ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPRINGFIELD, MA · NOVEMBER 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/springfield/november-2025-report
Monthly Traffic Safety Analysis
217 CRASHES IN
SPRINGFIELD, MA
NOVEMBER 2025
Total crashes in Springfield, MA decreased from 226 in November 2024 to 217 in November 2025, representing a 3.98% reduction. Concurrently, total injuries saw a more significant decline, dropping from 112 to 82, a decrease of 26.79%. A notable shift was the absence of pedestrian and bicycle crashes in November 2025, compared to 6 pedestrian crashes and 3 bicycle crashes in November 2024.
217
▼ -4.0%was 226
Total Crash Events
0
Persons Killed
82
▼ -26.8%was 112
Persons Injured
28
▼ -37.8%was 45
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 · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for November 2025 indicates a downward trend compared to November 2024. Total crashes decreased by 9 incidents, a 3.98% reduction year-over-year. Fatalities remained at zero in both periods, while total injuries significantly decreased by 30, a 26.79% decline.
28
Hit-and-Run Crashes — November 2025
▼ -37.8% vs prior (45)
Hit-and-run crashes decreased from 45 in November 2024 to 28 in November 2025, representing a 37.78% reduction in count. The hit-and-run rate also decreased, falling from 19.9% of all crashes in November 2024 to 12.9% in November 2025.
Vulnerable Road User Casualties
0
Motorists Killed
82
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Friday (46 crashes) in November 2024 to Saturday (47 crashes) in November 2025. Friday crashes notably decreased from 46 to 25, while Monday crashes increased from 21 to 31. The peak hour for crashes also shifted from 3 PM (23 crashes) in November 2024 to 5 PM (21 crashes) in November 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities in either November 2024 or November 2025. Total injuries decreased from 112 to 82, a 26.79% reduction. Serious injuries (Severity A) decreased from 6 (2.7% share of crashes) to 3 (1.4% share), and minor injuries (Severity B) decreased from 56 (24.8% share) to 38 (17.5% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor shifted from 'No improper driving' (51 crashes, 22.6% share) in November 2024 to 'Inattention' (53 crashes, 24.4% share) in November 2025. 'No improper driving' crashes decreased by 23, while 'Inattention' crashes increased by 15. Crashes due to 'Followed too closely' increased by 9, from 13 to 22, and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased by 4, from 6 to 10.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions decreased from 157 in November 2024 to 148 in November 2025, while those in 'Rain' conditions slightly increased from 19 to 21. For lighting conditions, crashes during 'Daylight' increased from 119 to 123, and crashes in 'Dark - lighted roadway' decreased from 97 to 77. Crashes on 'Wet' road surfaces decreased from 47 to 33, while those on 'Dry' surfaces increased from 177 to 182.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes slightly increased from 424 to 430. Honda remained the top make involved, though its count decreased from 66 to 60, while Toyota also saw a decrease from 60 to 50. Hyundai and Chevrolet saw increases in involvement, with Hyundai rising from 24 to 35 and Chevrolet from 19 to 33. The age group '26-34' saw an increase in persons involved, from 81 to 102, while the '16-20' and '35-44' age groups saw decreases.
Top Vehicle Makes (430 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records
89 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (447 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events
Speed Limit Zones
The highest number of crashes shifted from 30 mph and 35 mph zones (63 crashes each) in November 2024 to the 25 mph zone (69 crashes) in November 2025. Crashes in 35 mph zones saw a significant decrease from 63 to 37, while those in 55 mph zones increased from 14 to 27. No fatal crashes were recorded in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-11-01 through 2025-11-30 (30 days)
- Geographic scope: SPRINGFIELD, MA
- Total crash records analyzed: 217
- Total persons involved: 549
- Total vehicles involved: 430
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). "SPRINGFIELD, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/november-2025-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: 2025-11-01 – 2025-11-30
Generated: June 21, 2026 · All rights reserved