ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPRINGFIELD, 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/springfield/2025-annual-report
Yearly Traffic Safety Analysis
2,974 CRASHES IN
SPRINGFIELD, MA
2025
In 2025, Springfield recorded 2,974 total vehicle crashes, a 16.6% increase from the 2,551 crashes recorded in 2024. While overall crashes and injuries rose, the most notable year-over-year shift was a sharp decline in crashes involving pedestrians and bicyclists; pedestrian-involved crashes fell from 54 to 17, and bicycle-involved crashes dropped from 34 to 6.
2,974
▲ 16.6%was 2,551
Total Crash Events
13
Persons Killed
1,394
▲ 19.1%was 1,170
Persons Injured
504
▲ 2.0%was 494
Hit-and-Run Crashes
Note: "Persons Killed" (13) counts individual fatalities across all crash events. "Fatal" in the severity table below (13) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 158 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
Traffic safety trends in Springfield show a notable increase in crash frequency year-over-year. Total crashes rose by 16.6% from 2,551 to 2,974, and the number of people injured increased by 19.1% from 1,170 to 1,394. The number of fatalities, however, remained unchanged at 13 for both periods.
504
Hit-and-Run Crashes — 2025
▲ 2.0% vs prior (494)
The absolute number of hit-and-run crashes increased slightly from 494 in 2024 to 504 in 2025. However, due to the larger increase in overall crashes, the hit-and-run rate trended downward. Hit-and-runs constituted 16.9% of all crashes in 2025, a decrease from the 19.4% rate observed in the prior year.
Vulnerable Road User Casualties
7
Pedestrians Killed
1
Cyclists Killed
5
Motorists Killed
0
Other Killed
9
Pedestrians Injured
8
Cyclists Injured
1,374
Motorists Injured
3
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 temporal patterns of crashes remained largely consistent between the two years. Friday was the peak day for crashes in both 2025 (480 crashes) and 2024 (433 crashes). The peak hour for crashes shifted slightly earlier, from 4 PM in 2024 (218 crashes) to 3 PM in 2025 (257 crashes), though the afternoon commute period continues to see the highest volume of incidents.
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
While the absolute number of fatal crashes was identical year-over-year at 13, the fatal crash rate as a percentage of all crashes decreased from 0.5% in 2024 to 0.4% in 2025. The proportion of crashes resulting in serious injuries also declined, from 1.8% to 1.3% of all incidents. Conversely, the share of crashes involving minor injuries increased from 19.0% to 20.4%.
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
The primary contributing factors to crashes remained consistent year-over-year, with 'Inattention,' 'No improper driving,' and 'Failed to yield right of way' as the top three in both periods. The count of crashes attributed to inattention grew by 24.0%, from 541 incidents in 2024 to 671 in 2025. Similarly, crashes involving failure to yield increased in count by 16.9%, from 367 to 429.
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
Compared to the prior year, a greater proportion of crashes in 2025 occurred under favorable conditions. The share of crashes taking place in daylight increased from 62.4% to 67.8% of the total. Likewise, incidents on dry road surfaces represented 81.4% of all crashes in 2025, up from a 76.7% share in 2024.
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 most frequently involved in crashes were largely unchanged, with Honda (873 vehicles) and Toyota (810 vehicles) remaining the top two. Ford (507 vehicles) moved into the third position, displacing Nissan from the prior year. The age distribution of all persons involved in crashes remained stable, with no significant shifts in representation among different age groups.
Top Vehicle Makes (5,903 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
1,212 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (6,444 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 crashes in both periods occurred in lower speed zones, with the largest year-over-year increases in crash counts seen in 25 mph zones (from 769 to 910) and 30 mph zones (from 737 to 836). Fatalities in 2025 were more concentrated in a single speed zone, with 8 of 13 deaths occurring in 30 mph zones. This compares to 2024, when fatalities were more distributed, with 4 deaths in 30 mph zones and 4 in 35 mph zones.
Fatal crashes by zone: 25 mph: 2 of 910 (0.22%) · 30 mph: 8 of 836 (0.957%) · 35 mph: 3 of 577 (0.52%)
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: SPRINGFIELD, MA
- Total crash records analyzed: 2,974
- Total persons involved: 7,775
- Total vehicles involved: 5,903
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: 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/springfield/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