Monthly Traffic Safety Analysis

12 CRASHES IN
TEMPLETON, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

In September 2024, TEMPLETON experienced 12 total crashes, which is unchanged from the 12 crashes reported in September 2023. However, total injuries increased by 100%, rising from 2 in the prior period to 4 in the current period. Notably, there were no fatal crashes in either period.

12

Total Crash Events

0

Persons Killed

4

100.0%was 2

Persons Injured

0

Fatal Crash Events

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

The total number of crashes in TEMPLETON remained stable year-over-year, with 12 crashes recorded in both September 2023 and September 2024. Despite stable crash counts, total injuries saw a significant increase of 100%, rising from 2 to 4. Fatalities remained at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 2100.0%

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 patterns of crashes shifted year-over-year, with the peak crash day moving from Saturday in September 2023 (4 crashes) to Thursday in September 2024 (3 crashes). The peak crash hour also changed, moving from 1 AM (2 crashes) in the prior period to 3 PM (2 crashes) in the current period. This indicates a shift towards more daytime crashes in the current period, with 10 crashes occurring between 7 AM and 3 PM, compared to 5 crashes between 12 AM and 2 AM in the prior year.

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

While fatal crashes remained at zero in both September 2023 and September 2024, the number of injuries increased substantially, rising from 2 to 4. Minor injuries (severity 'B') saw a notable increase, accounting for 4 crashes (33.3% of total crashes) in the current period, up from 1 crash (8.3%) in the prior period. Additionally, possible injuries (severity 'C'), which accounted for 1 crash (8.3%) in September 2023, were not reported in September 2024.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes33.3%
300.0%prior 1
No Injury8no injury crashes66.7%
-11.1%prior 9

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

Contributing factors saw shifts in prevalence year-over-year. 'Failed to yield right of way' increased from 0 crashes in September 2023 to 3 crashes in September 2024. Conversely, 'Inattention' and 'Physical impairment', which each contributed to 2 crashes in the prior period, were not reported as factors in the current period. 'Followed too closely' also emerged as a factor in the current period with 2 crashes, up from 0 in the prior period.

Officer-Reported Primary Contributing Cause

Failed to yield right of way3 (25%)
No improper driving2 (16.7%)
Followed too closely2 (16.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (8.3%)
Over-correcting/over-steering1 (8.3%)
Visibility obstructed1 (8.3%)
Failure to keep in proper lane or running off road1 (8.3%)
Operating defective equipment1 (8.3%)

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

Weather conditions for crashes showed a slight increase in 'Clear' conditions from 6 to 7 crashes, and 'Cloudy' conditions increased from 1 to 4 crashes year-over-year. Crashes in 'Rain' conditions decreased from 2 to 0. Lighting conditions shifted significantly, with 'Daylight' crashes increasing from 4 in September 2023 to 10 in September 2024, while crashes in 'Dark - lighted roadway' decreased from 4 to 1, and 'Dark - roadway not lighted' decreased from 3 to 1.

Weather

Clear7 (58.3%)
16.7%prior 6
Cloudy4 (33.3%)
Clear/Clear1 (8.3%)

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

Lighting

Daylight10 (83.3%)
Dark - lighted roadway1 (8.3%)
Dark - roadway not lighted1 (8.3%)

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

Vehicles & Demographics

Top Vehicle Makes (20 vehicles)

1
HYUNDAI3 (15%)
2
NISSAN3 (15%)
3
HONDA2 (10%)
4
GMC2 (10%)
5
HD1 (5%)
6
KIA1 (5%)
7
SUBARU1 (5%)
8
TOYOTA1 (5%)
-80.0%prior 5
9
ACURA1 (5%)
10
VOLKSWAGEN1 (5%)

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

Sex Distribution (22 persons with recorded sex)

Male12 (54.5%)
-7.7%prior 13
Female10 (45.5%)
233.3%prior 3

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

Crash distribution across speed zones shifted year-over-year, with an increase in crashes in lower speed zones. Crashes in 25 mph zones increased from 1 to 2, 30 mph zones from 2 to 4, and 35 mph zones from 1 to 4. Conversely, crashes in 45 mph zones decreased from 4 to 0, and 55 mph zones decreased from 2 to 1. There were no fatal crashes reported in any speed zone during either period.

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: TEMPLETON, MA
  • Total crash records analyzed: 12
  • Total persons involved: 22
  • Total vehicles involved: 20

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). "TEMPLETON, 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/templeton/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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Templeton, MA Crash Report — September 2024 | ThatCarHitMe.com