Monthly Traffic Safety Analysis

7 CRASHES IN
ROWLEY, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

In January 2023, ROWLEY experienced 7 total crashes, marking a 133.3% increase compared to the 3 crashes recorded in January 2022. This substantial rise in overall crash incidents is the most significant year-over-year shift for the period.

7

133.3%was 3

Total Crash Events

0

Persons Killed

2

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

Trend Summary

The overall trend indicates a significant increase in crash incidents, with total crashes rising from 3 in January 2022 to 7 in January 2023, representing a 133.3% increase. Despite this rise in crash volume, the number of total injuries remained stable at 2 for both periods, and no fatalities were reported in either year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns shifted year-over-year, with the peak day for crashes moving from Friday in January 2022 (1 crash) to Monday in January 2023 (3 crashes). The peak crash hour also changed, with January 2022 seeing a peak at 4 PM (1 crash), while January 2023 experienced a peak at 12 PM with 2 crashes.

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

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

Crash Severity Breakdown

The distribution of crash severity showed some changes, though no fatal crashes occurred in either January 2022 or January 2023. In January 2023, 1 crash resulted in minor injury (14.3% of crashes) and 6 crashes resulted in no injury (85.7%). In contrast, January 2022 recorded 1 minor injury crash (33.3% of crashes) and 1 possible injury crash (33.3% of crashes).

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes14.3%
0.0%prior 1
No Injury6no injury crashes85.7%
500.0%prior 1

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

The contributing factors for crashes showed shifts between the two periods. "Failed to yield right of way" remained consistent, contributing to 1 crash in both January 2022 and January 2023. Factors such as "Driving too fast for conditions," "Inattention," and "Operating defective equipment" each contributed to 1 crash in January 2023, but were not listed among the top factors in January 2022, which instead listed "Distracted" and "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" as contributing to 1 crash each.

Officer-Reported Primary Contributing Cause

No improper driving3 (42.9%)
Driving too fast for conditions1 (14.3%)
Failed to yield right of way1 (14.3%)
Inattention1 (14.3%)
Operating defective equipment1 (14.3%)

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

Road & Environmental Conditions

Regarding lighting conditions, crashes occurring in "Daylight" increased from 2 in January 2022 to 4 in January 2023. Crashes in "Dark - lighted roadway" also increased from 1 to 2, and 1 crash occurred in "Dark - roadway not lighted" in January 2023 where none were reported in January 2022. Data for weather and road surface conditions were not available for comparison in January 2022.

Weather

Clear3 (42.9%)
Snow2 (28.6%)
Cloudy1 (14.3%)
Sleet, hail (freezing rain or drizzle)/Snow1 (14.3%)

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

Lighting

Daylight4 (57.1%)
Dark - lighted roadway2 (28.6%)
Dark - roadway not lighted1 (14.3%)

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

Road Surface

Dry4 (57.1%)
Snow2 (28.6%)
Wet1 (14.3%)

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

Vehicles & Demographics

Top Vehicle Makes (11 vehicles)

1
TOYOTA3 (27.3%)
2
BMW2 (18.2%)
3
CHRYSLER1 (9.1%)
4
AUDI1 (9.1%)
5
HONDA1 (9.1%)
6
MITS1 (9.1%)
7
FORD1 (9.1%)
8
CHEVROLET1 (9.1%)

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

Sex Distribution (13 persons with recorded sex)

Male8 (61.5%)
100.0%prior 4
Female5 (38.5%)
150.0%prior 2

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

Speed Limit Zones

Crashes in the 25 mph speed limit zone increased from 1 in January 2022 to 4 in January 2023, and crashes in the 40 mph zone increased from 1 to 3 during the same period. Conversely, the 50 mph zone, which had 1 crash in January 2022, reported no crashes in January 2023. No fatal crashes were recorded in any speed zone for either period.

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

Data Coverage

  • Reporting period: 2023-01-01 through 2023-01-31 (31 days)
  • Geographic scope: ROWLEY, MA
  • Total crash records analyzed: 7
  • Total persons involved: 13
  • Total vehicles involved: 11

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). "ROWLEY, MA Crash Intelligence Report: January 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/rowley/january-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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Rowley, MA Crash Report — January 2023 | ThatCarHitMe.com