ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEST SPRINGFIELD, MA · 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.
Yearly Traffic Safety Analysis
992 CRASHES IN
WEST SPRINGFIELD, MA
2022
In West Springfield, total traffic crashes increased slightly from 975 in 2021 to 992 in 2022, a change of approximately 1.7%. While total crashes rose, the number of fatalities decreased from 5 to 3. One of the most significant year-over-year shifts was the increase in pedestrian-involved crashes, which rose from 7 in 2021 to 19 in 2022.
992
▲ 1.7%was 975
Total Crash Events
3
▼ -40.0%was 5
Persons Killed
296
▼ -3.3%was 306
Persons Injured
114
▲ 12.9%was 101
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 48 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash trends show a slight increase in volume but a decrease in severity. Total crashes rose by 1.7% from 975 to 992 year-over-year. However, the number of persons injured fell by 3.3% from 306 to 296, and fatalities decreased by 40% from 5 to 3.
114
Hit-and-Run Crashes — 2022
▲ 12.9% vs prior (101)
Hit-and-run incidents trended upward between the two periods. The total count of hit-and-run crashes increased from 101 in 2021 to 114 in 2022. Consequently, the hit-and-run rate also rose, accounting for 11.5% of all crashes in 2022 compared to 10.4% in the prior year.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
10
Pedestrians Injured
8
Cyclists Injured
275
Motorists Injured
3
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between the two periods. The peak day for crashes moved from Friday (174 crashes) in 2021 to Thursday (164 crashes) in 2022. The peak hour for collisions remained consistent at 3 p.m. in both years, though the number of crashes during that hour decreased from 95 in 2021 to 80 in 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The distribution of crash severity changed year-over-year. The number of fatal crashes decreased from 5 to 3, with the fatal crash rate falling from 0.5% to 0.3% of all crashes. Conversely, the count of serious injury crashes increased from 14 to 23, raising their share of total crashes from 1.4% to 2.3%. The proportion of crashes resulting in no injury grew from 68.7% in 2021 to 72.4% in 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors remained the same in both years: 'No improper driving,' 'Inattention,' and 'Failed to yield right of way.' However, the counts for these factors shifted; crashes attributed to 'Inattention' decreased by 24% from 158 to 120, while crashes where 'No improper driving' was cited increased by 24% from 290 to 360. Crashes involving 'Driving too fast for conditions' saw a notable 39% decrease in count, from 46 to 28.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in 2022 were more likely to occur in clear conditions compared to the prior year. Collisions in 'Clear' weather accounted for 72.5% of all incidents in 2022, up from 63.7% in 2021. Similarly, crashes on 'Dry' road surfaces increased from 75.6% of the total in 2021 to 81.0% in 2022. Crashes occurring during 'Daylight' conditions remained proportionally stable at around 69% for both years.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes shifted slightly, with Toyota (246 vehicles) surpassing Honda (212 vehicles) for the top spot in 2022, reversing their 2021 ranking. An analysis of person age distribution shows an increased involvement of the 0-15 age group, which grew from 81 individuals in 2021 to 124 in 2022. The 65+ age group also saw an increase, from 192 to 227 persons involved.
Top Vehicle Makes (1,859 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
283 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,950 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The 30 mph speed zone remained the most frequent location for crashes in both years, with 383 incidents in 2022 compared to 396 in 2021. There was a notable increase in crashes within 40 mph zones, which rose from 114 to 147. Fatal crashes were more dispersed across speed zones in 2022, with one fatality each in 30, 35, and 50 mph zones, whereas in 2021, three of the five fatalities occurred in 30 mph zones.
Fatal crashes by zone: 30 mph: 1 of 383 (0.261%) · 35 mph: 1 of 69 (1.449%) · 50 mph: 1 of 10 (10%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: WEST SPRINGFIELD, MA
- Total crash records analyzed: 992
- Total persons involved: 2,265
- Total vehicles involved: 1,859
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved