ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPRINGFIELD, MA · MAY 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/may-2022-report
Monthly Traffic Safety Analysis
406 CRASHES IN
SPRINGFIELD, MA
MAY 2022
In May 2022, Springfield experienced 406 total crashes, an increase of 7.12% compared to 379 crashes in May 2021. Despite the rise in total crashes, total fatalities decreased by 50%, from 2 in May 2021 to 1 in May 2022. This represents a significant positive shift in crash outcomes.
406
▲ 7.1%was 379
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
256
▲ 21.9%was 210
Persons Injured
51
▲ 15.9%was 44
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. 22 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash data for May 2022 indicates an upward trend in total crash incidents, with 406 crashes recorded compared to 379 in May 2021, marking a 7.12% increase. Conversely, total fatalities decreased by 50%, from 2 in May 2021 to 1 in May 2022, while total injuries increased by 21.9% from 210 to 256.
51
Hit-and-Run Crashes — May 2022
▲ 15.9% vs prior (44)
Hit-and-run crashes increased in May 2022, with 51 incidents compared to 44 in May 2021, an increase of 7 crashes. The hit-and-run rate also rose from 11.6% of total crashes in May 2021 to 12.6% in May 2022, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
6
Pedestrians Injured
8
Cyclists Injured
242
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year. In May 2022, Monday became the peak day for crashes with 69 incidents, differing from May 2021 where Saturday had the highest count at 78 crashes. The peak crash hour also shifted, with 3 PM recording the most crashes (42) in May 2022, compared to 4 PM (36 crashes) in May 2021.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate decreased from 0.53% in May 2021 to 0.25% in May 2022, with total fatalities dropping from 2 to 1. While serious injury crashes (Severity A) decreased from 10 to 7, minor injury crashes (Severity B) saw a substantial increase from 66 to 102, representing a 54.5% rise in count. The overall injury rate increased from 55.4% of total crashes in May 2021 to 63.1% in May 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record
Top Contributing Factors
Several key contributing factors saw changes in crash counts year-over-year. Crashes attributed to 'Inattention' increased by 15.2% in count, from 99 to 114, while 'Failed to yield right of way' increased by 22.0% in count, from 59 to 72. Conversely, 'No improper driving' decreased by 28.6% in count, from 42 to 30, and 'Followed too closely' more than doubled, increasing by 109.1% in count from 11 to 23.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in clear weather conditions slightly increased from 73.6% in May 2021 to 77.3% in May 2022. Crashes during daylight hours also saw an increase in proportion, rising from 67.8% to 76.6% of total crashes. Conversely, the proportion of crashes occurring in dark, lighted roadway conditions decreased from 26.9% to 19.5%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 723 to 784 year-over-year. While Honda maintained its position with 124 vehicles involved in both periods, Toyota saw a notable increase from 82 to 107 vehicles. The age group 26-34 experienced an increase in persons involved, from 173 to 189, while the 16-20 age group saw a decrease from 111 to 93.
Top Vehicle Makes (784 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records
138 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (926 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones increased by 26 incidents, from 112 to 138, and crashes in 30 mph zones increased by 16 incidents, from 118 to 134. Conversely, crashes in 35 mph zones decreased by 12 incidents, from 102 to 90. The single fatal crash in May 2022 occurred in a 35 mph zone, where the fatal rate for that zone increased from 0.98% to 1.111%.
Fatal crashes by zone: 35 mph: 1 of 90 (1.111%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-05-01 through 2022-05-31 (31 days)
- Geographic scope: SPRINGFIELD, MA
- Total crash records analyzed: 406
- Total persons involved: 1,059
- Total vehicles involved: 784
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: May 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/may-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: 2022-05-01 – 2022-05-31
Generated: June 21, 2026 · All rights reserved