ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HOLYOKE, MA · 2025
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/holyoke/2025-annual-report
Yearly Traffic Safety Analysis
1,065 CRASHES IN
HOLYOKE, MA
2025
In 2025, Holyoke recorded 1,065 total traffic crashes, an 11.4% increase from the 956 crashes reported in 2024. This rise was accompanied by a significant increase in crash severity. The most notable year-over-year change was a fourfold increase in traffic fatalities, which rose from 2 in 2024 to 8 in 2025.
1,065
▲ 11.4%was 956
Total Crash Events
8
▲ 300.0%was 2
Persons Killed
436
▲ 38.4%was 315
Persons Injured
131
Hit-and-Run Crashes
Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 16 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Holyoke worsened year-over-year. Total crashes increased by 11.4% from 956 to 1,065. The number of people injured rose more sharply by 38.4%, from 315 to 436, while total fatalities increased from 2 to 8.
131
Hit-and-Run Crashes — 2025
▼ 0.0% vs prior (131)
The total number of hit-and-run incidents remained constant at 131 for both 2024 and 2025. However, due to the overall increase in total crashes in 2025, the hit-and-run rate as a percentage of all crashes decreased. The rate trended down from 13.7% in 2024 to 12.3% in 2025.
Vulnerable Road User Casualties
2
Pedestrians Killed
2
Cyclists Killed
4
Motorists Killed
0
Other Killed
20
Pedestrians Injured
7
Cyclists Injured
404
Motorists Injured
5
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes showed some changes between the two periods. While the peak hour for collisions remained the 3 p.m. hour in both years, the peak day shifted from Monday (154 crashes) in 2024 to Friday (183 crashes) in 2025. The number of crashes during the peak 3 p.m. hour also increased from 87 to 101.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased significantly in 2025 compared to the prior year. The number of fatal crashes quadrupled from 2 to 8, raising the fatal crash rate from 0.2% to 0.8% of all collisions. The proportion of crashes resulting in any level of injury also grew, accounting for 28.4% of all incidents in 2025, up from 23.1% in 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' remained the most common factor listed in both years, its count decreased from 319 to 302. Conversely, several other contributing factors saw large increases in count, most notably 'Disregarded traffic signs, signals, road markings,' which more than doubled from 29 to 72 incidents. Crashes attributed to 'Followed too closely' also rose by 37.3% (from 59 to 81), and 'Failed to yield right of way' increased by 22.2% (from 108 to 132).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across lighting and road surface conditions remained broadly similar year-over-year, with most incidents occurring in daylight on dry roads in both periods. However, the number of crashes on wet road surfaces increased from 128 in 2024 to 172 in 2025. Similarly, crashes during rainy weather rose from 55 to 94 incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes were consistent, with Toyota, Honda, and Ford being the top three in both years, though Toyota (304 vehicles) surpassed Honda (249 vehicles) for the top spot in 2025. Analysis of persons involved shows increases across all age groups, but the largest year-over-year growth occurred in the 45-54 age group, which saw a 31.7% increase in involvement (from 252 to 332 people), and the 35-44 age group, which saw a 22.6% increase (from 359 to 440 people).
Top Vehicle Makes (1,964 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
222 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,434 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The majority of the year-over-year increase in crashes occurred in 25 mph zones, where incidents rose from 545 to 648. Crashes in 65 mph zones remained stable with 126 incidents, but these crashes became more severe, accounting for 3 fatalities in 2025 compared to zero in 2024. Conversely, crashes in 35 mph zones decreased from 104 to 84, though this zone recorded one fatal crash in 2025 where there were none the previous year.
Fatal crashes by zone: 25 mph: 3 of 648 (0.463%) · 30 mph: 1 of 63 (1.587%) · 35 mph: 1 of 84 (1.19%) · 65 mph: 3 of 126 (2.381%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: HOLYOKE, MA
- Total crash records analyzed: 1,065
- Total persons involved: 2,638
- Total vehicles involved: 1,964
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). "HOLYOKE, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/holyoke/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved