ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPRINGFIELD, MA · SEPTEMBER 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/september-2022-report
Monthly Traffic Safety Analysis
315 CRASHES IN
SPRINGFIELD, MA
SEPTEMBER 2022
In September 2022, SPRINGFIELD, MA recorded 315 total crashes, a 24.64% decrease from the 418 crashes in September 2021. Fatalities saw a substantial reduction, dropping by 66.67% from 3 to 1. Total injuries also decreased by 17.74%, from 248 to 204.
315
▼ -24.6%was 418
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
204
▼ -17.7%was 248
Persons Injured
30
▼ -11.8%was 34
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash data for September shows a declining trend year-over-year. Total crashes decreased by 103, representing a 24.64% reduction. Fatalities fell by 2 (66.67%), and injuries decreased by 44 (17.74%) compared to the prior year.
30
Hit-and-Run Crashes — September 2022
▼ -11.8% vs prior (34)
The total number of hit-and-run crashes decreased from 34 in the prior period to 30 in the current period, an 11.76% reduction. Despite the decrease in raw count, the hit-and-run rate increased from 8.1% to 9.5% year-over-year due to a larger overall reduction in total crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
11
Pedestrians Injured
5
Cyclists Injured
188
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak crash day shifted from Thursday, with 73 crashes in the prior period, to Wednesday, with 56 crashes in the current period. The peak crash hour also changed, moving from 3 PM (49 crashes) in the prior year to 4 PM (39 crashes) in the current year. While overall crash counts decreased across all days and hours, these shifts indicate a change in when crashes are most concentrated.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes decreased significantly by 66.67%, from 3 in the prior period to 1 in the current period, with the fatal crash rate dropping from 0.72% to 0.32%. The share of serious injuries increased from 0.7% to 2.2% of total crashes, and the share of minor and possible injuries also rose from 20.6% to 22.5% and 13.4% to 18.7% respectively. This indicates a shift towards a higher proportion of injury-involved crashes despite the overall reduction in total crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record
Top Contributing Factors
Inattention remained the leading contributing factor, decreasing from 112 crashes to 84 crashes, a 25% reduction. Crashes attributed to "Failed to yield right of way" also saw a notable decrease of 37 crashes, from 80 to 43. Conversely, crashes involving "Disregarded traffic signs, signals, road markings" increased by 8, from 13 in the prior period to 21 in the current period, representing a 61.5% increase in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 298 to 228, though their share of total crashes slightly increased from 71.3% to 72.4%. Crashes on wet road surfaces decreased from 79 to 53, with their share of total crashes slightly declining from 18.9% to 16.8%. There were no substantial proportional shifts in lighting conditions, with daylight crashes remaining the dominant category in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 822 to 620, a 24.57% reduction year-over-year. Honda, Toyota, and Ford remained the top three vehicle makes involved in crashes, all experiencing a decrease in their counts. Persons aged 26-34 and 55-64 represented a larger share of persons involved in crashes in the current period, increasing from 17.6% to 20.4% and 6.6% to 9.1% respectively, while younger age groups (0-15 and 16-20) saw their shares decrease.
Top Vehicle Makes (620 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records
94 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (768 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones decreased significantly from 162 to 88, a 45.7% reduction, and saw no fatal crashes in the current period compared to 2 in the prior period. Crashes in 35 mph zones also decreased from 104 to 74, a 28.8% reduction, with no fatal crashes in the current period compared to 1 in the prior period. Conversely, crashes in 25 mph zones saw a slight increase from 106 to 107 and were associated with the single fatal crash in the current period, whereas there were none in the prior period.
Fatal crashes by zone: 25 mph: 1 of 107 (0.935%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-09-01 through 2022-09-30 (30 days)
- Geographic scope: SPRINGFIELD, MA
- Total crash records analyzed: 315
- Total persons involved: 861
- Total vehicles involved: 620
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: September 2022." Published June 21, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/september-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: 2022-09-01 – 2022-09-30
Generated: June 21, 2026 · All rights reserved