Monthly Traffic Safety Analysis

48 CRASHES IN
BILLERICA, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

In September 2025, BILLERICA experienced 48 total crashes, a decrease from 55 crashes in September 2024, representing a 12.7% reduction. This period saw a notable decrease in total injuries, falling from 22 to 13 year-over-year. The most significant shift was a 40.9% reduction in total injuries.

48

-12.7%was 55

Total Crash Events

0

Persons Killed

13

-40.9%was 22

Persons Injured

6

-25.0%was 8

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 · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Total crashes in BILLERICA decreased by 12.7%, from 55 in September 2024 to 48 in September 2025. Concurrently, total injuries saw a substantial decline of 40.9%, dropping from 22 to 13 over the same period, indicating an overall downward trend in crash severity and frequency.

6

Hit-and-Run Crashes — September 2025

-25.0% vs prior (8)

Hit-and-run crashes decreased from 8 in September 2024 to 6 in September 2025. The hit-and-run rate also decreased, falling from 14.5% to 12.5% year-over-year, indicating a downward trend in such incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

12

Motorists Injured

Prior: 21-42.9%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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 Thursday in September 2024 (14 crashes) to Thursday again in September 2025 (12 crashes), remaining the busiest day. The peak hour for crashes remained consistent at 5 PM, with 6 crashes in September 2024 and 7 crashes in September 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both September 2024 and September 2025. Total injuries decreased from 22 to 13, a 40.9% reduction. The proportion of crashes resulting in 'No Injury' increased from 63.6% in the prior year to 77.1% in the current period, while 'Minor Injury' crashes decreased from 18.2% to 14.6%.

Outcome by Severity (Crash Events)

Minor Injury7minor injury crashes14.6%
-30.0%prior 10
Possible Injury4possible injury crashes8.3%
-50.0%prior 8
No Injury37no injury crashes77.1%
5.7%prior 35

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'No improper driving', increased in count from 8 in September 2024 to 13 in September 2025, a 62.5% increase. 'Failed to yield right of way' decreased from 13 crashes to 6 crashes, a 53.8% reduction. 'Followed too closely' increased from 4 crashes to 8 crashes, a 100% increase.

Officer-Reported Primary Contributing Cause

No improper driving13 (27.1%)62.5%prior 8
Followed too closely8 (16.7%)
Failed to yield right of way6 (12.5%)-53.8%prior 13
Inattention6 (12.5%)
Disregarded traffic signs, signals, road markings3 (6.3%)
Failure to keep in proper lane or running off road3 (6.3%)
Made an improper turn2 (4.2%)
Exceeded authorized speed limit1 (2.1%)
Operating defective equipment1 (2.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions remained the most common, accounting for 29 crashes in September 2024 and 31 crashes in September 2025. The proportion of crashes in 'Daylight' conditions decreased slightly from 72.7% (40 crashes) to 72.9% (35 crashes) year-over-year. Crashes on 'Dry' road surfaces decreased from 45 to 40, while those on 'Wet' surfaces decreased from 9 to 7.

Weather

Clear31 (64.6%)
6.9%prior 29
Clear/Clear10 (20.8%)
66.7%prior 6
Rain3 (6.3%)
Cloudy/Rain2 (4.2%)
Clear/Cloudy1 (2.1%)
Rain/Rain1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash

Lighting

Daylight35 (72.9%)
-12.5%prior 40
Dark - roadway not lighted7 (14.6%)
40.0%prior 5
Dark - lighted roadway3 (6.3%)
-66.7%prior 9
Dusk2 (4.2%)
Dawn1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field

Road Surface

Dry40 (83.3%)
-11.1%prior 45
Wet7 (14.6%)
-22.2%prior 9
Sand, mud, dirt, oil, gravel1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 108 in September 2024 to 90 in September 2025. HONDA, which was the top make in September 2024 with 20 vehicles, fell to second place in September 2025 with 11 vehicles, while TOYOTA became the top make, increasing from 11 to 16 vehicles. The age group '21-25' saw a decrease in persons involved, from 22 to 12.

Top Vehicle Makes (90 vehicles)

1
TOYOTA16 (17.8%)
45.5%prior 11
2
HONDA11 (12.2%)
-45.0%prior 20
3
FORD8 (8.9%)
-11.1%prior 9
4
CHEVROLET7 (7.8%)
-30.0%prior 10
5
SUBARU6 (6.7%)
6
HYUNDAI5 (5.6%)
7
JEEP4 (4.4%)
8
ACURA2 (2.2%)
9
DODGE2 (2.2%)
10
NISSAN2 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records

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

Sex Distribution (101 persons with recorded sex)

Male60 (59.4%)
-14.3%prior 70
Female41 (40.6%)
-14.6%prior 48

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in the 30 mph speed limit zone decreased from 24 in September 2024 to 12 in September 2025. Conversely, crashes in the 35 mph speed limit zone increased from 8 to 11. Both periods reported 0 fatal crashes across all speed zones.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-09-01 through 2025-09-30 (30 days)
  • Geographic scope: BILLERICA, MA
  • Total crash records analyzed: 48
  • Total persons involved: 115
  • Total vehicles involved: 90

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). "BILLERICA, MA Crash Intelligence Report: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/billerica/september-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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Billerica, MA Crash Report — September 2025 | ThatCarHitMe.com