ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPRINGFIELD, MA · NOVEMBER 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/springfield/november-2023-report
Monthly Traffic Safety Analysis
376 CRASHES IN
SPRINGFIELD, MA
NOVEMBER 2023
In November 2023, Springfield recorded 376 total crashes, a slight decrease of 1.3% compared to the 381 crashes in November 2022. The most significant year-over-year shift was in fatalities, which increased from 0 in November 2022 to 4 in November 2023.
376
▼ -1.3%was 381
Total Crash Events
4
Persons Killed
165
▼ -17.9%was 201
Persons Injured
39
▲ 2.6%was 38
Hit-and-Run Crashes
Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 10 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes in November decreased slightly year-over-year, from 381 crashes in 2022 to 376 crashes in 2023, representing a 1.3% reduction. However, this period saw a notable increase in crash severity, with fatalities rising from 0 to 4.
39
Hit-and-Run Crashes — November 2023
▲ 2.6% vs prior (38)
Hit-and-run crashes increased slightly from 38 in November 2022 to 39 in November 2023. The hit-and-run rate also saw a minor increase, rising from 10.0% of total crashes in 2022 to 10.4% in 2023.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
4
Pedestrians Injured
1
Cyclists Injured
160
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes showed some shifts; while Wednesday remained the peak day for crashes in both periods, its count decreased from 78 in 2022 to 72 in 2023. The peak hour shifted from 3 PM with 37 crashes in 2022 to 5 PM with 40 crashes in 2023. Crashes on Tuesday and Saturday decreased, while crashes on Sunday, Monday, Thursday, and Friday increased year-over-year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall severity of crashes increased significantly, with total fatalities rising from 0 in November 2022 to 4 in November 2023, resulting in a fatal crash rate of 1.06% in the current period compared to 0% previously. Total injuries decreased by 17.9%, from 201 in 2022 to 165 in 2023, with serious injuries (Code A) decreasing from 6 to 2, while minor injuries (Code B) increased from 59 to 63.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Inattention' decreased by 21 crashes, from 95 in 2022 to 74 in 2023, but remained the top factor. 'Failed to yield right of way' increased by 13 crashes (from 54 to 67), and 'Followed too closely' saw a substantial increase of 27 crashes (from 18 to 45). 'Disregarded traffic signs, signals, road markings' decreased by 5 crashes, from 19 to 14.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 267 in 2022 to 315 in 2023, while those in 'Rain' decreased from 33 to 15. The number of crashes on 'Dry' road surfaces increased from 296 to 323, whereas crashes on 'Wet' surfaces decreased from 78 to 52. The distribution of crashes by lighting conditions remained relatively stable, with 'Dark - lighted roadway' reporting 133 crashes in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes saw some changes; HONDA crashes decreased from 130 to 110, while TOYOTA crashes increased from 99 to 107. HYUNDAI crashes decreased from 64 to 41, and JEEP crashes increased from 28 to 34. In terms of persons involved, the 16-20 age group saw a decrease from 127 to 99, while the 45-54 age group experienced an increase from 91 to 134.
Top Vehicle Makes (727 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records
103 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (912 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones decreased from 142 in 2022 to 116 in 2023, while crashes in 35 mph zones increased from 91 to 98. Notably, all 4 fatal crashes in November 2023 occurred in speed zones of 25 mph (1 fatal crash), 30 mph (1 fatal crash), and 35 mph (2 fatal crashes), whereas no fatal crashes were recorded in any speed zone in November 2022.
Fatal crashes by zone: 25 mph: 1 of 91 (1.099%) · 30 mph: 1 of 116 (0.862%) · 35 mph: 2 of 98 (2.041%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-11-01 through 2023-11-30 (30 days)
- Geographic scope: SPRINGFIELD, MA
- Total crash records analyzed: 376
- Total persons involved: 1,024
- Total vehicles involved: 727
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 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/november-2023-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: 2023-11-01 – 2023-11-30
Generated: June 21, 2026 · All rights reserved