ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HAMPDEN, MA · 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/hampden/2023-annual-report
Yearly Traffic Safety Analysis
70 CRASHES IN
HAMPDEN, MA
2023
In 2023, Hampden recorded 70 total traffic crashes, a 16.7% increase from the 60 crashes reported in 2022. While the number of total injuries remained nearly the same, the number of crashes involving a driver suspected of being under the influence of alcohol more than doubled, rising from 3 in 2022 to 7 in 2023. There were no traffic fatalities reported in either year.
70
▲ 16.7%was 60
Total Crash Events
0
Persons Killed
13
▼ -7.1%was 14
Persons Injured
4
▲ 300.0%was 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Hampden showed an upward trend, increasing by 16.7% from 60 incidents in 2022 to 70 in 2023. Despite the rise in total collisions, the number of reported injuries saw a slight decrease from 14 to 13. There were no fatal crashes recorded in either period.
4
Hit-and-Run Crashes — 2023
▲ 300.0% vs prior (1)
Hit-and-run incidents saw a significant increase in 2023 compared to the prior year. The number of hit-and-run crashes quadrupled, rising from just 1 in 2022 to 4 in 2023. This pushed the hit-and-run rate up from 1.7% of all crashes in 2022 to 5.7% in 2023, indicating a clear upward trend for this type of collision.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
12
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 some shifts between the two years. While Friday remained a peak day for collisions in both 2023 (11 crashes) and 2022 (12 crashes), the peak hour for crashes moved later in the day, from 4 p.m. in 2022 (9 crashes) to 6 p.m. in 2023 (9 crashes). In 2023, crashes were more evenly distributed throughout the week, with Friday, Sunday, and Tuesday each recording 11 incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either 2022 or 2023. The overall severity of crashes decreased, with the proportion of incidents resulting in an injury falling from 20% (12 crashes) in 2022 to 14.3% (10 crashes) in 2023. Notably, the one serious injury crash recorded in 2022 was not repeated in 2023. Consequently, the share of crashes with no injuries increased from 80% in 2022 to 84.3% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, though their counts increased year-over-year. Crashes attributed to 'Failed to yield right of way' grew from 6 in 2022 to 9 in 2023, a 50% increase in count. Similarly, crashes involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' rose from 4 to 7 incidents, a 75% increase in count. 'Inattention' was cited as a factor in 5 crashes in both periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in both periods predominantly occurred in clear weather and on dry roads. In 2023, 75.7% of crashes (53 incidents) were on dry surfaces, compared to 76.7% (46 incidents) in 2022. The proportion of crashes happening in darkness was also similar, accounting for 28.6% of incidents in 2023 versus 30% in 2022. There was a slight increase in crashes during rainy conditions, which rose from 2 incidents in 2022 to 5 in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in crashes remained consistent, with Toyota, Chevrolet, and Ford in the top ranks for both years. The number of Toyotas involved in collisions saw a notable increase, rising from 11 vehicles in 2022 to 19 in 2023. The age demographics of persons involved in crashes were also stable, although the 55-64 age group saw an increase from 16 individuals involved in 2022 to 21 in 2023.
Top Vehicle Makes (116 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
9 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (121 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained largely consistent year-over-year. The 30 mph and 40 mph zones accounted for the majority of incidents in both periods, with crashes in 30 mph zones increasing from 33 to 39. Crashes in 40 mph zones held steady at 21 incidents. Notably, collisions in 35 mph zones more than doubled, increasing from 3 in 2022 to 7 in 2023. No fatal crashes were recorded in any speed zone during either year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: HAMPDEN, MA
- Total crash records analyzed: 70
- Total persons involved: 129
- Total vehicles involved: 116
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). "HAMPDEN, MA Crash Intelligence Report: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hampden/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved