ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPRINGFIELD, MA · FEBRUARY 2023
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/february-2023-report
Monthly Traffic Safety Analysis
317 CRASHES IN
SPRINGFIELD, MA
FEBRUARY 2023
In February 2023, Springfield recorded 317 total crashes, marking an 11.7% decrease from the 359 crashes reported in February 2022. Despite the overall reduction in crashes, total fatalities increased significantly by 100%, rising from 2 to 4 deaths year-over-year. Total injuries also saw an increase, climbing by 9.4% from 149 to 163.
317
▼ -11.7%was 359
Total Crash Events
4
▲ 100.0%was 2
Persons Killed
163
▲ 9.4%was 149
Persons Injured
43
▼ -2.3%was 44
Hit-and-Run Crashes
Note: "Persons Killed" (4) 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. 16 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Springfield showed a downward trend year-over-year, with total crashes decreasing by 11.7% from 359 in February 2022 to 317 in February 2023. However, this reduction in crash volume was accompanied by an increase in severe outcomes, as total fatalities doubled during the same period.
43
Hit-and-Run Crashes — February 2023
▼ -2.3% vs prior (44)
The number of hit-and-run crashes slightly decreased from 44 in February 2022 to 43 in February 2023. However, despite this minor reduction in count, the hit-and-run rate relative to total crashes increased from 12.3% to 13.6% year-over-year. This indicates that a larger proportion of the total crashes in February 2023 involved a hit-and-run incident.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
4
Motorists Killed
9
Pedestrians Injured
1
Cyclists Injured
153
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal patterns of crashes showed shifts year-over-year. The peak day for crashes moved from Wednesday in February 2022 (63 crashes) to Friday in February 2023 (60 crashes), although the overall count on the peak day slightly decreased. Similarly, the peak crash hour shifted from 5 PM in February 2022 (27 crashes) to 6 PM in February 2023 (29 crashes), indicating a slight delay in the evening rush hour peak.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes worsened in February 2023 compared to the prior year. Fatal crashes increased from 2 (0.6% of total crashes) to 3 (0.9%), with total fatalities doubling from 2 to 4. Crashes resulting in serious injury rose from 5 to 6, while minor injury crashes increased from 53 to 58. Overall, the proportion of crashes resulting in any injury (A, B, or C) increased from 26.7% to 32.2%.
Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors saw shifts in their counts year-over-year. 'Inattention' remained the leading factor, decreasing from 90 crashes in February 2022 to 83 crashes in February 2023. 'Driving too fast for conditions' saw a notable decrease of 14 crashes, falling from 27 to 13, while 'Distracted' driving crashes increased significantly by 7 incidents, rising from 5 to 12. 'Disregarded traffic signs, signals, road markings' also increased slightly from 20 to 21 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions showed shifts, with a notable decrease in crashes on adverse road surfaces. Crashes on wet roads decreased from 74 to 52, on snow from 27 to 17, and on ice from 21 to 7. While clear weather crashes decreased from 250 to 228, crashes during dark-lighted roadway conditions increased from 116 to 122, suggesting a slight increase in nighttime incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field
Vehicles & Demographics
The distribution of top vehicle makes involved in crashes remained largely consistent, with Honda, Toyota, and Nissan retaining the top three positions. Honda-involved crashes increased from 102 to 117, while Toyota-involved crashes decreased from 81 to 76. A significant shift was observed in the age distribution of persons involved, with the 0-15 age group increasing by 43.4% from 53 to 76, and the 21-25 age group increasing by 19.6% from 92 to 110. Conversely, the 26-34 age group saw a decrease of 18.9%, from 175 to 142.
Top Vehicle Makes (614 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records
87 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (744 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed zone decreased from 129 to 107 year-over-year, and fatal crashes in this zone dropped from 1 to 0. Conversely, crashes in the 30 mph zone slightly increased from 108 to 110, but critically, fatal crashes in this zone rose from 0 to 2. The 35 mph zone saw a minor decrease in crashes from 71 to 70, with fatal crashes remaining constant at 1.
Fatal crashes by zone: 30 mph: 2 of 110 (1.818%) · 35 mph: 1 of 70 (1.429%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-02-01 through 2023-02-28 (28 days)
- Geographic scope: SPRINGFIELD, MA
- Total crash records analyzed: 317
- Total persons involved: 839
- Total vehicles involved: 614
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: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/february-2023-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: 2023-02-01 – 2023-02-28
Generated: June 21, 2026 · All rights reserved