Monthly Traffic Safety Analysis

60 CRASHES IN
FAIRHAVEN, MA
JUNE 2023

All metrics benchmarked againstJune 2022

In June 2023, FAIRHAVEN experienced 60 total crashes, an increase of 15.4% compared to 52 crashes in June 2022. Total injuries also rose by 25.0%, from 12 to 15. A notable shift was observed in hit-and-run crashes, which decreased by 75.0% from 4 to 1.

60

15.4%was 52

Total Crash Events

0

Persons Killed

15

25.0%was 12

Persons Injured

1

-75.0%was 4

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. 4 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for FAIRHAVEN indicates an upward trend year-over-year, with total crashes increasing from 52 in June 2022 to 60 in June 2023. This represents an increase of 8 crashes, or 15.4%. Total injuries also increased by 25.0%, from 12 to 15.

1

Hit-and-Run Crashes — June 2023

-75.0% vs prior (4)

The number of hit-and-run crashes decreased significantly from 4 in June 2022 to 1 in June 2023. This resulted in a reduction of the hit-and-run rate from 7.7% of all crashes in the prior period to 1.7% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

15

Motorists Injured

Prior: 1225.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Friday (13 crashes) in June 2022 to Thursday (14 crashes) in June 2023. Similarly, the peak hour changed from 4 p.m. (6 crashes) in June 2022 to 5 p.m. (7 crashes) in June 2023. Monday crashes saw a significant increase from 3 to 11, while Friday crashes decreased from 13 to 8.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities in either June 2022 or June 2023. Total injuries increased from 12 to 15 year-over-year. Minor injury crashes (severity code 'B') increased from 5 (9.6% of crashes) to 8 (13.3% of crashes), while possible injury crashes (severity code 'C') decreased from 4 (7.7% of crashes) to 1 (1.7% of crashes).

Outcome by Severity (Crash Events)

Minor Injury8minor injury crashes13.3%
60.0%prior 5
Possible Injury1possible injury crashes1.7%
-75.0%prior 4
No Injury47no injury crashes78.3%
30.6%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record

Top Contributing Factors

Inattention remained a primary contributing factor, increasing by 7 crashes from 10 in June 2022 to 17 in June 2023, a 70.0% increase in count. 'Failure to keep in proper lane or running off road' saw a substantial increase in count, from 1 to 5 crashes, a 400.0% change. Conversely, 'Failed to yield right of way' decreased by 2 crashes, from 4 to 2, representing a 50.0% reduction in count.

Officer-Reported Primary Contributing Cause

Inattention17 (28.3%)70.0%prior 10
No improper driving13 (21.7%)18.2%prior 11
Failure to keep in proper lane or running off road5 (8.3%)
Other improper action5 (8.3%)
Driving too fast for conditions2 (3.3%)
Failed to yield right of way2 (3.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.7%)
Illness1 (1.7%)
Over-correcting/over-steering1 (1.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 42 to 46 year-over-year, and those in 'Rain' conditions increased from 1 to 5. Crashes under 'Daylight' conditions increased from 44 to 48, while crashes in 'Dark - lighted roadway' conditions increased from 3 to 7. The number of crashes on 'Wet' road surfaces increased from 4 to 10.

Weather

Clear46 (78.0%)
9.5%prior 42
Cloudy5 (8.5%)
Rain5 (8.5%)
Cloudy/Rain3 (5.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash

Lighting

Daylight48 (81.4%)
9.1%prior 44
Dark - lighted roadway7 (11.9%)
Dusk3 (5.1%)
Dawn1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field

Road Surface

Dry49 (83.1%)
8.9%prior 45
Wet10 (16.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 100 to 114. Honda remained a top vehicle make, increasing from 13 to 18 vehicles, while Hyundai saw a significant rise from 1 to 8 vehicles involved. Regarding persons, the 0-15 age group saw an increase from 4 to 9 individuals involved, and the 26-34 age group saw a decrease from 20 to 12 individuals.

Top Vehicle Makes (114 vehicles)

1
HONDA18 (15.8%)
38.5%prior 13
2
FORD16 (14%)
23.1%prior 13
3
TOYOTA13 (11.4%)
18.2%prior 11
4
HYUNDAI8 (7%)
5
NISSAN5 (4.4%)
0.0%prior 5
6
GMC5 (4.4%)
7
KIA5 (4.4%)
0.0%prior 5
8
RAM4 (3.5%)
9
SUBARU3 (2.6%)
10
VOLKSWAGEN3 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records

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

Sex Distribution (123 persons with recorded sex)

Male68 (55.3%)
11.5%prior 61
Female55 (44.7%)
5.8%prior 52

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 MPH speed zones increased by 7, from 14 in June 2022 to 21 in June 2023. Crashes in 25 MPH zones decreased by 5, from 25 to 20. There were no fatal crashes reported in any speed limit zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-06-01 through 2023-06-30 (30 days)
  • Geographic scope: FAIRHAVEN, MA
  • Total crash records analyzed: 60
  • Total persons involved: 140
  • Total vehicles involved: 114

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). "FAIRHAVEN, MA Crash Intelligence Report: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fairhaven/june-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

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Fairhaven, MA Crash Report — June 2023 | ThatCarHitMe.com