Monthly Traffic Safety Analysis

111 CRASHES IN
WALTHAM, MA
JANUARY 2025

All metrics benchmarked againstJanuary 2024

Total crashes decreased from 124 in January 2024 to 111 in January 2025, a reduction of 10.48%. The most notable shift was the significant increase in crashes where 'Failed to yield right of way' was a contributing factor, rising from 15 crashes to 28 crashes.

111

-10.5%was 124

Total Crash Events

0

Persons Killed

36

20.0%was 30

Persons Injured

14

-6.7%was 15

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend for total crashes in WALTHAM, MA for January shows a decrease, falling by 13 crashes from 124 in January 2024 to 111 in January 2025. This represents a 10.48% reduction in total crashes year-over-year.

14

Hit-and-Run Crashes — January 2025

-6.7% vs prior (15)

The number of hit-and-run crashes decreased slightly from 15 in January 2024 to 14 in January 2025. However, the hit-and-run rate increased by 0.5 percentage points, from 12.1% to 12.6%, indicating a slight upward trend in the proportion of total crashes that are hit-and-runs.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 10.0%

35

Motorists Injured

Prior: 2920.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year. In January 2024, the peak day for crashes was Tuesday with 23 incidents, and the peak hour was 5 p.m. with 17 crashes; however, in January 2025, the peak day moved to Friday with 22 crashes, and the peak hour shifted to 8 a.m. with 14 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both January 2024 and January 2025. Total injuries increased by 6, from 30 in January 2024 to 36 in January 2025, representing a 20% increase. The proportion of minor injury crashes increased from 10.5% (13 crashes) to 14.4% (16 crashes), while possible injury crashes decreased from 7.3% (9 crashes) to 5.4% (6 crashes).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.9%
0.0%prior 1
Minor Injury16minor injury crashes14.4%
23.1%prior 13
Possible Injury6possible injury crashes5.4%
-33.3%prior 9
No Injury84no injury crashes75.7%
-8.7%prior 92

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Failed to yield right of way" increased significantly by 13, from 15 in January 2024 to 28 in January 2025, an 86.7% increase in count. This factor became the top contributing factor in January 2025 with a 25.2% share of crashes, up from a 12.1% share. Conversely, crashes with "No improper driving" decreased by 10, from 30 to 20, a 33.3% reduction in count.

Officer-Reported Primary Contributing Cause

Failed to yield right of way28 (25.2%)86.7%prior 15
No improper driving20 (18%)-33.3%prior 30
Inattention18 (16.2%)5.9%prior 17
Disregarded traffic signs, signals, road markings7 (6.3%)
Other improper action7 (6.3%)-22.2%prior 9
Followed too closely5 (4.5%)-28.6%prior 7
Failure to keep in proper lane or running off road4 (3.6%)-50.0%prior 8
Driving too fast for conditions4 (3.6%)-33.3%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (3.6%)
Visibility obstructed2 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" weather conditions increased by 18, from 52 in January 2024 to 70 in January 2025, while crashes in "Cloudy" conditions decreased by 13, from 31 to 18. Crashes on "Wet" road surfaces decreased by 14, from 31 to 17, and crashes on "Snow" surfaces decreased by 8, from 13 to 5. There was an increase of 11 crashes occurring in "Daylight" conditions, from 71 to 82, and a decrease of 16 crashes in "Dark - lighted roadway" conditions, from 36 to 20.

Weather

Clear70 (63.6%)
34.6%prior 52
Cloudy18 (16.4%)
-41.9%prior 31
Clear/Clear6 (5.5%)
Snow6 (5.5%)
0.0%prior 6
Rain5 (4.5%)
-44.4%prior 9
Sleet, hail (freezing rain or drizzle)1 (0.9%)
Clear/Cloudy1 (0.9%)
Clear/Other1 (0.9%)
Cloudy/Snow1 (0.9%)
Rain/Cloudy1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash

Lighting

Daylight82 (73.9%)
15.5%prior 71
Dark - lighted roadway20 (18.0%)
-44.4%prior 36
Dark - roadway not lighted4 (3.6%)
-42.9%prior 7
Dusk4 (3.6%)
Dawn1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field

Road Surface

Dry81 (73.0%)
8.0%prior 75
Wet17 (15.3%)
-45.2%prior 31
Ice5 (4.5%)
Snow5 (4.5%)
-61.5%prior 13
Slush2 (1.8%)
Other1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 254 in January 2024 to 218 in January 2025. The number of persons in the 0-15 age group involved in crashes saw a substantial increase from 5 to 54. Toyota remained the top vehicle make involved, though its count decreased from 52 to 49, and Honda also saw a decrease from 42 to 31.

Top Vehicle Makes (218 vehicles)

1
TOYOTA49 (22.5%)
-5.8%prior 52
2
HONDA31 (14.2%)
-26.2%prior 42
3
FORD21 (9.6%)
-4.5%prior 22
4
SUBARU13 (6%)
0.0%prior 13
5
JEEP13 (6%)
0.0%prior 13
6
NISSAN9 (4.1%)
-10.0%prior 10
7
CHEVROLET9 (4.1%)
-25.0%prior 12
8
LEXUS7 (3.2%)
40.0%prior 5
9
VOLKSWAGEN5 (2.3%)
-16.7%prior 6
10
GMC5 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records

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

Sex Distribution (271 persons with recorded sex)

Male164 (60.5%)
9.3%prior 150
Female107 (39.5%)
4.9%prior 102

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones saw a significant increase, rising by 44 from 16 in January 2024 to 60 in January 2025. Conversely, crashes in 30 mph speed zones decreased by 46, from 67 to 21. No fatal crashes were recorded in any speed limit zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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: 2025-01-01 through 2025-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-01-31 (31 days)
  • Geographic scope: WALTHAM, MA
  • Total crash records analyzed: 111
  • Total persons involved: 300
  • Total vehicles involved: 218

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). "WALTHAM, MA Crash Intelligence Report: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/waltham/january-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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Waltham, MA Crash Report — January 2025 | ThatCarHitMe.com