ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPENCER, 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/spencer/2023-annual-report
Yearly Traffic Safety Analysis
184 CRASHES IN
SPENCER, MA
2023
In 2023, Spencer recorded 184 total traffic crashes, a 22% decrease from the 236 crashes reported in 2022. While the number of total fatalities remained unchanged at one death in each period, the total number of injuries saw a slight increase from 59 to 60. Despite the overall reduction in collisions, the number of hit-and-run incidents increased from 9 in 2022 to 12 in 2023.
184
▼ -22.0%was 236
Total Crash Events
1
Persons Killed
60
▲ 1.7%was 59
Persons Injured
12
▲ 33.3%was 9
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. 3 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, traffic crashes in Spencer showed a downward trend from 2022 to 2023, with total collisions falling by 52 incidents, or 22%. Despite this significant drop in crash volume, the number of people injured remained nearly stable, increasing by one from 59 to 60. The number of fatalities was unchanged, with one death recorded in both years.
12
Hit-and-Run Crashes — 2023
▲ 33.3% vs prior (9)
The number of hit-and-run crashes in Spencer increased from 9 in 2022 to 12 in 2023, representing a 33.3% rise in count. The hit-and-run rate, calculated as a percentage of total crashes, also trended upward. These incidents accounted for 6.5% of all crashes in 2023, up from 3.8% in the prior year.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Motorists Killed
0
Other Killed
1
Pedestrians Injured
58
Motorists Injured
1
Other 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 2022 and 2023. The peak day for crashes moved from Wednesday, with 53 incidents in 2022, to Tuesday, with 36 incidents in 2023. Similarly, the peak hour for collisions shifted slightly from 3 p.m. in the prior year (25 crashes) to 4 p.m. in the current year (22 crashes). While the afternoon commute hours remained the most frequent time for crashes in both periods, the pronounced mid-week spike seen in 2022 was less evident in 2023.
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
While the absolute number of fatal crashes remained constant at one in both 2022 and 2023, the fatal crash rate increased from 0.42 to 0.54 per 100 crashes due to the lower total number of incidents in 2023. The proportion of crashes resulting in an injury grew year-over-year; crashes involving serious injuries rose from 2.1% to 3.8% of all incidents, and minor injury crashes increased from 8.1% to 13.0%. Consequently, the share of crashes with no reported injuries decreased from 78.8% in 2022 to 70.7% 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
The leading contributing factors cited in crashes saw some shifts between 2022 and 2023. While 'Failed to yield right of way' remained the most common improper driving action cited in both years, its count decreased from 39 incidents in 2022 to 26 in 2023. Notably, crashes attributed to 'Failure to keep in proper lane or running off road' increased by 33%, from 15 to 20 incidents, making it the second most frequent improper action in 2023. Conversely, incidents involving 'Other improper action' saw a significant drop in count from 21 to 12.
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
The majority of crashes in both 2022 and 2023 occurred in daylight on dry roads, with the proportion of crashes on dry surfaces remaining stable at around 74-75%. There was a shift in crashes occurring during dark conditions; the proportion of incidents on unlit dark roadways increased from 8.5% in 2022 (20 crashes) to 11.4% in 2023 (21 crashes). While the total number of crashes on snowy or icy roads decreased from 33 to 23, the count of crashes specifically during snowy weather doubled from 6 in 2022 to 12 in 2023.
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 most common vehicle makes involved in crashes remained consistent, with Ford and Toyota leading in both years, although their total counts decreased from 63 to 57 and 56 to 43, respectively. Chevrolet (32 vehicles) replaced Honda (18 vehicles) as the third most-involved make in 2023. Analysis of persons involved shows a shift in age demographics; the proportion of individuals in the 16-20 age group decreased from 14.3% in 2022 to 11.9% in 2023. Conversely, the representation of the 65+ age group increased from 12.8% to 15.2% of all persons involved in crashes.
Top Vehicle Makes (306 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
21 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (347 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 in 30 mph zones remained the most frequent in both periods, though the count fell from 100 in 2022 to 83 in 2023. The number of crashes in 40 mph zones was relatively stable, with 71 incidents in 2022 and 66 in 2023. A notable reduction occurred in 25 mph zones, where crashes dropped from 27 to just 8. The single fatal crash in 2023 occurred in a 40 mph zone, whereas the fatal crash in 2022 took place in a 30 mph zone.
Fatal crashes by zone: 40 mph: 1 of 66 (1.515%)
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: SPENCER, MA
- Total crash records analyzed: 184
- Total persons involved: 369
- Total vehicles involved: 306
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: 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/spencer/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