ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEST SPRINGFIELD, MA · MAY 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/may-2023-report
Monthly Traffic Safety Analysis
83 CRASHES IN
WEST SPRINGFIELD, MA
MAY 2023
Total crashes in WEST SPRINGFIELD for May 2023 remained stable at 83, matching the 83 crashes recorded in May 2022. Despite the consistent total crash count, the period saw a notable increase in fatalities, with 1 fatality in May 2023 compared to none in May 2022. This led to a fatal crash rate of 1.2% in the current period, up from 0% in the prior period.
83
Total Crash Events
1
Persons Killed
29
▼ -9.4%was 32
Persons Injured
8
▲ 60.0%was 5
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for crashes in WEST SPRINGFIELD indicates stability year-over-year, with no change in the total number of crashes between May 2022 and May 2023. Both periods recorded 83 total crashes, reflecting a 0% change. However, total injuries decreased slightly from 32 in May 2022 to 29 in May 2023.
8
Hit-and-Run Crashes — May 2023
▲ 60.0% vs prior (5)
Hit-and-run crashes increased year-over-year, rising from 5 incidents in May 2022 to 8 incidents in May 2023. This change resulted in an increase in the hit-and-run rate from 6% to 9.6% of all crashes.
Vulnerable Road User Casualties
0
Cyclists Killed
1
Motorists Killed
1
Cyclists Injured
28
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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, with Tuesday becoming the peak day for crashes in May 2023 with 24 incidents, compared to Thursday with 17 incidents in May 2022. The peak hour for crashes also changed, moving from 9 PM with 7 crashes in May 2022 to 6 PM with 9 crashes in May 2023. This suggests a shift in crash concentration to earlier evening hours and a different weekday.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution of crashes changed notably year-over-year, primarily due to the increase in fatal incidents. May 2023 recorded 1 fatal crash (1.2% of total crashes) and 1 serious injury crash (1.2%), whereas May 2022 had no fatal crashes (0%) but 3 serious injury crashes (3.6%). Overall, total injuries decreased from 32 in May 2022 to 29 in May 2023, with a reduction in possible injury crashes from 10 to 8.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' increased by 6 crashes, from 24 in May 2022 to 30 in May 2023, maintaining its position as the top factor. 'Inattention' also saw an increase of 4 crashes, rising from 8 to 12 incidents, and its share of crashes increased from 9.6% to 14.5%. Conversely, factors like 'Distracted' and 'Over-correcting/over-steering' decreased by 1 and 2 crashes respectively.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Adverse weather conditions saw a decrease in crashes year-over-year, with crashes occurring in 'Rain' or 'Cloudy/Rain' conditions decreasing from 12 in May 2022 to 6 in May 2023. Correspondingly, crashes under 'Clear' weather conditions increased from 61 to 68. There was a significant shift in lighting conditions, with crashes occurring in 'Daylight' increasing from 61 to 77, while those in 'Dark - lighted roadway' decreased from 16 to 5. Crashes on 'Wet' road surfaces decreased from 16 to 5, while those on 'Dry' surfaces increased from 66 to 78.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased slightly from 160 in May 2022 to 153 in May 2023. Toyota remained the top make, though its count decreased from 24 to 23, while Honda increased from 17 to 18. In terms of age distribution among persons involved, the '26-34' age group saw a notable increase of 13 persons, from 34 to 47, becoming the largest demographic in May 2023. Conversely, the '16-20' and '35-44' age groups experienced significant decreases of 14 persons each.
Top Vehicle Makes (153 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records
20 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (158 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone increased by 6, from 31 in May 2022 to 37 in May 2023, making it the most common speed zone for crashes. Crashes in the 40 mph zone decreased from 15 to 10, while those in the 65 mph zone increased from 5 to 9. The fatal crash in May 2023 occurred in a 65 mph speed zone, which had no fatal crashes in May 2022.
Fatal crashes by zone: 65 mph: 1 of 9 (11.111%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-05-01 through 2023-05-31 (31 days)
- Geographic scope: WEST SPRINGFIELD, MA
- Total crash records analyzed: 83
- Total persons involved: 180
- Total vehicles involved: 153
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: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/may-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: 2023-05-01 – 2023-05-31
Generated: June 21, 2026 · All rights reserved