ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · AMHERST, 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/amherst/2023-annual-report
Yearly Traffic Safety Analysis
348 CRASHES IN
AMHERST, MA
2023
In 2023, Amherst recorded 348 total traffic crashes, a slight decrease from the 350 crashes reported in 2022. This represents a 0.6% year-over-year reduction in total collisions. The most significant change was the elimination of traffic fatalities, which dropped from 3 in the prior year to 0 in the current period.
348
▼ -0.6%was 350
Total Crash Events
0
▼ -100.0%was 3
Persons Killed
91
▼ -1.1%was 92
Persons Injured
11
▼ -8.3%was 12
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. 6 crashes with unreported severity are 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
Overall, traffic crash trends in Amherst remained stable year-over-year, with total crashes decreasing by just 0.6% from 350 in 2022 to 348 in 2023. Similarly, the number of persons injured saw a minimal decline from 92 to 91. The most positive trend was a reduction in total fatalities from 3 to 0.
11
Hit-and-Run Crashes — 2023
▼ -8.3% vs prior (12)
Hit-and-run incidents showed a slight downward trend in 2023. The total count of hit-and-run crashes decreased from 12 in 2022 to 11 in 2023. Correspondingly, the hit-and-run rate as a percentage of all crashes declined from 3.4% to 3.2%, suggesting a relatively stable trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
8
Pedestrians Injured
2
Cyclists Injured
81
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
Temporal crash patterns showed some shifts between the two periods. The peak day for crashes moved from Saturday in 2022 (64 crashes) to Friday in 2023 (64 crashes). The peak hour for collisions shifted two hours later, from 4 p.m. in the prior year (46 crashes) to 6 p.m. in the current year (34 crashes).
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
Crash severity outcomes improved significantly with the elimination of fatal crashes, which fell from 3 in 2022 to 0 in 2023. However, the number of crashes resulting in non-fatal injuries increased. Crashes involving serious injuries rose from 4 to 7, and those with minor injuries increased from 38 to 44. Consequently, the proportion of crashes involving any injury (serious, minor, or possible) grew from 18% of all crashes in 2022 to 21.3% 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 ranking of top contributing factors shifted year-over-year. In 2023, 'Inattention' became the leading factor, cited in 80 crashes, up from 77 in the prior year. 'No improper driving,' which was the top category in 2022 with 92 crashes, fell to second place with 76 crashes in 2023. Notably, crashes attributed to 'Failed to yield right of way' increased by 53% in count, from 30 incidents in 2022 to 46 in 2023, though it remained the third-ranked factor 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
The distribution of crashes across different environmental conditions remained largely consistent year-over-year. The number of crashes occurring in daylight was identical in both periods at 223 incidents. Similarly, crashes on dry roads (255 in 2023 vs. 254 in 2022) and in clear weather (228 vs. 222) were stable. There was a small decrease in crashes occurring on roads with snow or ice, which fell from a combined 29 incidents in 2022 to 20 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
Demographics of persons involved in crashes showed a shift among younger age groups. While the 21-25 age group remained the most represented, their involvement decreased from 192 individuals in 2022 to 173 in 2023. Conversely, the number of persons in the 16-20 age group increased from 124 to 150. The top vehicle makes involved in collisions remained consistent, with Toyota (121 vehicles) and Honda (98 vehicles) leading in 2023, similar to the prior year. Subaru (60 vehicles) replaced Ford as the third most common make.
Top Vehicle Makes (619 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
34 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (754 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 by speed limit remained similar, with the 35 mph zone accounting for the highest number of incidents in both 2022 (106 crashes) and 2023 (93 crashes). Crashes in 30 mph zones increased from 64 to 72, while those in 25 mph zones decreased slightly from 81 to 77. A significant improvement was the elimination of fatalities across all speed zones; in the prior year, fatal crashes had occurred in 25 mph, 30 mph, and 50 mph zones.
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: AMHERST, MA
- Total crash records analyzed: 348
- Total persons involved: 794
- Total vehicles involved: 619
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). "AMHERST, 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/amherst/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