ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEST SPRINGFIELD, MA · 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.
Yearly Traffic Safety Analysis
1,004 CRASHES IN
WEST SPRINGFIELD, MA
2023
In West Springfield, total traffic crashes increased slightly from 992 in 2022 to 1,004 in 2023, a change of 1.2%. Despite the rise in total incidents, the number of fatalities recorded decreased from three in the prior year to one in the current year. This reduction in severe outcomes was the most significant year-over-year shift observed in the data.
1,004
▲ 1.2%was 992
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
293
▼ -1.0%was 296
Persons Injured
143
▲ 25.4%was 114
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. 37 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends indicate a slight increase in the total number of incidents, which rose by 12 crashes from 992 to 1,004 year-over-year. However, the severity of these incidents trended downward, with total fatalities dropping from 3 to 1 and total injuries decreasing marginally from 296 to 293. This suggests a higher volume of less severe collisions in 2023 compared to 2022.
143
Hit-and-Run Crashes — 2023
▲ 25.4% vs prior (114)
Hit-and-run crashes showed a clear upward trend. The total count of hit-and-run incidents increased by 25.4%, from 114 in 2022 to 143 in 2023. The hit-and-run rate, which measures these incidents as a percentage of all crashes, also rose from 11.5% in the prior year to 14.2% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
8
Pedestrians Injured
4
Cyclists Injured
281
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 between the two periods. In 2023, the peak day for crashes was Friday with 170 incidents, a change from Thursday (164 incidents) in 2022. Similarly, the peak hour for collisions moved an hour later, from the 3 PM hour in 2022 (80 crashes) to the 4 PM hour in 2023 (94 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes decreased from 2022 to 2023. The number of fatal crashes fell from 3 to 1, and the fatal crash rate dropped from 0.3% to 0.1%. Crashes resulting in serious injuries also saw a significant reduction, falling from 23 incidents (2.3% of total) to 10 incidents (1.0% of total). Consequently, the proportion of crashes involving no injuries increased from 72.4% in 2022 to 77.1% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' remained the most common factor listed in both years, its count decreased from 360 to 353. Conversely, crashes attributed to 'Inattention' increased in count from 120 to 136. A notable change was observed in crashes involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner,' which grew from 14 incidents in 2022 to 23 in 2023, a 64% increase in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There was a notable shift toward more crashes occurring in adverse road conditions year-over-year. The number of crashes on wet road surfaces increased from 145 in 2022 to 197 in 2023. This represents a proportional increase, with crashes on wet roads accounting for 14.6% of all incidents in 2022 and rising to 19.6% in 2023. Crashes on dry surfaces decreased from 803 to 772.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford leading in both years. However, the number of Hondas involved rose from 212 to 250, while Fords decreased from 195 to 181. Analysis of persons involved shows a demographic shift, with a decrease in crash involvement for the 16-20 and 21-25 age groups and an increase for the 26-34 age group.
Top Vehicle Makes (1,876 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
283 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,963 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes became more concentrated in lower speed zones, with incidents in 30 mph zones increasing from 383 in 2022 to 424 in 2023. While the total number of fatalities decreased, the single fatal crash in 2023 occurred in a 65 mph zone. This contrasts with 2022, where the three fatalities occurred in zones with posted speed limits of 30, 35, and 50 mph.
Fatal crashes by zone: 65 mph: 1 of 72 (1.389%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: WEST SPRINGFIELD, MA
- Total crash records analyzed: 1,004
- Total persons involved: 2,266
- Total vehicles involved: 1,876
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved