Monthly Traffic Safety Analysis

17 CRASHES IN
MEDFIELD, MA
JANUARY 2024

All metrics benchmarked againstJanuary 2023

MEDFIELD experienced a significant increase in total crashes in January 2024, with 17 crashes compared to 11 in January 2023, marking a 54.5% rise. Despite this increase in crash volume, the number of reported injuries decreased by 66.7%, from 3 injuries in January 2023 to 1 injury in January 2024.

17

54.5%was 11

Total Crash Events

0

Persons Killed

1

-66.7%was 3

Persons Injured

0

-100.0%was 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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for January in MEDFIELD shows a notable increase in crash incidents year-over-year. Total crashes rose from 11 in January 2023 to 17 in January 2024, representing a 54.5% increase.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 3-66.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

In January 2024, Wednesday remained the peak day for crashes, with 5 incidents, up from 3 on Wednesdays in January 2023. The peak crash hour shifted from 12p with 2 crashes in January 2023 to 8a with 3 crashes in January 2024, indicating a change in the most common time for incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes increased, the number of injury crashes decreased from 3 in January 2023 to 1 in January 2024. This resulted in a lower proportion of injury crashes, falling from 27.3% to 5.9% of all crashes. There were no fatal crashes reported in either January 2023 or January 2024.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes5.9%
No Injury15no injury crashes88.2%
87.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving,' increased from 3 crashes in January 2023 to 6 crashes in January 2024. Crashes attributed to 'Inattention' decreased from 3 to 1, while 'Followed too closely' increased from 1 to 2 crashes year-over-year. 'Driving too fast for conditions' was a factor in 1 crash in January 2024, not present in January 2023.

Officer-Reported Primary Contributing Cause

No improper driving6 (35.3%)
Followed too closely2 (11.8%)
Driving too fast for conditions1 (5.9%)
Other improper action1 (5.9%)
Visibility obstructed1 (5.9%)
Inattention1 (5.9%)
Failed to yield right of way1 (5.9%)
Failure to keep in proper lane or running off road1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in clear weather increased from 6 in January 2023 to 10 in January 2024, while crashes in rainy conditions decreased from 3 to 1. There was a notable increase in crashes on snowy road surfaces, rising from 0 in January 2023 to 5 in January 2024. Crashes occurring in dark-lighted roadway conditions increased from 1 to 5 year-over-year.

Weather

Clear10 (58.8%)
66.7%prior 6
Cloudy2 (11.8%)
Snow2 (11.8%)
Blowing sand, snow/Snow1 (5.9%)
Cloudy/Rain1 (5.9%)
Rain1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Weather condition at time of crash

Lighting

Daylight11 (64.7%)
57.1%prior 7
Dark - lighted roadway5 (29.4%)
Dusk1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Lighting condition field

Road Surface

Dry9 (52.9%)
80.0%prior 5
Snow5 (29.4%)
Wet3 (17.6%)
-50.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (27 vehicles)

1
HONDA4 (14.8%)
-20.0%prior 5
2
CHEVROLET4 (14.8%)
3
TOYOTA3 (11.1%)
-40.0%prior 5
4
NISSAN3 (11.1%)
5
JEEP3 (11.1%)
6
VOLVO2 (7.4%)
7
FORD2 (7.4%)
8
SUBARU2 (7.4%)
9
MERCEDES-BENZ1 (3.7%)
10
HYUNDAI1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Vehicle unit records

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

Sex Distribution (28 persons with recorded sex)

Male18 (64.3%)
38.5%prior 13
Female10 (35.7%)
11.1%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Person-level records linked to crash events

Speed Limit Zones

The majority of crashes in January 2024 occurred in 30 mph zones, increasing from 4 crashes in January 2023 to 9 crashes. Crashes in 45 mph zones decreased from 2 to 1. New crash occurrences were observed in 10 mph and 15 mph zones in January 2024, with 1 crash in each. No fatal crashes were reported across any speed limit zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · 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: 2024-01-01 through 2024-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-01-31 (31 days)
  • Geographic scope: MEDFIELD, MA
  • Total crash records analyzed: 17
  • Total persons involved: 29
  • Total vehicles involved: 27

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 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/medfield/january-2024-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 2024 | ThatCarHitMe.com