Monthly Traffic Safety Analysis

33 CRASHES IN
LUDLOW, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

Total crashes in November 2025 decreased to 33, a 15.4% reduction from the 39 crashes reported in November 2024. A notable shift is the doubling of hit-and-run crashes, increasing from 2 in the prior period to 4 in the current period. This also led to an increase in the hit-and-run rate from 5.1% to 12.1%.

33

-15.4%was 39

Total Crash Events

0

Persons Killed

10

-28.6%was 14

Persons Injured

4

100.0%was 2

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity showed a downward trend year-over-year. Total crashes decreased by 15.4%, from 39 in November 2024 to 33 in November 2025. Similarly, total injuries decreased by 28.6%, from 14 to 10 during the same period.

4

Hit-and-Run Crashes — November 2025

100.0% vs prior (2)

Hit-and-run crashes increased from 2 in November 2024 to 4 in November 2025, marking a 100% increase in count. This also led to an increase in the hit-and-run rate, which rose from 5.1% to 12.1% of all crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 2-50.0%

9

Motorists Injured

Prior: 12-25.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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 with 10 crashes in November 2024 to Wednesday with 8 crashes in November 2025. The peak hour also changed, moving from 8 p.m. with 5 crashes in the prior period to 5 p.m. with 7 crashes in the current period. This indicates a shift in the most frequent times and days for crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total injuries decreased from 14 in November 2024 to 10 in November 2025, while fatalities remained at 0 in both periods. The prior period reported 12 minor injuries, whereas the current period saw a reduction to 2 minor injuries but introduced 1 serious injury and 4 possible injuries. This suggests a change in the distribution of injury severities.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3%
Minor Injury2minor injury crashes6.1%
-83.3%prior 12
Possible Injury4possible injury crashes12.1%
No Injury23no injury crashes69.7%
-14.8%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Inattention" increased from 7 in November 2024 to 12 in November 2025, representing a 71.4% increase in count. Conversely, crashes due to "Failed to yield right of way" decreased significantly from 7 to 2, a 71.4% decrease in count. "No improper driving" also saw a slight decrease in count, from 6 to 5 crashes.

Officer-Reported Primary Contributing Cause

Inattention12 (36.4%)71.4%prior 7
No improper driving5 (15.2%)-16.7%prior 6
Failure to keep in proper lane or running off road3 (9.1%)
Distracted2 (6.1%)
Failed to yield right of way2 (6.1%)-71.4%prior 7
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (6.1%)
Visibility obstructed2 (6.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (3%)
Illness1 (3%)
Disregarded traffic signs, signals, road markings1 (3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 23 in November 2024 to 15 in November 2025. Crashes during "Dark - lighted roadway" conditions increased from 13 to 17, while "Daylight" crashes decreased from 15 to 11. Crashes on dry road surfaces decreased from 32 to 24, but those on wet surfaces slightly increased from 7 to 8.

Weather

Clear15 (45.5%)
-34.8%prior 23
Clear/Other4 (12.1%)
Rain4 (12.1%)
Cloudy3 (9.1%)
Cloudy/Rain2 (6.1%)
Rain/Other1 (3.0%)
Clear/Clear1 (3.0%)
-83.3%prior 6
Clear/Cloudy1 (3.0%)
Cloudy/Clear1 (3.0%)
Cloudy/Snow1 (3.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Dark - lighted roadway17 (53.1%)
30.8%prior 13
Daylight11 (34.4%)
-26.7%prior 15
Dark - roadway not lighted3 (9.4%)
Dawn1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry24 (72.7%)
-25.0%prior 32
Wet8 (24.2%)
14.3%prior 7
Sand, mud, dirt, oil, gravel1 (3.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 70 in November 2024 to 56 in November 2025. Crashes involving Toyota vehicles decreased from 10 to 5, and Hyundai vehicles decreased from 9 to 4. Across age groups, the total number of persons involved in crashes decreased from 97 to 70, with notable decreases in the 26-34 age group (from 18 to 8) and 35-44 age group (from 19 to 13).

Top Vehicle Makes (56 vehicles)

1
TOYOTA5 (8.9%)
-50.0%prior 10
2
NISSAN5 (8.9%)
-16.7%prior 6
3
FORD5 (8.9%)
-28.6%prior 7
4
HYUNDAI4 (7.1%)
-55.6%prior 9
5
HONDA4 (7.1%)
-20.0%prior 5
6
CHEVROLET4 (7.1%)
7
GMC3 (5.4%)
8
SUBARU3 (5.4%)
9
MAZDA2 (3.6%)
10
VOLKSWAGEN2 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

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

Sex Distribution (61 persons with recorded sex)

Male35 (57.4%)
-27.1%prior 48
Female26 (42.6%)
-36.6%prior 41

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph zones increased from 8 in November 2024 to 15 in November 2025. Conversely, crashes in 30 mph zones decreased from 11 to 5, and those in 65 mph zones decreased from 10 to 3. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-11-01 through 2025-11-30 (30 days)
  • Geographic scope: LUDLOW, MA
  • Total crash records analyzed: 33
  • Total persons involved: 70
  • Total vehicles involved: 56

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). "LUDLOW, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ludlow/november-2025-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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Ludlow, MA Crash Report — November 2025 | ThatCarHitMe.com