ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BELCHERTOWN, 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.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/belchertown/2023-annual-report
Yearly Traffic Safety Analysis
196 CRASHES IN
BELCHERTOWN, MA
2023
In 2023, Belchertown recorded 196 total traffic crashes, a 59.3% increase from the 123 crashes documented in 2022. This rise was accompanied by an increase in both injuries and fatalities. The most notable year-over-year shift was the emergence of two fatal crashes in 2023, whereas none were recorded in the prior year.
196
▲ 59.3%was 123
Total Crash Events
2
Persons Killed
53
▲ 71.0%was 31
Persons Injured
4
▲ 300.0%was 1
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data indicates a rising trend in Belchertown year-over-year. Total crashes increased from 123 in 2022 to 196 in 2023. This upward trend is also reflected in crash outcomes, with total injuries rising from 31 to 53 and fatalities increasing from zero to two.
4
Hit-and-Run Crashes — 2023
▲ 300.0% vs prior (1)
Hit-and-run crashes increased in both count and as a proportion of total incidents. The number of hit-and-run crashes rose from one in 2022 to four in 2023. This change caused the hit-and-run rate to more than double, increasing from 0.8% of all crashes in the prior year to 2.0% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
2
Motorists Killed
1
Pedestrians Injured
52
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 primary temporal patterns for crashes remained consistent between the two periods. Friday was the peak day for crashes in both 2023, with 38 incidents, and 2022, with 23 incidents. Similarly, the 5 p.m. hour was the single hour with the most crashes in both years, accounting for 18 crashes in 2023 and 13 in 2022.
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
Crash severity worsened in 2023 compared to the prior year. The city recorded two fatal crashes, representing 1% of all incidents, after having zero in 2022. The proportion of crashes involving any injury also increased, with minor injury crashes rising from an 11.4% share to a 14.3% share of all incidents. Consequently, the share of crashes resulting in no injuries decreased from 77.2% in 2022 to 74.0% 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 frequent contributing factor in both periods, its count increased from 40 in 2022 to 74 in 2023. Crashes attributed to "Inattention" more than doubled, rising from 12 incidents in 2022 to 28 in 2023. Other notable increases in crash counts were seen for "Failed to yield right of way" (from 5 to 10 incidents) and "Failure to keep in proper lane or running off road" (from 6 to 10 incidents).
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
In both years, the majority of crashes occurred during daylight hours on dry roads under clear weather. However, the proportion of crashes happening in these ideal conditions was higher in 2023 than in 2022. Crashes on dry roads accounted for 75.0% of the total in 2023, up from 65.9% in 2022, while daylight crashes increased from a 61.0% share to a 66.3% share.
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 ranking of top vehicle makes involved in crashes shifted, with Toyota moving from second place (21 vehicles) in 2022 to first place in 2023 with 41 vehicles. There was also a significant change in the age distribution of persons involved in crashes. The 16-20 age group's share of involved persons fell from 25.6% in 2022 to 10.7% in 2023, while the 0-15 age group's share grew from 2.3% to 24.4%.
Top Vehicle Makes (298 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (440 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 remained most common in 30 mph and 40 mph zones in both years, but their counts increased significantly. Incidents in 40 mph zones doubled from 26 in 2022 to 52 in 2023, and crashes in 30 mph zones rose from 41 to 51. The two fatal crashes recorded in 2023 occurred within these zones, with one in a 30 mph zone and the other in a 40 mph zone.
Fatal crashes by zone: 30 mph: 1 of 51 (1.961%) · 40 mph: 1 of 52 (1.923%)
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: BELCHERTOWN, MA
- Total crash records analyzed: 196
- Total persons involved: 459
- Total vehicles involved: 298
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). "BELCHERTOWN, 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/belchertown/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