In both periods, the highest number of incidents occurred in 35 mph zones (75 in 2024 vs. 79 in 2023) and 30 mph zones (57 in 2024 vs. 66 in 2023). There was no significant shift of crashes into higher or lower speed zones. The single fatal crash in 2023 occurred in a 30 mph zone, while no fatal crashes were recorded in any speed zone in 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: EASTHAMPTON, MA
- Total crash records analyzed: 265
- Total persons involved: 577
- Total vehicles involved: 492
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/easthampton/2024-annual-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 – 2024-12-31
Generated: June 21, 2026 · All rights reserved