ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPENCER, MA · 2025
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/2025-annual-report
Yearly Traffic Safety Analysis
206 CRASHES IN
SPENCER, MA
2025
In SPENCER, MA, total traffic crashes increased from 194 in 2024 to 206 in 2025, a 6.2% year-over-year rise. Despite the increase in total collisions, the number of fatalities decreased from two to one. A notable shift was observed in contributing factors, with crashes attributed to 'Failed to yield right of way' increasing by 35.7% in count.
206
▲ 6.2%was 194
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
62
▲ 8.8%was 57
Persons Injured
17
▲ 41.7%was 12
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic crashes in SPENCER trended upward, increasing by 6.2% from 194 in the prior year to 206 in the current year. While total crashes rose, fatalities fell from 2 to 1. The number of persons injured showed a modest increase from 57 to 62.
17
Hit-and-Run Crashes — 2025
▲ 41.7% vs prior (12)
Hit-and-run incidents increased in both count and rate. The number of hit-and-run crashes rose from 12 in 2024 to 17 in 2025, a 41.7% increase. Consequently, the hit-and-run rate as a percentage of total crashes climbed from 6.2% to 8.3% year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Motorists Killed
5
Pedestrians Injured
57
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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 year-over-year. The peak day for crashes moved from Tuesday (37 crashes) in the prior period to Sunday (35 crashes) in the current period. The peak hour for collisions shifted slightly earlier, from 5 p.m. (21 crashes) in 2024 to 4 p.m. (22 crashes) in 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Although total crashes increased, their overall severity decreased. The number of fatal crashes fell from 2 to 1, and the fatal crash rate dropped from 1.03 to 0.49 per 100 crashes. Crashes resulting in serious injuries also decreased, from 6 incidents (3.1% of total) to 2 incidents (1.0% of total). The proportion of crashes with no injuries remained stable at approximately 74% in both periods.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The ranking of top contributing factors shifted between periods. 'Failed to yield right of way' became a more prominent factor, with the count of related crashes increasing from 28 to 38, a 35.7% rise, moving it from third to second place. Conversely, crashes involving 'Inattention' decreased in count from 29 to 22, dropping from the second to the third-ranked cause. The count for 'No improper driving' and 'Failure to keep in proper lane' remained unchanged at 53 and 21 crashes, respectively.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained broadly consistent year-over-year. The majority of collisions in both periods occurred on dry roads (75.8% in 2024 vs. 76.2% in 2025) and during daylight hours (69.1% vs. 68.4%). The proportion of crashes in clear weather conditions saw a slight increase, from 67.0% of crashes in the prior year to 73.8% in the current year, while the absolute count of crashes in adverse weather like rain or snow was similar.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes showed some shifts. While Ford and Toyota remained the top two makes, Chevrolet-involved crashes increased from 29 to 45, tying Ford for the most common make in the current period. Analysis of persons involved in crashes reveals a notable increase in the 16-20 age group (from 43 to 61 persons) and the 65+ age group (from 44 to 59 persons) compared to the prior year.
Top Vehicle Makes (338 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
25 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (389 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones was consistent between the two periods. The 30 mph zone accounted for the highest number of crashes in both 2024 (91 crashes) and 2025 (96 crashes), followed by the 40 mph zone (59 and 62 crashes, respectively). All fatal crashes in both years (2 in 2024, 1 in 2025) occurred in 30 mph speed zones.
Fatal crashes by zone: 30 mph: 1 of 96 (1.042%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: SPENCER, MA
- Total crash records analyzed: 206
- Total persons involved: 417
- Total vehicles involved: 338
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/spencer/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved