Monthly Traffic Safety Analysis

24 CRASHES IN
FREETOWN, MA
NOVEMBER 2022

All metrics benchmarked againstNovember 2021

In November 2022, FREETOWN experienced 24 crashes, identical to the 24 crashes recorded in November 2021. Despite the stable number of total crashes, total injuries saw a significant 125% increase, rising from 4 in the prior period to 9 in the current period.

24

Total Crash Events

0

Persons Killed

9

125.0%was 4

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 · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes in FREETOWN remained stable year-over-year, with 24 crashes reported in both November 2021 and November 2022. However, the number of injured persons increased substantially, rising from 4 to 9, representing a 125% increase.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

9

Motorists Injured

Prior: 4125.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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; November 2021's peak crash day was Monday with 9 incidents, while November 2022 saw crashes peak on both Monday and Saturday with 6 incidents each. The peak hour for crashes also moved from 2 PM with 3 incidents in the prior period to 5 PM with 5 incidents in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

FREETOWN reported no fatalities in either November 2021 or November 2022. However, the total number of injured persons increased by 125%, from 4 in the prior period to 9 in the current period. The distribution of crash severities also shifted: in November 2021, there was 1 serious injury crash (4.2%) and 2 minor injury crashes (8.3%), whereas in November 2022, there were 5 minor injury crashes (20.8%) and 3 possible injury crashes (12.5%).

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes20.8%
150.0%prior 2
Possible Injury3possible injury crashes12.5%
No Injury16no injury crashes66.7%
-23.8%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record

Top Contributing Factors

The count of crashes attributed to 'No improper driving' decreased by 60%, from 15 in November 2021 to 6 in November 2022. Conversely, crashes due to 'Failure to keep in proper lane or running off road' saw a 400% increase, rising from 1 incident to 5. Additionally, 'Exceeded authorized speed limit' and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' each emerged as a contributing factor in one crash in the current period, having not been present in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving6 (25%)-60.0%prior 15
Failure to keep in proper lane or running off road5 (20.8%)
Followed too closely2 (8.3%)
Other improper action2 (8.3%)
Failed to yield right of way2 (8.3%)
Made an improper turn1 (4.2%)
Inattention1 (4.2%)
Exceeded authorized speed limit1 (4.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.2%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather decreased from 20 in November 2021 to 16 in November 2022, while crashes during rain increased from 1 to 5. A notable shift was observed in road surface conditions, with crashes on wet surfaces increasing from 3 to 8, coinciding with a decrease in crashes on dry surfaces from 21 to 16. Furthermore, crashes in 'Dark - roadway not lighted' conditions increased from 8 to 12, while those in 'Daylight' conditions decreased from 12 to 9.

Weather

Clear16 (66.7%)
-20.0%prior 20
Rain5 (20.8%)
Cloudy3 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash

Lighting

Dark - roadway not lighted12 (50.0%)
50.0%prior 8
Daylight9 (37.5%)
-25.0%prior 12
Dark - lighted roadway2 (8.3%)
Dark - unknown roadway lighting1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field

Road Surface

Dry16 (66.7%)
-23.8%prior 21
Wet8 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (36 vehicles)

1
TOYOTA6 (16.7%)
2
HONDA4 (11.1%)
3
HYUNDAI3 (8.3%)
4
FORD2 (5.6%)
5
FRHT2 (5.6%)
6
LEXUS2 (5.6%)
7
VOLVO2 (5.6%)
8
CHEVROLET2 (5.6%)
9
DODGE2 (5.6%)
10
NISSAN2 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records

2 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (39 persons with recorded sex)

Male23 (59.0%)
21.1%prior 19
Female16 (41.0%)
-5.9%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone increased by 100%, from 4 incidents in November 2021 to 8 incidents in November 2022. Conversely, crashes in the 40 mph zone decreased by 50%, from 6 to 3. The 65 mph zone maintained a consistent 8 crashes across both periods, and no fatalities were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-11-01 through 2022-11-30 (30 days)
  • Geographic scope: FREETOWN, MA
  • Total crash records analyzed: 24
  • Total persons involved: 43
  • Total vehicles involved: 36

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). "FREETOWN, MA Crash Intelligence Report: November 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/freetown/november-2022-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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Freetown, MA Crash Report — November 2022 | ThatCarHitMe.com