Monthly Traffic Safety Analysis

13 CRASHES IN
FREETOWN, MA
MAY 2023

All metrics benchmarked againstMay 2022

In FREETOWN, MA, total crashes decreased by 40.9%, from 22 in May 2022 to 13 in May 2023. The most notable shift was the absence of fatal crashes in May 2023, down from one fatality recorded in May 2022.

13

-40.9%was 22

Total Crash Events

0

-100.0%was 1

Persons Killed

7

Persons Injured

0

-100.0%was 1

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 · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant decrease in crash activity year-over-year, with total crashes falling from 22 to 13, representing a 40.9% reduction. Fatalities also decreased, from 1 in May 2022 to 0 in May 2023, while the total number of injured persons remained stable at 7 in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

7

Motorists Injured

Prior: 70.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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. The peak day for crashes moved from Sunday, with 7 crashes in May 2022, to Monday, with 4 crashes in May 2023. Similarly, the peak hour for crashes changed from 5 AM, which saw 3 crashes in May 2022, to 2 PM, with 2 crashes in May 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate decreased from 4.55% in May 2022 (1 fatal crash out of 22 total) to 0% in May 2023 (0 fatal crashes out of 13 total). While the number of serious injury crashes decreased from 2 to 1, minor injury crashes increased from 2 to 3. The total number of injured persons remained consistent at 7 in both periods.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes7.7%
-50.0%prior 2
Minor Injury3minor injury crashes23.1%
50.0%prior 2
No Injury9no injury crashes69.2%
-43.8%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'No improper driving,' decreased significantly from 7 crashes in May 2022 to 2 crashes in May 2023, a 71.4% decrease in count, and its share dropped from 31.8% to 15.4%. 'Inattention' remained stable at 2 crashes in both periods, increasing its share from 9.1% to 15.4%. New factors like 'Driving too fast for conditions' and 'Followed too closely' each contributed to 2 crashes in May 2023, while they were not listed in May 2022 data.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions2 (15.4%)
Inattention2 (15.4%)
No improper driving2 (15.4%)-71.4%prior 7
Followed too closely2 (15.4%)
Disregarded traffic signs, signals, road markings1 (7.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (7.7%)
Exceeded authorized speed limit1 (7.7%)
Fatigued/asleep1 (7.7%)
History heart/epilepsy/fainting1 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 16 in May 2022 to 10 in May 2023, while rain-related crashes decreased from 2 to 1. Crashes occurring during daylight decreased from 13 to 10, and those in 'Dark - roadway not lighted' conditions decreased from 4 to 3. Wet road crashes remained stable at 2 in both periods, but their proportion of total crashes increased from 9.1% in May 2022 to 15.4% in May 2023.

Weather

Clear10 (76.9%)
-37.5%prior 16
Cloudy1 (7.7%)
Cloudy/Rain1 (7.7%)
Rain1 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight10 (76.9%)
-23.1%prior 13
Dark - roadway not lighted3 (23.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry11 (84.6%)
-45.0%prior 20
Wet2 (15.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (22 vehicles)

1
TOYOTA4 (18.2%)
2
FORD4 (18.2%)
-33.3%prior 6
3
HONDA3 (13.6%)
4
VOLKSWAGEN2 (9.1%)
5
FRHT2 (9.1%)
6
JEEP2 (9.1%)
7
MERCEDES-BENZ1 (4.5%)
8
RAM1 (4.5%)
9
SUBARU1 (4.5%)
10
CHEVROLET1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

Sex Distribution (27 persons with recorded sex)

Male19 (70.4%)
5.6%prior 18
Female8 (29.6%)
-33.3%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone decreased from 9 in May 2022 to 6 in May 2023, with the single fatal crash in May 2022 occurring in this zone. The 30 mph zone also saw a decrease from 4 crashes to 2 crashes, while the 40 mph zone increased from 1 crash to 2 crashes. Speed zones of 15 mph and 20 mph each recorded 1 crash in May 2023, not appearing in the May 2022 data, while 35 mph and 45 mph zones present in May 2022 were not recorded in May 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: FREETOWN, MA
  • Total crash records analyzed: 13
  • Total persons involved: 27
  • Total vehicles involved: 22

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: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/freetown/may-2023-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

Freetown, MA Crash Report — May 2023 | ThatCarHitMe.com