ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NORTHAMPTON, 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/northampton/2024-annual-report
Yearly Traffic Safety Analysis
493 CRASHES IN
NORTHAMPTON, MA
2024
In 2024, Northampton recorded 493 total crashes, representing a 14.3% decrease from the 575 crashes reported in 2023. Despite the overall decline in collisions, total fatalities doubled from one to two, and the number of people injured increased from 153 to 161 during the same period.
493
▼ -14.3%was 575
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
161
▲ 5.2%was 153
Persons Injured
9
▼ -30.8%was 13
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 6 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 shows a notable decrease in total crashes, with a 14.3% drop from 575 in 2023 to 493 in 2024. However, this was accompanied by a 5.2% rise in total injuries (from 153 to 161) and an increase in fatalities from one to two, indicating a rise in crash severity.
9
Hit-and-Run Crashes — 2024
▼ -30.8% vs prior (13)
The number of hit-and-run incidents decreased from 13 in 2023 to 9 in 2024, a 30.8% reduction in count. The hit-and-run rate, as a percentage of total crashes, also trended down, falling from 2.3% in the prior year to 1.8% in the current year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
12
Pedestrians Injured
10
Cyclists Injured
137
Motorists Injured
2
Other 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 shifted year-over-year. In 2024, the peak day for crashes was Thursday with 94 incidents, a change from Tuesday (102 incidents) in 2023. The busiest hour for collisions also moved later in the day, from 2 p.m. (69 crashes) in the prior year to 4 p.m. (58 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
The severity of crashes increased from the prior year. The number of fatal crashes doubled from one to two, and the count of serious injury crashes rose from five to seven. As a share of all collisions, fatal crashes increased from 0.2% to 0.4%, and serious injury crashes grew from 0.9% to 1.4%. Consequently, the proportion of non-injury crashes fell slightly from 77.2% to 76.1%.
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 top contributing factor in both periods was 'Inattention,' though its count decreased by 25% from 148 incidents in 2023 to 111 in 2024. While remaining the third most common factor, 'Failed to yield right of way' incidents increased by 12.3% from 73 to 82. Crashes attributed to 'Followed too closely' saw a significant 38.9% drop in count, from 54 to 33 incidents.
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
In both periods, most crashes occurred during daylight on dry roads. The proportion of crashes happening in daylight was stable, at 77.3% in 2024 compared to 76.3% in 2023. There was a slight shift in weather, with the share of crashes in 'Clear' conditions decreasing from 67.6% of all crashes in 2023 to 61.5% in 2024.
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 top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained consistent year-over-year with similar counts. Analysis of persons involved in crashes shows that the 65+ age group saw an increase in representation from 230 individuals in 2023 to 249 in 2024. In contrast, the number of individuals aged 26-34 involved in crashes decreased from 211 to 194.
Top Vehicle Makes (1,058 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
57 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,266 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 remained most frequent in lower speed zones, particularly the 25 mph zone, though the count in this zone dropped from 210 to 166. In 2024, one of the two fatal crashes occurred in a 65 mph zone, which had no fatal crashes in 2023. The other 2024 fatality was in a 5 mph zone, whereas 2023's single fatal crash occurred in a 30 mph zone.
Fatal crashes by zone: 5 mph: 1 of 1 (100%) · 65 mph: 1 of 45 (2.222%)
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: NORTHAMPTON, MA
- Total crash records analyzed: 493
- Total persons involved: 1,341
- Total vehicles involved: 1,058
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). "NORTHAMPTON, 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/northampton/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