Monthly Traffic Safety Analysis

26 CRASHES IN
MEDFIELD, MA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

In MEDFIELD, MA, total crashes increased by 18.18% year-over-year, rising from 22 crashes in January 2025 to 26 crashes in January 2026. The number of total injuries remained stable at 6 persons in both periods, and there were no fatalities reported in either month. A notable shift was the emergence of hit-and-run crashes, with 1 reported in January 2026 compared to none in January 2025.

26

18.2%was 22

Total Crash Events

0

Persons Killed

6

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

Trend Summary

The overall trend indicates an increase in crash incidents, with total crashes rising from 22 in January 2025 to 26 in January 2026, representing an 18.18% increase. Despite this rise in crash count, the total number of injured persons remained consistent at 6 for both periods, and no fatal crashes occurred in either year.

1

Hit-and-Run Crashes — January 2026

3.8% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 60.0%

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 peak day for crashes remained Friday in both periods, although the count decreased from 8 crashes in January 2025 to 7 crashes in January 2026. The peak crash hour shifted from 8 PM (3 crashes) in January 2025 to 5 PM (4 crashes) in January 2026. Crashes occurring at 12 AM increased from 0 in January 2025 to 2 in January 2026.

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. The number of crashes resulting in serious injury increased from 0 in January 2025 to 1 in January 2026. Crashes with possible injuries decreased from 3 in January 2025 to 1 in January 2026, while crashes with no injuries increased from 18 to 23.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.8%
Minor Injury1minor injury crashes3.8%
0.0%prior 1
Possible Injury1possible injury crashes3.8%
-66.7%prior 3
No Injury23no injury crashes88.5%
27.8%prior 18

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 count of 'No improper driving' as a contributing factor increased from 11 crashes in January 2025 to 13 crashes in January 2026, maintaining a 50% share of all factors in both periods. 'Failed to yield right of way' decreased significantly from 5 crashes to 1 crash, while 'Disregarded traffic signs, signals, road markings' also saw a decrease from 2 crashes to 1 crash. 'Inattention' and 'Made an improper turn' emerged as new factors in January 2026, each contributing to 2 crashes.

Officer-Reported Primary Contributing Cause

No improper driving13 (50%)18.2%prior 11
Inattention2 (7.7%)
Made an improper turn2 (7.7%)
Glare1 (3.8%)
Wrong side or wrong way1 (3.8%)
Disregarded traffic signs, signals, road markings1 (3.8%)
Distracted1 (3.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.8%)
Failed to yield right of way1 (3.8%)-80.0%prior 5
Followed too closely1 (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 decreased from 20 in January 2025 to 15 in January 2026, while 'Cloudy' conditions saw an increase from 0 to 6 crashes. On road surfaces, crashes on 'Dry' conditions decreased from 17 to 13, and crashes on 'Wet' conditions increased substantially from 1 to 8. Crashes in 'Daylight' increased from 13 to 16, while crashes in 'Dark - lighted roadway' decreased from 7 to 6.

Weather

Clear15 (57.7%)
-25.0%prior 20
Cloudy6 (23.1%)
Snow2 (7.7%)
Clear/Cloudy1 (3.8%)
Cloudy/Snow1 (3.8%)
Rain1 (3.8%)

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

Lighting

Daylight16 (61.5%)
23.1%prior 13
Dark - lighted roadway6 (23.1%)
-14.3%prior 7
Dark - roadway not lighted3 (11.5%)
Dark - unknown roadway lighting1 (3.8%)

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

Road Surface

Dry13 (50.0%)
-23.5%prior 17
Wet8 (30.8%)
Snow3 (11.5%)
Ice1 (3.8%)
Other1 (3.8%)

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 (47 vehicles)

1
CHEVROLET7 (14.9%)
2
TOYOTA7 (14.9%)
40.0%prior 5
3
NISSAN4 (8.5%)
4
FORD4 (8.5%)
5
HONDA4 (8.5%)
-33.3%prior 6
6
HYUNDAI3 (6.4%)
7
JEEP3 (6.4%)
-40.0%prior 5
8
AUDI2 (4.3%)
9
MAZDA2 (4.3%)
10
MERCEDES-BENZ2 (4.3%)

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

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

Sex Distribution (50 persons with recorded sex)

Male31 (62.0%)
19.2%prior 26
Female19 (38.0%)
-20.8%prior 24

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

The 30 mph speed zone experienced the largest increase in crashes, rising from 8 in January 2025 to 13 in January 2026. Conversely, the 40 mph speed zone saw a decrease in crashes from 6 to 4. A new speed zone, 10 mph, appeared in January 2026 with 2 crashes, while the 50 mph zone, which had 1 crash in January 2025, was not present in January 2026 data. No fatal crashes were reported in any speed zone for 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: MEDFIELD, MA
  • Total crash records analyzed: 26
  • Total persons involved: 53
  • Total vehicles involved: 47

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). "MEDFIELD, 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/medfield/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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Medfield, MA Crash Report — January 2026 | ThatCarHitMe.com