Monthly Traffic Safety Analysis

25 CRASHES IN
AVON, MA
MARCH 2026

All metrics benchmarked againstMarch 2025

In March 2026, AVON experienced 25 crashes, an increase from 24 crashes in March 2025, representing a 4.17% rise year-over-year. The most notable change was a substantial increase in total injuries, which rose by 157.14% from 7 in March 2025 to 18 in March 2026.

25

4.2%was 24

Total Crash Events

0

Persons Killed

18

157.1%was 7

Persons Injured

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 · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in AVON remained relatively stable year-over-year, increasing by 4.17% from 24 crashes in March 2025 to 25 crashes in March 2026. However, total injuries saw a significant upward trend, more than doubling from 7 to 18, a 157.14% increase during the same period.

1

Hit-and-Run Crashes — March 2026

0.0% vs prior (1)

The number of hit-and-run crashes remained consistent at 1 in both March 2025 and March 2026. The hit-and-run rate slightly decreased from 4.2% of total crashes in the prior period to 4% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

18

Motorists Injured

Prior: 7157.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · 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 March 2025 (9 crashes) and March 2026 (8 crashes), and the peak hour also remained 3 PM, though crash counts at this hour decreased from 4 to 3. Notably, crashes on Fridays increased from 1 in March 2025 to 5 in March 2026, while Saturday crashes decreased from 3 to 0 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both March 2025 and March 2026. However, the overall proportion of crashes resulting in some form of injury increased from 25% (6 out of 24 crashes) in March 2025 to 36% (9 out of 25 crashes) in March 2026. While serious injuries decreased from 1 to 0, possible injuries saw a notable increase from 1 crash (4.2% share) to 7 crashes (28% share) year-over-year.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes8%
-50.0%prior 4
Possible Injury7possible injury crashes28%
600.0%prior 1
No Injury16no injury crashes64%
0.0%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record

Top Contributing Factors

The count of crashes where 'No improper driving' was cited decreased from 10 in March 2025 to 9 in March 2026. 'Followed too closely' emerged as a significant factor in March 2026 with 3 crashes, up from 0 in the prior period. Conversely, factors like 'Over-correcting/over-steering' and 'Visibility obstructed,' each contributing to 2 crashes in March 2025, were not present in March 2026.

Officer-Reported Primary Contributing Cause

No improper driving9 (36%)-10.0%prior 10
Followed too closely3 (12%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (8%)
Made an improper turn2 (8%)
Failed to yield right of way2 (8%)
Inattention2 (8%)
Driving too fast for conditions1 (4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on 'Dry' road surfaces increased from 18 in March 2025 to 22 in March 2026, while crashes on 'Wet' surfaces decreased from 6 to 3. The number of crashes during 'Daylight' conditions increased from 18 to 20 year-over-year. Crashes during 'Rain' conditions remained relatively low, with 2 crashes in March 2026 compared to 3 rain-related crashes in March 2025.

Weather

Clear14 (56.0%)
7.7%prior 13
Clear/Unknown4 (16.0%)
Clear/Clear2 (8.0%)
Clear/Other2 (8.0%)
Rain2 (8.0%)
Cloudy1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash

Lighting

Daylight20 (80.0%)
11.1%prior 18
Dark - lighted roadway3 (12.0%)
Dark - roadway not lighted1 (4.0%)
Dawn1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field

Road Surface

Dry22 (88.0%)
22.2%prior 18
Wet3 (12.0%)
-50.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (49 vehicles)

1
TOYOTA11 (22.4%)
57.1%prior 7
2
NISSAN7 (14.3%)
3
FORD6 (12.2%)
-14.3%prior 7
4
CHEVROLET4 (8.2%)
5
HYUNDAI3 (6.1%)
6
HONDA3 (6.1%)
-50.0%prior 6
7
JEEP2 (4.1%)
8
RAM1 (2%)
9
SMRT1 (2%)
10
SUBARU1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records

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

Sex Distribution (61 persons with recorded sex)

Male40 (65.6%)
37.9%prior 29
Female21 (34.4%)
31.3%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events

Speed Limit Zones

All speed limit zones reported zero fatal crashes in both March 2025 and March 2026. Crashes in the 40 mph speed limit zone saw a notable increase, rising from 3 in March 2025 to 7 in March 2026. Conversely, crashes in the 65 mph zone decreased from 4 to 3, and crashes in the 25 mph zone decreased from 2 to 1 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · 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: 2026-03-01 through 2026-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2026-03-01 through 2026-03-31 (31 days)
  • Geographic scope: AVON, MA
  • Total crash records analyzed: 25
  • Total persons involved: 67
  • Total vehicles involved: 49

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). "AVON, MA Crash Intelligence Report: March 2026." Published June 21, 2026. Reporting period: 2026-03-01 to 2026-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/avon/march-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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Avon, MA Crash Report — March 2026 | ThatCarHitMe.com