ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPRINGFIELD, MA · NOVEMBER 2022
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-2022-report
Monthly Traffic Safety Analysis
381 CRASHES IN
SPRINGFIELD, MA
NOVEMBER 2022
In November 2022, SPRINGFIELD, MA recorded 381 total crashes, a 3.81% increase from the 367 crashes reported in November 2021. The most notable year-over-year shift was a significant decrease in fatalities, from 6 in November 2021 to 0 in November 2022. Total injuries also increased from 188 to 201.
381
▲ 3.8%was 367
Total Crash Events
0
▼ -100.0%was 6
Persons Killed
201
▲ 6.9%was 188
Persons Injured
38
▼ -2.6%was 39
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. 17 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in SPRINGFIELD, MA saw a slight increase year-over-year, with total crashes rising from 367 to 381, a 3.81% increase. Conversely, total fatalities experienced a substantial decrease, falling from 6 to 0, indicating an improvement in crash outcomes despite the higher crash volume.
38
Hit-and-Run Crashes — November 2022
▼ -2.6% vs prior (39)
Hit-and-run crashes saw a slight decrease, falling from 39 incidents in November 2021 to 38 incidents in November 2022. The hit-and-run rate also decreased marginally, from 10.6% to 10% of total crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
8
Pedestrians Injured
2
Cyclists Injured
191
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year. The peak day for crashes moved from Monday, with 71 crashes in November 2021, to Wednesday, with 78 crashes in November 2022. The peak hour also shifted, from 4 PM with 39 crashes in November 2021 to 3 PM with 37 crashes in November 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes saw a complete elimination, dropping from 6 in November 2021 to 0 in November 2022, leading to a fatal crash rate reduction from 1.63% to 0%. Serious injury crashes (severity A) increased slightly from 5 to 6, while minor injury crashes (severity B) decreased from 70 to 59. Possible injury crashes (severity C) rose from 41 to 50, contributing to an overall increase in total injuries from 188 to 201.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Inattention' remained the leading factor, increasing from 83 crashes in November 2021 to 95 crashes in November 2022, a 14.46% increase in count. 'Failed to yield right of way' decreased significantly from 75 crashes to 54 crashes, a 28% decrease in count, causing its rank to drop from second to third. Conversely, crashes attributed to 'Driving too fast for conditions' saw a substantial increase, rising from 3 to 16, a 433.33% increase in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Rain' conditions increased notably from 19 in November 2021 to 33 in November 2022. Similarly, crashes on 'Wet' road surfaces increased from 45 to 78 year-over-year. Crashes during 'Daylight' conditions also saw an increase, from 201 to 216.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field
Vehicles & Demographics
The number of persons aged '0-15' involved in crashes increased from 69 to 85, and those aged '16-20' increased from 102 to 127. Conversely, persons aged '26-34' decreased from 201 to 178, and those aged '45-54' decreased from 125 to 91. Among vehicle makes, HONDA vehicles involved in crashes increased from 110 to 130, and TOYOTA vehicles increased from 92 to 99.
Top Vehicle Makes (748 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records
110 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (892 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones increased from 131 to 142, and crashes in 55 mph zones increased from 21 to 33. Notably, 30 mph zones, which recorded 5 fatalities in November 2021, had 0 fatalities in November 2022. Crashes in 25 mph zones also increased from 87 to 94.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-11-01 through 2022-11-30 (30 days)
- Geographic scope: SPRINGFIELD, MA
- Total crash records analyzed: 381
- Total persons involved: 1,005
- Total vehicles involved: 748
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 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/november-2022-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: 2022-11-01 – 2022-11-30
Generated: June 21, 2026 · All rights reserved