ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEST SPRINGFIELD, MA · JUNE 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/west-springfield/june-2023-report
Monthly Traffic Safety Analysis
74 CRASHES IN
WEST SPRINGFIELD, MA
JUNE 2023
In West Springfield, total crashes increased by 12.12%, from 66 in June 2022 to 74 in June 2023. Despite the rise in overall crashes, total injuries saw a significant decrease of 48.48%, falling from 33 to 17. Fatalities remained at zero in both periods.
74
▲ 12.1%was 66
Total Crash Events
0
Persons Killed
17
▼ -48.5%was 33
Persons Injured
13
▲ 62.5%was 8
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in West Springfield experienced an upward trend, increasing by 12.12% from 66 crashes in June 2022 to 74 crashes in June 2023. Conversely, the number of total injuries decreased by 48.48%, falling from 33 to 17 over the same period.
13
Hit-and-Run Crashes — June 2023
▲ 62.5% vs prior (8)
Hit-and-run crashes increased by 62.5% year-over-year, rising from 8 incidents in June 2022 to 13 in June 2023. The hit-and-run rate also increased, from 12.1% to 17.6% of all crashes, indicating an upward trend in these incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns for crashes shifted between the two periods. The peak day for crashes moved from Thursday with 15 crashes in June 2022 to Friday with 20 crashes in June 2023. Similarly, the peak hour for crashes changed from 9a with 7 crashes in June 2022 to 5p with 10 crashes in June 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at 0 in both June 2022 and June 2023. Total injuries decreased by 48.48%, from 33 to 17. Serious injury crashes decreased from 3 (4.5% share) to 1 (1.4% share), and possible injury crashes decreased from 8 (12.1% share) to 2 (2.7% share), while minor injury crashes remained constant at 10 but decreased in share from 15.2% to 13.5%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors remained consistent in ranking, with 'No improper driving' increasing from 29 to 30 crashes, a 3.4% increase in count. 'Failed to yield right of way' and 'Inattention' both saw a 42.86% increase in crash counts, rising from 7 to 10 crashes each. 'Followed too closely' decreased from 3 to 2 crashes, a 33.33% decrease in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in rainy weather increased from 2 to 6, a 200% increase, and those on wet road surfaces increased from 3 to 10, a 233.33% increase. Crashes in daylight conditions increased from 53 to 65, while those in dark-lighted roadway conditions decreased from 10 to 6. Cloudy weather crashes more than doubled from 6 to 13.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field
Vehicles & Demographics
HONDA vehicles involved in crashes increased significantly from 7 to 23, making it the top make in June 2023, while TOYOTA decreased from 23 to 11. In terms of persons involved, the 26-34 age group saw a notable increase from 21 to 37, and the 65+ age group increased from 11 to 17. Conversely, the 21-25 age group experienced a decrease from 19 to 6 persons involved.
Top Vehicle Makes (137 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records
21 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (135 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events
Speed Limit Zones
The 30 mph speed zone continued to account for the highest number of crashes, increasing from 26 in June 2022 to 34 in June 2023. Crashes in the 40 mph zone doubled from 4 to 8, while the 65 mph zone maintained 7 crashes in both periods. No fatalities were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-06-01 through 2023-06-30 (30 days)
- Geographic scope: WEST SPRINGFIELD, MA
- Total crash records analyzed: 74
- Total persons involved: 157
- Total vehicles involved: 137
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: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/june-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: 2023-06-01 – 2023-06-30
Generated: June 21, 2026 · All rights reserved