ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · 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.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/springfield/2022-annual-report
Yearly Traffic Safety Analysis
4,342 CRASHES IN
SPRINGFIELD, MA
2022
In 2022, Springfield recorded 4,342 total crashes, a 1.5% decrease from the 4,408 crashes in 2021. Despite the slight drop in overall incidents, the most significant year-over-year change was a 45.5% reduction in total fatalities, which fell from 22 in 2021 to 12 in 2022.
4,342
▼ -1.5%was 4,408
Total Crash Events
12
▼ -45.5%was 22
Persons Killed
2,368
▲ 0.2%was 2,364
Persons Injured
491
▼ -0.2%was 492
Hit-and-Run Crashes
Note: "Persons Killed" (12) counts individual fatalities across all crash events. "Fatal" in the severity table below (12) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 318 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 crashes in Springfield showed a slight downward trend, decreasing by 1.5% from 4,408 incidents in 2021 to 4,342 in 2022. While total injuries remained stable with a 0.17% increase to 2,368, the number of fatalities saw a substantial decrease of 45.5% year-over-year.
491
Hit-and-Run Crashes — 2022
▼ -0.2% vs prior (492)
The incidence of hit-and-run crashes remained stable year-over-year. In 2022, there were 491 hit-and-run incidents, compared to 492 in the prior year. This represents a nearly unchanged rate, with hit-and-runs accounting for 11.3% of all crashes in 2022, a marginal increase from the 11.2% rate recorded in 2021.
Vulnerable Road User Casualties
3
Pedestrians Killed
1
Cyclists Killed
8
Motorists Killed
0
Other Killed
66
Pedestrians Injured
36
Cyclists Injured
2,265
Motorists Injured
1
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 timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Wednesday with 688 incidents, a change from 2021 when Friday was the peak day with 717 crashes. The afternoon rush hour remained the most common time for collisions, with the 4 p.m. hour being the peak in both years, recording 387 crashes in 2021 and 407 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
While the overall number of crashes saw a minor decrease, the severity distribution shifted notably. The number of fatal crashes fell from 22 in 2021 to 12 in 2022, reducing their share of total crashes from 0.5% to 0.3%. The proportion of serious injury crashes remained constant at 2.1% in both years, while the share of crashes resulting in no injury increased from 52.0% in 2021 to 57.3% 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
Inattention remained the leading contributing factor in both years, with its count increasing by 6.4% from 1,058 incidents in 2021 to 1,126 in 2022. In contrast, crashes attributed to 'Failed to yield right of way' decreased by 10.1% in count, from 739 to 664. The top three contributing factors remained the same, but their respective counts shifted year-over-year.
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 predominantly occurred in clear weather and on dry roads in both years, and this proportion increased in 2022. Crashes on dry road surfaces accounted for 78.0% of incidents in 2022, up from 75.9% in 2021. Correspondingly, crashes on wet roads decreased from 806 to 714. The proportion of crashes occurring in daylight increased from 63.6% to 65.7%, while those in darkness on lighted roadways fell from 30.3% to 28.8%.
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 five vehicle makes involved in crashes remained consistent between 2021 and 2022: Honda, Toyota, Nissan, Ford, and Hyundai. The number of Hondas (1,285), Toyotas (1,067), and Fords (674) involved in crashes decreased in 2022, while Nissans (753) and Hyundais (580) saw slight increases. The age distribution of persons involved in crashes also remained stable, with the 26-34 age group representing the largest cohort in both years at 18.4% of persons in 2022 compared to 18.6% in 2021.
Top Vehicle Makes (8,381 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
1,428 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (9,742 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 distribution of crashes across speed zones showed minor shifts, with an increase in incidents in 25 mph zones (from 1,305 to 1,377) and a decrease in 30 mph zones (from 1,565 to 1,476). The most significant change occurred in fatal crash locations; fatalities in 30 mph zones dropped from 10 in 2021 to 2 in 2022. In contrast, fatal crashes in 25 mph zones increased from 3 to 4.
Fatal crashes by zone: 25 mph: 4 of 1,377 (0.29%) · 30 mph: 2 of 1,476 (0.136%) · 35 mph: 5 of 951 (0.526%) · 55 mph: 1 of 250 (0.4%)
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: SPRINGFIELD, MA
- Total crash records analyzed: 4,342
- Total persons involved: 11,176
- Total vehicles involved: 8,381
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: 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/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