ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TEMPLETON, 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/templeton/2024-annual-report
Yearly Traffic Safety Analysis
144 CRASHES IN
TEMPLETON, MA
2024
In 2024, Templeton recorded 144 total traffic crashes, a 19% increase from the 121 crashes reported in 2023. While total fatalities remained constant at one death in each period, the number of injuries rose from 39 to 52. A significant year-over-year shift was observed in the number of rear-end collisions, which increased from 7 in 2023 to 18 in 2024.
144
▲ 19.0%was 121
Total Crash Events
1
Persons Killed
52
▲ 33.3%was 39
Persons Injured
2
▼ -50.0%was 4
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. 4 crashes with unreported severity are 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
Traffic crashes in Templeton showed an upward trend, increasing by 19% from 121 in 2023 to 144 in 2024. This rise was accompanied by a 33.3% increase in total injuries, which grew from 39 to 52. The number of fatalities remained stable, with one fatality recorded in both years.
2
Hit-and-Run Crashes — 2024
▼ -50.0% vs prior (4)
Hit-and-run incidents decreased in both absolute numbers and as a proportion of total crashes. The number of hit-and-run crashes fell from 4 in 2023 to 2 in 2024. Consequently, the hit-and-run rate declined from 3.3% of all crashes in the prior year to 1.4% in the current year.
Vulnerable Road User Casualties
1
Motorists Killed
52
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 shifted between the two years. In 2024, the peak day for crashes was Saturday with 30 incidents, whereas in 2023, Saturday and Wednesday were tied for the most frequent crash day with 20 incidents each. The peak hour also changed, moving from the 4 p.m. hour in 2023 (10 crashes) to the 7 a.m. hour in 2024 (13 crashes).
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 number of fatal crashes remained unchanged at one in both 2023 and 2024, resulting in a slight decrease in the fatal crash rate from 0.83% to 0.69% due to the higher total number of crashes in the current period. The proportion of crashes involving serious injuries decreased from 3.3% to 2.1%. Conversely, crashes resulting in minor injuries increased as a share of the total, rising from 13.2% in 2023 to 14.6% 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
While 'No improper driving' was the most common factor listed in both periods, its count increased from 36 to 47. Significant shifts occurred among other factors; crashes attributed to 'Followed too closely' saw a substantial increase in count, rising from 1 to 9 incidents. Similarly, the count of crashes involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from 8 to 12, a 50% rise. In contrast, crashes citing 'Inattention' as a factor decreased from 14 in 2023 to 4 in 2024.
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
The proportion of crashes occurring on non-dry road surfaces increased slightly from 29.8% in 2023 to 31.9% in 2024, driven by a rise in crashes on snowy roads from 10 to 19 incidents. Regarding lighting, crashes in daylight conditions made up a larger share of the total in 2024 (56.9%) compared to 2023 (53.7%). The proportion of crashes occurring in dark conditions decreased from 41.3% to 33.3%.
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 demographic profile of individuals involved in crashes shifted, with the 26-34 age group becoming the most represented in 2024 with 54 persons, up from 40 in 2023. In the prior year, the 35-44 age group was the largest. In terms of vehicle makes, Toyota became the most frequently involved vehicle in 2024 with 28 vehicles, overtaking Ford, which saw its involvement decrease from 27 to 19 vehicles. The number of Subarus involved in crashes doubled from 8 to 16.
Top Vehicle Makes (198 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
6 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (236 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
Crashes increased across several common speed zones, with the largest count increases in the 55 mph zone (from 29 to 37 crashes) and the 30 mph zone (from 27 to 34 crashes). The location of the year's single fatal crash also shifted between periods. In 2023, the fatal crash occurred in a 30 mph zone, while in 2024, it occurred in a 45 mph zone.
Fatal crashes by zone: 45 mph: 1 of 15 (6.667%)
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: TEMPLETON, MA
- Total crash records analyzed: 144
- Total persons involved: 244
- Total vehicles involved: 198
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: 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/templeton/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