Monthly Traffic Safety Analysis

23 CRASHES IN
BOLTON, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

In January 2023, Bolton experienced 23 crashes, marking a significant 109.1% increase compared to the 11 crashes recorded in January 2022. While no fatalities occurred in either period, DUI-related crashes emerged as a new concern in the current period, with 1 crash reported compared to none in the prior year.

23

109.1%was 11

Total Crash Events

0

Persons Killed

11

266.7%was 3

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

Trend Summary

The overall trend indicates a substantial increase in crashes year-over-year, with total crashes rising from 11 in January 2022 to 23 in January 2023. This represents a 109.1% increase in crash incidents for the month.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

11

Motorists Injured

Prior: 3266.7%

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

The peak day for crashes remained Tuesday in both periods, although the number of crashes on Tuesdays more than doubled from 3 in January 2022 to 7 in January 2023. The peak crash hour shifted from 2 PM with 2 crashes in the prior period to 8 PM with 3 crashes in the current period. Crashes on Mondays also saw a notable increase, rising from 1 to 5 year-over-year.

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

No fatal crashes were recorded in either January 2022 or January 2023. However, total injuries significantly increased from 3 in the prior period to 11 in the current period. The current period saw 1 serious injury crash, which was not present in the prior period, and minor injury crashes rose from 1 to 4 year-over-year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.3%
Minor Injury4minor injury crashes17.4%
300.0%prior 1
Possible Injury1possible injury crashes4.3%
0.0%prior 1
No Injury17no injury crashes73.9%
88.9%prior 9

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

"No improper driving" became the most frequent contributing factor in January 2023 with 10 crashes, a substantial increase from 2 crashes in January 2022. Crashes attributed to "Failed to yield right of way" doubled from 2 to 4, and "Driving too fast for conditions" increased from 2 to 3 crashes. "Failure to keep in proper lane or running off road" emerged with 2 crashes in the current period, while it was not a listed factor in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving10 (43.5%)
Failed to yield right of way4 (17.4%)
Driving too fast for conditions3 (13%)
Followed too closely2 (8.7%)
Failure to keep in proper lane or running off road2 (8.7%)
Inattention1 (4.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.3%)

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

Crashes in "Clear" weather conditions saw a slight increase from 7 to 8, while crashes in "Cloudy" conditions rose sharply from 1 to 7. "Snow" conditions were associated with 4 crashes in January 2023, up from 1 in January 2022. For road surfaces, "Dry" conditions saw an increase from 8 to 12 crashes, and "Snow" conditions, which were not explicitly noted in the prior period, accounted for 5 crashes in the current period.

Weather

Clear8 (34.8%)
14.3%prior 7
Cloudy7 (30.4%)
Snow4 (17.4%)
Snow/Sleet, hail (freezing rain or drizzle)1 (4.3%)
Rain1 (4.3%)
Clear/Other1 (4.3%)
Snow/Clear1 (4.3%)

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

Lighting

Daylight13 (56.5%)
116.7%prior 6
Dark - roadway not lighted6 (26.1%)
Dark - lighted roadway3 (13.0%)
Dusk1 (4.3%)

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

Road Surface

Dry12 (52.2%)
50.0%prior 8
Snow5 (21.7%)
Wet4 (17.4%)
Ice2 (8.7%)

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 (36 vehicles)

1
TOYOTA8 (22.2%)
33.3%prior 6
2
HONDA3 (8.3%)
3
CHEVROLET3 (8.3%)
4
FORD3 (8.3%)
5
SUBARU3 (8.3%)
6
MAZDA2 (5.6%)
7
LEXUS2 (5.6%)
8
BMW2 (5.6%)
9
MERCURY1 (2.8%)
10
NISSAN1 (2.8%)

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

Sex Distribution (41 persons with recorded sex)

Female24 (58.5%)
166.7%prior 9
Male17 (41.5%)
-10.5%prior 19

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 30 MPH zones doubled from 3 in January 2022 to 6 in January 2023, and crashes in 40 MPH zones also doubled from 3 to 6. A notable increase was observed in 65 MPH zones, which rose from 1 crash to 5 crashes year-over-year. Additionally, 20 MPH and 25 MPH zones recorded 2 and 1 crashes respectively in the current period, which were not present in the prior period's data.

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: BOLTON, MA
  • Total crash records analyzed: 23
  • Total persons involved: 42
  • 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). "BOLTON, 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/bolton/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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Bolton, MA Crash Report — January 2023 | ThatCarHitMe.com