ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEST SPRINGFIELD, MA · MARCH 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.
Monthly Traffic Safety Analysis
67 CRASHES IN
WEST SPRINGFIELD, MA
MARCH 2022
Total crashes in WEST SPRINGFIELD, MA decreased by 21.2%, from 85 in March 2021 to 67 in March 2022. This period also saw a significant 58.3% reduction in total injuries, falling from 36 to 15. The most notable shift was the substantial decrease in overall injuries.
67
▼ -21.2%was 85
Total Crash Events
0
Persons Killed
15
▼ -58.3%was 36
Persons Injured
9
▼ -10.0%was 10
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a decrease in crash activity year-over-year. Total crashes fell from 85 in March 2021 to 67 in March 2022, representing a 21.2% reduction. Similarly, total injuries decreased significantly by 58.3%, from 36 to 15.
9
Hit-and-Run Crashes — March 2022
▼ -10.0% vs prior (10)
The number of hit-and-run crashes decreased slightly from 10 in March 2021 to 9 in March 2022. Despite this decrease in count, the hit-and-run rate increased from 11.8% to 13.4% year-over-year. This indicates that hit-and-run incidents represent a larger proportion of the fewer total crashes in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
13
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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 Wednesday with 15 crashes in March 2021 to Saturday and Thursday, both with 13 crashes, in March 2022. The peak hour also shifted, with March 2021 experiencing its peak at 4 PM with 9 crashes, while March 2022 saw its peak at 12 PM, also with 9 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities in either period. Serious injury crashes remained stable at 1 crash in both March 2021 and March 2022. However, minor injury crashes decreased by 46.2% from 13 to 7, and possible injury crashes decreased by 63.6% from 11 to 4, leading to a higher proportion of no-injury crashes in the current period (80.6% vs. 64.7%).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'No improper driving' increased by 4, from 23 to 27 crashes, a 17.4% increase in count. Conversely, 'Inattention' as a contributing factor decreased by 6 crashes, from 15 to 9, a 40% reduction in count. 'Failed to yield right of way' increased by 2 crashes, from 6 to 8, while 'Followed too closely' decreased by 3 crashes, from 5 to 2.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions decreased from 64 to 44, a reduction of 20 crashes. The proportion of crashes on 'Dry' road surfaces decreased from 88.2% (75 crashes) in March 2021 to 71.6% (48 crashes) in March 2022, with 'Wet' road crashes increasing from 10 to 14. Crashes in 'Dark - lighted roadway' conditions decreased from 24 to 14.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field
Vehicles & Demographics
The top-ranked vehicle make, Honda, saw a decrease of 15 vehicles involved in crashes, from 28 in March 2021 to 13 in March 2022, falling from 1st to 3rd rank. Ford and Toyota now share the top rank with 16 vehicles each in March 2022, compared to 13 (Ford) and 18 (Toyota) in March 2021. Regarding persons involved, the 26-34 age group experienced the largest decrease, with 13 fewer individuals involved (from 36 to 23).
Top Vehicle Makes (117 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records
15 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (120 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones remained constant at 32 in both periods. Crashes in 40 mph zones decreased from 15 to 8, a reduction of 7 crashes. Similarly, crashes in 65 mph zones decreased from 7 to 3, a reduction of 4 crashes. No fatalities were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-03-01 through 2022-03-31 (31 days)
- Geographic scope: WEST SPRINGFIELD, MA
- Total crash records analyzed: 67
- Total persons involved: 136
- Total vehicles involved: 117
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). "WEST SPRINGFIELD, MA Crash Intelligence Report: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/march-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: 2022-03-01 – 2022-03-31
Generated: June 21, 2026 · All rights reserved