ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BECKET, MA · 2024
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/becket/2024-annual-report
Yearly Traffic Safety Analysis
85 CRASHES IN
BECKET, MA
2024
In Becket, total traffic crashes increased from 79 in 2023 to 85 in 2024, a rise of 7.6%. The most significant change was the occurrence of one fatal crash in 2024, resulting in one death, compared to zero fatalities in the prior year. Additionally, the number of persons injured increased from 19 to 33.
85
▲ 7.6%was 79
Total Crash Events
1
Persons Killed
33
▲ 73.7%was 19
Persons Injured
0
▼ -100.0%was 3
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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic collisions in Becket trended upward year-over-year. The total number of crashes increased by 7.6%, from 79 in 2023 to 85 in 2024. This increase was accompanied by a rise in crash severity, with total injuries climbing by 73.7% and the first recorded fatality in the two-year period.
Vulnerable Road User Casualties
1
Motorists Killed
33
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes saw some shifts between the two years. The peak day for collisions moved from Wednesday (15 crashes) in 2023 to Thursday (16 crashes) in 2024. However, the peak hour for crashes remained stable at 4 p.m. in both periods, with 8 incidents in 2023 and 9 in 2024. Monthly crash distribution also changed, with December becoming the month with the highest crash count in 2024 (12 crashes), a change from 2023 where January and October were the peak months (9 crashes each).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased significantly in 2024 compared to the prior year. A fatal crash was recorded in 2024, accounting for 1.2% of all incidents, whereas no fatal crashes occurred in 2023. The proportion of crashes resulting in injury also rose, with the introduction of 3 'Serious Injury' crashes in 2024, a severity level not seen in the previous year's data. Consequently, the share of 'No Injury' crashes decreased from 77.2% of all crashes in 2023 to 70.6% in 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' remained the most common contributing factor in both years, its count decreased from 40 in 2023 to 31 in 2024. The most dramatic shift was in crashes attributed to 'Driving too fast for conditions,' which more than doubled in count from 8 to 19 incidents year-over-year. Other factors with notable increases in count include 'Over-correcting/over-steering' (from 1 to 6 crashes) and 'Exceeded authorized speed limit' (from 1 to 4 crashes). Consequently, the share of crashes where no improper driving was noted fell from 50.6% in 2023 to 36.5% in 2024.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across lighting conditions remained largely consistent, with daylight crashes accounting for 51.9% of incidents in 2023 and 57.6% in 2024. Similarly, weather conditions were stable, with clear weather present in about half of all crashes in both periods. A notable shift occurred in road surface conditions: while crashes on dry roads were steady at around 51%, the number of crashes on snowy surfaces increased from 11 to 17, as incidents on wet surfaces decreased from 17 to 11.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The demographics of persons involved in crashes shifted year-over-year, with the 26-34 age group becoming the most represented cohort in 2024 (34 persons), up from 19 persons in 2023. This displaced the 65+ age group, which was the largest in 2023 with 20 involved persons. Regarding vehicle makes, Toyota was the most common make in both years with 14 vehicles involved. Ford, the second most common make in 2023 with 13 vehicles, saw its involvement drop to 7 vehicles in 2024, while Honda's involvement increased from 6 to 11 vehicles.
Top Vehicle Makes (112 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
2 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 · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 65 mph speed zone continued to be the most frequent, accounting for 34 incidents in 2023 and increasing slightly to 37 in 2024. The distribution across other speed zones remained relatively stable, with minor fluctuations in zones like the 45 mph (16 to 13 crashes) and 40 mph (8 to 11 crashes) areas. The single fatal crash in 2024 occurred in a 35 mph zone, which had no fatalities in the prior year. This resulted in a 12.5% fatal crash rate for that specific zone in 2024.
Fatal crashes by zone: 35 mph: 1 of 8 (12.5%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: BECKET, MA
- Total crash records analyzed: 85
- Total persons involved: 140
- Total vehicles involved: 112
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). "BECKET, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/becket/2024-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved