Monthly Traffic Safety Analysis

11 CRASHES IN
SPENCER, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

In September 2024, SPENCER experienced 11 total crashes, a notable decrease of 45% compared to the 20 total crashes recorded in September 2023. The most significant year-over-year shift was the 71.4% reduction in crashes attributed to 'Failure to keep in proper lane or running off road', which decreased from 7 crashes to 2 crashes.

11

-45.0%was 20

Total Crash Events

0

Persons Killed

5

-28.6%was 7

Persons Injured

0

-100.0%was 2

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash data for SPENCER indicates a significant downward trend year-over-year, with total crashes decreasing from 20 in September 2023 to 11 in September 2024, representing a 45% reduction. Total injuries also decreased by 28.6%, from 7 injuries in the prior period to 5 in the current period, while fatalities remained at zero in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 7-28.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak crash day moving from Tuesday (5 crashes) in September 2023 to Friday (2 crashes, tied with Sun, Mon, Tue, Thu) in September 2024. The peak crash hour also shifted slightly, from 8 PM (2 crashes) in the prior period to 7 PM (2 crashes, tied with 12 PM, 5 PM) in the current period. While the prior period had zero crashes on Monday, the current period recorded two crashes on that day.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either September 2023 or September 2024. Total injuries decreased from 7 in the prior period to 5 in the current period, a 28.6% reduction. Notably, serious injuries (code A) and possible injuries (code C) reported in September 2023 (1 and 3 respectively) were absent in September 2024, with only minor injuries (code B) recorded (3 crashes in both periods).

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes27.3%
0.0%prior 3
No Injury8no injury crashes72.7%
-33.3%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor in September 2023, 'Failure to keep in proper lane or running off road', saw a substantial 71.4% decrease in count, falling from 7 crashes to 2 crashes. Conversely, 'No improper driving' increased by 50% in count, rising from 2 crashes to 3 crashes, making it the most frequent factor in the current period. 'Failed to yield right of way' crashes decreased by 33.3% in count, from 3 to 2 crashes year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving3 (27.3%)
Failed to yield right of way2 (18.2%)
Failure to keep in proper lane or running off road2 (18.2%)-71.4%prior 7
Disregarded traffic signs, signals, road markings1 (9.1%)
Other improper action1 (9.1%)
Distracted1 (9.1%)
Exceeded authorized speed limit1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 14 in September 2023 to 10 in September 2024. Similarly, crashes on dry road surfaces decreased from 17 to 10 year-over-year. Crashes occurring during daylight hours also decreased from 13 to 8, while crashes in 'Dark - lighted roadway' conditions remained constant at 3 in both periods.

Weather

Clear/Clear10 (90.9%)
-28.6%prior 14
Rain/Rain1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight8 (72.7%)
-38.5%prior 13
Dark - lighted roadway3 (27.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry10 (90.9%)
-41.2%prior 17
Wet1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (19 vehicles)

1
CHEVROLET3 (15.8%)
2
FORD3 (15.8%)
3
HONDA3 (15.8%)
4
TOYOTA3 (15.8%)
-40.0%prior 5
5
MITS2 (10.5%)
6
VOLKSWAGEN1 (5.3%)
7
NISSAN1 (5.3%)
8
RAM1 (5.3%)
9
SUBARU1 (5.3%)
10
BUICK1 (5.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

Sex Distribution (24 persons with recorded sex)

Female14 (58.3%)
-17.6%prior 17
Male10 (41.7%)
-41.2%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased by 50% in count, from 10 crashes in September 2023 to 5 crashes in September 2024. Crashes in 40 mph zones also saw a significant 66.7% reduction in count, falling from 6 to 2 crashes. Conversely, crashes in 25 mph zones increased by 200% in count, rising from 1 crash to 3 crashes year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: SPENCER, MA
  • Total crash records analyzed: 11
  • Total persons involved: 24
  • Total vehicles involved: 19

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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/spencer/september-2024-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

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Spencer, MA Crash Report — September 2024 | ThatCarHitMe.com