Monthly Traffic Safety Analysis

29 CRASHES IN
ARLINGTON, MA
JULY 2025

All metrics benchmarked againstJuly 2024

Total crashes in Arlington increased from 21 in July 2024 to 29 in July 2025, representing a 38.1% rise. A notable shift includes the emergence of 3 DUI-related crashes in July 2025, compared to none in the prior year. Additionally, crashes resulting in minor injuries doubled from 2 to 4 year-over-year. Overall, the data indicates an increase in crash incidents and injuries.

29

38.1%was 21

Total Crash Events

0

Persons Killed

8

33.3%was 6

Persons Injured

4

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Arlington increased year-over-year, with total crashes rising by 38.1% from 21 in July 2024 to 29 in July 2025. This upward trend is also reflected in total injuries, which increased from 6 to 8 during the same period. Fatalities remained at zero in both periods.

4

Hit-and-Run Crashes — July 2025

0.0% vs prior (4)

The number of hit-and-run crashes remained constant at 4 incidents in both July 2024 and July 2025. However, due to an overall increase in total crashes, the hit-and-run rate decreased from 19% in July 2024 to 13.8% in July 2025. This indicates a relative decrease in hit-and-run incidents compared to the overall crash volume.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 10.0%

6

Motorists Injured

Prior: 520.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with Sunday becoming the peak day for crashes in July 2025 with 6 incidents, compared to Wednesday being the peak day in July 2024, also with 6 incidents. The peak hour for crashes also shifted from 4 p.m. (3 crashes) in July 2024 to 5 p.m. (4 crashes) in July 2025. This indicates a change in when the highest number of crashes occurred.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While both periods reported zero fatalities, the total number of injuries increased from 6 in July 2024 to 8 in July 2025. Crashes resulting in minor injuries (severity B) doubled from 2 to 4, and possible injury crashes (severity C) increased from 2 to 3. The prior period also recorded 1 serious injury (severity A) crash, which was not present in the current period.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes13.8%
100.0%prior 2
Possible Injury3possible injury crashes10.3%
50.0%prior 2
No Injury19no injury crashes65.5%
26.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, "No improper driving," saw a slight decrease from 10 crashes in July 2024 to 9 crashes in July 2025. "Failed to yield right of way" remained constant at 3 crashes in both periods. Notably, "Inattention" emerged as a significant factor in July 2025 with 5 crashes, having not been reported in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving9 (31%)-10.0%prior 10
Inattention5 (17.2%)
Failed to yield right of way3 (10.3%)
Followed too closely2 (6.9%)
Other improper action2 (6.9%)
Disregarded traffic signs, signals, road markings1 (3.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.4%)
Fatigued/asleep1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions (Clear or Clear/Clear) increased from 15 in July 2024 to 24 in July 2025. Conversely, crashes in cloudy conditions decreased from 4 to 2. The number of crashes on dry road surfaces increased from 18 to 23, while those on wet surfaces decreased from 3 to 2.

Weather

Clear20 (71.4%)
185.7%prior 7
Clear/Clear4 (14.3%)
-50.0%prior 8
Cloudy2 (7.1%)
Unknown/Unknown2 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Weather condition at time of crash

Lighting

Daylight23 (88.5%)
21.1%prior 19
Dark - lighted roadway3 (11.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Lighting condition field

Road Surface

Dry23 (88.5%)
27.8%prior 18
Wet2 (7.7%)
Other1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (48 vehicles)

1
TOYOTA8 (16.7%)
-11.1%prior 9
2
SUBARU8 (16.7%)
3
HONDA6 (12.5%)
20.0%prior 5
4
HYUNDAI5 (10.4%)
5
VOLVO3 (6.3%)
6
CHEVROLET3 (6.3%)
7
NISSAN2 (4.2%)
8
DODGE2 (4.2%)
9
BUIC1 (2.1%)
10
KIA1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Vehicle unit records

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

Sex Distribution (52 persons with recorded sex)

Male33 (63.5%)
43.5%prior 23
Female19 (36.5%)
26.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Person-level records linked to crash events

Speed Limit Zones

The 25 mph speed zone continued to account for the majority of crashes, increasing from 16 incidents in July 2024 to 25 in July 2025. Crashes in the 30 mph zone (3 incidents) and 55 mph zone (1 incident) present in the prior period were absent in the current period. Additionally, 1 crash occurred in a 5 mph zone in July 2025, a category not present in the prior year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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: 2025-07-01 through 2025-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-07-01 through 2025-07-31 (31 days)
  • Geographic scope: ARLINGTON, MA
  • Total crash records analyzed: 29
  • Total persons involved: 62
  • Total vehicles involved: 48

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). "ARLINGTON, MA Crash Intelligence Report: July 2025." Published June 21, 2026. Reporting period: 2025-07-01 to 2025-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/arlington/july-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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Arlington, MA Crash Report — July 2025 | ThatCarHitMe.com