Monthly Traffic Safety Analysis

52 CRASHES IN
BOURNE, MA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

In January 2026, Bourne experienced 52 total crashes, a substantial increase from the 27 crashes recorded in January 2025. This represents a 92.6% rise in total crashes year-over-year. The most notable shift was the significant increase in total injuries, which rose from 6 to 22.

52

92.6%was 27

Total Crash Events

0

Persons Killed

22

266.7%was 6

Persons Injured

4

-20.0%was 5

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant increase in crash activity, with total crashes rising from 27 in January 2025 to 52 in January 2026, an increase of 92.6%. Concurrently, total injuries surged by 266.7%, from 6 to 22 over the same period.

4

Hit-and-Run Crashes — January 2026

-20.0% vs prior (5)

The number of hit-and-run crashes decreased from 5 in January 2025 to 4 in January 2026. Concurrently, the hit-and-run rate significantly declined from 18.5% of all crashes to 7.7% of all crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

21

Motorists Injured

Prior: 6250.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted year-over-year. In January 2026, Thursday became the peak day with 12 crashes, whereas Saturday was the peak day in January 2025 with 6 crashes. The peak hour also changed from 5 PM (4 crashes) in the prior period to 10 AM (6 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either January 2025 or January 2026. However, total injuries increased from 6 to 22. The proportion of minor injury crashes rose from 11.1% to 30.8% of all crashes, while crashes with no injury decreased from 81.5% to 61.5% of the total.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.9%
0.0%prior 1
Minor Injury16minor injury crashes30.8%
433.3%prior 3
Possible Injury2possible injury crashes3.8%
100.0%prior 1
No Injury32no injury crashes61.5%
45.5%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving,' increased from 4 crashes in January 2025 to 12 crashes in January 2026, a 200% increase. 'Followed too closely' crashes rose from 3 to 7, a 133.3% increase, while 'Inattention' crashes increased from 2 to 6, a 200% increase, moving into the top three factors. Conversely, 'Driving too fast for conditions' decreased from 4 crashes to 3 crashes, a 25% decrease, falling out of the top three factors by count.

Officer-Reported Primary Contributing Cause

No improper driving12 (23.1%)
Followed too closely7 (13.5%)
Inattention6 (11.5%)
Disregarded traffic signs, signals, road markings4 (7.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (7.7%)
Driving too fast for conditions3 (5.8%)
Other improper action3 (5.8%)
Failed to yield right of way2 (3.8%)
Over-correcting/over-steering2 (3.8%)
Visibility obstructed2 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 13 to 29 year-over-year. Crashes during 'Daylight' conditions rose from 16 to 34, and crashes on 'Dry' road surfaces increased from 17 to 29. These increases are consistent with the overall rise in total crash counts.

Weather

Clear29 (55.8%)
123.1%prior 13
Snow8 (15.4%)
60.0%prior 5
Clear/Clear7 (13.5%)
16.7%prior 6
Cloudy/Cloudy2 (3.8%)
Cloudy2 (3.8%)
Snow/Blowing sand, snow2 (3.8%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.9%)
Clear/Cloudy1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash

Lighting

Daylight34 (65.4%)
112.5%prior 16
Dark - lighted roadway9 (17.3%)
80.0%prior 5
Dark - roadway not lighted7 (13.5%)
16.7%prior 6
Dark - unknown roadway lighting2 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field

Road Surface

Dry29 (56.9%)
70.6%prior 17
Wet9 (17.6%)
80.0%prior 5
Snow8 (15.7%)
Ice4 (7.8%)
Slush1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (91 vehicles)

1
TOYOTA11 (12.1%)
120.0%prior 5
2
JEEP8 (8.8%)
3
FORD8 (8.8%)
14.3%prior 7
4
HONDA8 (8.8%)
5
CHEVROLET7 (7.7%)
16.7%prior 6
6
GMC5 (5.5%)
7
BUIC4 (4.4%)
8
NISSAN4 (4.4%)
9
SUBARU3 (3.3%)
10
DODGE3 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records

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

Sex Distribution (105 persons with recorded sex)

Male59 (56.2%)
103.4%prior 29
Female46 (43.8%)
360.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone saw the largest increase, rising from 3 crashes in January 2025 to 11 crashes in January 2026. Crashes also increased in the 50 mph zone (from 1 to 6) and the 55 mph zone (from 3 to 7). No fatal crashes were reported in any speed zone during either period.

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

Data Coverage

  • Reporting period: 2026-01-01 through 2026-01-31 (31 days)
  • Geographic scope: BOURNE, MA
  • Total crash records analyzed: 52
  • Total persons involved: 116
  • Total vehicles involved: 91

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