ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · EASTHAM, 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/eastham/2024-annual-report
Yearly Traffic Safety Analysis
137 CRASHES IN
EASTHAM, MA
2024
In Eastham, total traffic crashes remained nearly stable, decreasing from 138 in the prior year to 137 in the current year, a change of less than 1%. There were no fatalities recorded in either period. The most notable year-over-year shift was in crash severity, with a significant decrease in serious injury crashes from 6 to 2, alongside an increase in minor injury crashes from 12 to 22.
137
▼ -0.7%was 138
Total Crash Events
0
Persons Killed
47
▼ -2.1%was 48
Persons Injured
6
▲ 50.0%was 4
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. 4 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
Overall crash trends in Eastham were stable year-over-year. The total number of crashes decreased by a single incident from 138 to 137. Similarly, the total number of injuries saw a marginal decline from 48 to 47, while fatalities remained at zero for both periods.
6
Hit-and-Run Crashes — 2024
▲ 50.0% vs prior (4)
Hit-and-run crashes trended upward in the current year compared to the prior year. The absolute number of hit-and-run incidents increased by 50%, from 4 to 6. This pushed the hit-and-run rate from 2.9% of all crashes in the prior period to 4.4% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
2
Cyclists Injured
44
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 temporal patterns of crashes showed consistency between the two periods. Monday remained the peak day for crashes, with the count increasing from 23 to 28. The peak hour for incidents shifted slightly earlier from 12 p.m. in the prior year to 11 a.m. 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
There were no fatal crashes in either period. A significant shift occurred in the distribution of injury severity, with serious injury crashes decreasing from 6 to 2, while minor injury crashes increased from 12 to 22. Consequently, the share of crashes involving any level of injury (serious, minor, or possible) increased from 20.2% to 24.1% of total crashes.
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 for crashes shifted year-over-year. The count of crashes attributed to "Inattention" decreased significantly from 53 to 32, while crashes with "No improper driving" cited increased from 23 to 34. This change caused "Inattention" to drop from the top-ranked factor to the second-ranked, replaced by "No improper driving".
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
Crash conditions remained largely consistent, with the majority of incidents in both years occurring in daylight and on dry roads. The proportion of crashes on dry roads was stable at 84.7% in the current year compared to 86.2% previously. A notable change was observed in lighting conditions, where crashes on dark, lighted roadways tripled from 4 to 12 incidents.
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
Toyota was the vehicle make most frequently involved in crashes during both periods, though its count decreased from 52 to 46. In terms of demographics of persons involved, there was a significant decrease in the 65+ age group, which fell from 83 individuals in the prior year to 51 in the current year. Conversely, involvement for the 55-64 age group increased from 44 to 53 persons.
Top Vehicle Makes (249 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (329 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
Crashes shifted towards higher speed zones year-over-year. Incidents in 40 mph zones, the most frequent location for crashes, increased from 79 to 85. In contrast, crashes in 30 mph zones saw a decrease from 28 to 23. No fatal crashes were recorded in any speed zone during either period.
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: EASTHAM, MA
- Total crash records analyzed: 137
- Total persons involved: 344
- Total vehicles involved: 249
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). "EASTHAM, 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/eastham/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