Monthly Traffic Safety Analysis

24 CRASHES IN
LAKEVILLE, MA
NOVEMBER 2022

All metrics benchmarked againstNovember 2021

In November 2022, Lakeville experienced a 26.3% increase in total crashes compared to November 2021, rising from 19 to 24 crashes. Total injuries also increased by 25%, from 4 to 5. A notable shift includes the emergence of DUI-related crashes and speeding-related crashes, with 2 crashes recorded for each in the current period, up from zero in the prior period.

24

26.3%was 19

Total Crash Events

0

Persons Killed

5

25.0%was 4

Persons Injured

0

-100.0%was 1

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.

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, crash data for Lakeville shows an increasing trend year-over-year. Total crashes rose from 19 in November 2021 to 24 in November 2022, marking a 26.3% increase. Similarly, the number of injured persons increased from 4 to 5, representing a 25% rise in injuries.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 425.0%

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 patterns of crashes showed some shifts year-over-year. While Saturday remained a peak day for crashes in both periods, the number of crashes on Saturdays decreased from 6 in November 2021 to 5 in November 2022. The peak hour for crashes shifted from 7p (4 crashes) in the prior period to 5p (5 crashes) in the current period, and Sunday, Tuesday, and Wednesday also emerged as peak days with 5 crashes each 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

The distribution of crash severity changed between the two periods, though no fatal crashes occurred in either. Serious injuries doubled from 1 crash in November 2021 to 2 crashes in November 2022, and minor injuries also doubled from 1 to 2 crashes. The prior period recorded 2 crashes with possible injuries, a category not present in the current period, while the proportion of no-injury crashes increased from 78.9% to 83.3%.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes8.3%
100.0%prior 1
Minor Injury2minor injury crashes8.3%
100.0%prior 1
No Injury20no injury crashes83.3%
33.3%prior 15

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

Analysis of contributing factors reveals shifts in crash causation. Crashes attributed to "No improper driving" decreased by 3, from 11 in the prior period to 8 in the current period. Conversely, "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" increased by 2 crashes, from 1 to 3. "Fatigued/asleep" crashes also increased from 0 to 2, and "Inattention" crashes decreased by 3, from 5 to 2.

Officer-Reported Primary Contributing Cause

No improper driving8 (33.3%)-27.3%prior 11
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (12.5%)
Fatigued/asleep2 (8.3%)
Inattention2 (8.3%)-60.0%prior 5
Visibility obstructed2 (8.3%)
Failed to yield right of way2 (8.3%)
Failure to keep in proper lane or running off road1 (4.2%)
Over-correcting/over-steering1 (4.2%)
Physical impairment1 (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

Weather conditions for crashes remained predominantly clear across both periods, with 'Clear' conditions increasing from 10 to 11 crashes and 'Clear/Clear' increasing from 7 to 8 crashes. Lighting conditions saw an increase in daylight crashes from 7 to 9 and dark-not-lighted roadway crashes from 7 to 8. 'Cloudy/Rain' conditions appeared in the current period, contributing to 2 crashes, while 'Dawn' crashes decreased from 1 to 0.

Weather

Clear11 (47.8%)
10.0%prior 10
Clear/Clear8 (34.8%)
14.3%prior 7
Cloudy2 (8.7%)
Cloudy/Rain2 (8.7%)

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

Lighting

Daylight9 (37.5%)
28.6%prior 7
Dark - roadway not lighted8 (33.3%)
14.3%prior 7
Dark - lighted roadway5 (20.8%)
Dark - unknown roadway lighting1 (4.2%)
Dusk1 (4.2%)

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

Road Surface

Dry21 (87.5%)
Wet3 (12.5%)

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 (31 vehicles)

1
FORD6 (19.4%)
2
TOYOTA4 (12.9%)
3
CHEVROLET3 (9.7%)
4
JEEP3 (9.7%)
5
HYUNDAI3 (9.7%)
6
DODGE2 (6.5%)
7
MAZDA2 (6.5%)
8
SUBARU1 (3.2%)
9
HONDA1 (3.2%)
10
GMC1 (3.2%)

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

Sex Distribution (44 persons with recorded sex)

Female22 (50.0%)
69.2%prior 13
Male22 (50.0%)
4.8%prior 21

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 recorded speed zones increased from 17 in November 2021 to 24 in November 2022. The 40 mph zone saw an increase from 4 to 6 crashes, and the 50 mph zone increased from 1 to 3 crashes. The 35 mph zone experienced a decrease from 5 to 3 crashes, and the 25 mph speed zone, which had no recorded crashes in the prior period, accounted for 3 crashes in the current 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: LAKEVILLE, MA
  • Total crash records analyzed: 24
  • Total persons involved: 44
  • Total vehicles involved: 31

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). "LAKEVILLE, 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/lakeville/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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Lakeville, MA Crash Report — November 2022 | ThatCarHitMe.com