ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPENCER, 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/spencer/2024-annual-report
Yearly Traffic Safety Analysis
194 CRASHES IN
SPENCER, MA
2024
In 2024, Spencer recorded 194 total vehicle crashes, a 5.4% increase from the 184 crashes documented in 2023. While total injuries saw a slight decrease from 60 to 57, the number of fatalities doubled from one in the prior year to two in the current year. A notable shift was observed in contributing factors, with crashes attributed to 'Inattention' increasing from 17 to 29 incidents.
194
▲ 5.4%was 184
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
57
▼ -5.0%was 60
Persons Injured
12
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. 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
Crash trends in Spencer show an upward movement year-over-year, with total collisions rising from 184 in 2023 to 194 in 2024. This represents an increase of 10 crashes, or 5.4%. While the total number of people injured decreased slightly from 60 to 57, the number of fatalities doubled from one to two.
12
Hit-and-Run Crashes — 2024
▼ 0.0% vs prior (12)
The number of hit-and-run incidents in Spencer remained unchanged year-over-year, with 12 crashes reported in both 2024 and 2023. Due to the overall increase in total crashes in the current period, the hit-and-run rate saw a marginal decrease from 6.5% in 2023 to 6.2% in 2024. This indicates a stable trend in the absolute number of hit-and-run events.
Vulnerable Road User Casualties
0
Cyclists Killed
2
Motorists Killed
1
Cyclists Injured
56
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 remained broadly consistent year-over-year, with Tuesday being the peak day for collisions in both 2024 (37 crashes) and 2023 (36 crashes). The peak hour for crashes shifted slightly, from 4 PM in 2023 (22 crashes) to 5 PM in 2024 (21 crashes). Both periods show a concentration of incidents during the afternoon and evening commute hours.
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
The severity of crashes increased in 2024, with the number of fatal crashes doubling from one to two and the fatality rate rising from 0.54% to 1.03%. The share of 'Minor Injury' crashes rose from 13% to 16% of all incidents, while 'Possible Injury' crashes decreased from a 10.3% share to 5.7%. The proportion of crashes resulting in no injuries increased from 70.7% in 2023 to 73.7% 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
The leading contributing factors for crashes shifted between the two periods, with 'Inattention' becoming more prominent in 2024. The count of crashes attributed to inattention rose by 70.6%, from 17 incidents in 2023 to 29 in 2024, moving it from the fourth to the second-ranked factor. 'Failed to yield right of way' remained a top cause, with the count of related crashes increasing slightly from 26 to 28. Crashes where 'No improper driving' was cited also saw a notable increase in count, from 38 in the prior year to 53 in the current year.
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
Environmental conditions during crashes remained largely consistent between 2023 and 2024. The majority of collisions in both years occurred in 'Daylight' (69.1% in 2024 vs. 66.3% in 2023) and on 'Dry' road surfaces (75.8% in 2024 vs. 75.0% in 2023). There was no significant year-over-year shift in the proportion of crashes happening during adverse weather, poor lighting, or challenging road surface conditions.
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 top three vehicle makes involved in crashes remained Ford, Toyota, and Chevrolet in both years, although their total counts decreased in 2024; Ford-involved crashes dropped from 57 to 50. Regarding the demographics of persons involved, there was a notable increase in the 26-34 age group, which grew from 63 individuals in 2023 to 75 in 2024. Conversely, the 65+ age group saw a decrease in involvement, from 56 individuals to 44.
Top Vehicle Makes (327 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
32 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (375 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
Analysis of speed zones reveals a shift in where crashes occurred, with collisions in 30 mph zones increasing from 83 in 2023 to 91 in 2024. Crashes in 40 mph zones decreased from 66 to 59. Notably, the location of fatal crashes also changed; the single fatal crash in 2023 occurred in a 40 mph zone, whereas both fatal crashes in 2024 took place in 30 mph zones.
Fatal crashes by zone: 30 mph: 2 of 91 (2.198%)
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: SPENCER, MA
- Total crash records analyzed: 194
- Total persons involved: 409
- Total vehicles involved: 327
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). "SPENCER, 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/spencer/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