Monthly Traffic Safety Analysis

108 CRASHES IN
WALTHAM, MA
SEPTEMBER 2023

All metrics benchmarked againstSeptember 2022

In September 2023, Waltham recorded 108 total crashes, a notable decrease from the 157 crashes reported in September 2022. This represents a 31.2% reduction in total crashes year-over-year. The most significant shift was the substantial decline in overall crash incidents.

108

-31.2%was 157

Total Crash Events

0

Persons Killed

20

-44.4%was 36

Persons Injured

21

-44.7%was 38

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Waltham are trending downward year-over-year, with a significant decrease observed. Total crashes fell from 157 in September 2022 to 108 in September 2023, marking a 31.2% reduction.

21

Hit-and-Run Crashes — September 2023

-44.7% vs prior (38)

The number of hit-and-run crashes decreased from 38 in September 2022 to 21 in September 2023. The hit-and-run crash rate also saw a decrease, falling from 24.2% of all crashes in the prior period to 19.4% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 20.0%

1

Cyclists Injured

Prior: 2-50.0%

17

Motorists Injured

Prior: 32-46.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Tuesday with 30 crashes in September 2022 to Wednesday with 20 crashes in September 2023. Similarly, the peak crash hour moved from 4 PM with 16 crashes in the prior period to 5 PM with 12 crashes in the current period. Crashes on Saturdays saw the largest decrease, dropping from 23 to 9.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either September 2022 or September 2023. The total number of injuries decreased from 36 in the prior period to 20 in the current period, representing a 44.4% reduction. The proportion of serious injury crashes (severity 'A') increased from 7.6% (12 crashes) in the prior year to 10.2% (11 crashes) in the current year, despite a slight decrease in the count of serious injury crashes.

Outcome by Severity (Crash Events)

Serious Injury11serious injury crashes10.2%
-8.3%prior 12
Minor Injury2minor injury crashes1.9%
-33.3%prior 3
Possible Injury3possible injury crashes2.8%
-76.9%prior 13
No Injury83no injury crashes76.9%
-25.2%prior 111

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Most severe injury per crash record

Top Contributing Factors

The count of crashes where 'No improper driving' was a factor decreased from 28 in the prior period to 23 in the current period. 'Inattention' as a contributing factor saw a decrease from 21 crashes to 11 crashes. Conversely, 'Failure to keep in proper lane or running off road' increased in count from 5 crashes to 9 crashes, and 'Other improper action' increased from 4 crashes to 6 crashes.

Officer-Reported Primary Contributing Cause

No improper driving23 (21.3%)-17.9%prior 28
Inattention11 (10.2%)-47.6%prior 21
Failed to yield right of way11 (10.2%)-35.3%prior 17
Followed too closely10 (9.3%)-28.6%prior 14
Failure to keep in proper lane or running off road9 (8.3%)80.0%prior 5
Disregarded traffic signs, signals, road markings6 (5.6%)-45.5%prior 11
Other improper action6 (5.6%)
Distracted4 (3.7%)
Over-correcting/over-steering2 (1.9%)
Visibility obstructed2 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 108 in the prior period to 64 in the current period, while crashes in 'Rain' conditions increased from 9 to 22. The proportion of crashes on 'Wet' road surfaces significantly increased from 12.7% (20 crashes) to 29.6% (32 crashes) year-over-year. Crashes during 'Daylight' decreased from 114 to 71, and crashes in 'Dark - lighted roadway' conditions decreased from 32 to 19.

Weather

Clear64 (60.4%)
-40.7%prior 108
Rain22 (20.8%)
144.4%prior 9
Cloudy11 (10.4%)
-60.7%prior 28
Clear/Clear4 (3.8%)
Cloudy/Rain3 (2.8%)
Rain/Cloudy1 (0.9%)
Rain/Rain1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Weather condition at time of crash

Lighting

Daylight71 (68.9%)
-37.7%prior 114
Dark - lighted roadway19 (18.4%)
-40.6%prior 32
Dusk6 (5.8%)
Dawn3 (2.9%)
Dark - unknown roadway lighting2 (1.9%)
Dark - roadway not lighted2 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Lighting condition field

Road Surface

Dry74 (69.8%)
-45.2%prior 135
Wet32 (30.2%)
60.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes decreased from 391 in September 2022 to 273 in September 2023. All age groups saw a reduction in the number of persons involved, with the 35-44 age group experiencing the largest decrease from 56 to 28 persons. Toyota remained the most frequently involved vehicle make, though its count decreased from 48 to 36.

Top Vehicle Makes (211 vehicles)

1
TOYOTA36 (17.1%)
-25.0%prior 48
2
HONDA23 (10.9%)
-36.1%prior 36
3
FORD22 (10.4%)
-12.0%prior 25
4
NISSAN15 (7.1%)
36.4%prior 11
5
CHEVROLET12 (5.7%)
0.0%prior 12
6
MAZDA8 (3.8%)
7
VOLKSWAGEN6 (2.8%)
8
JEEP6 (2.8%)
0.0%prior 6
9
LEXUS5 (2.4%)
-28.6%prior 7
10
BMW5 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Vehicle unit records

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

Sex Distribution (201 persons with recorded sex)

Male118 (58.7%)
-39.8%prior 196
Female83 (41.3%)
-34.1%prior 126

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased significantly from 107 in September 2022 to 63 in September 2023. Conversely, crashes in 25 mph zones saw a notable increase from 3 in the prior period to 17 in the current period. There were no fatalities reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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: 2023-09-01 through 2023-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-09-01 through 2023-09-30 (30 days)
  • Geographic scope: WALTHAM, MA
  • Total crash records analyzed: 108
  • Total persons involved: 273
  • Total vehicles involved: 211

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: September 2023." Published June 21, 2026. Reporting period: 2023-09-01 to 2023-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/waltham/september-2023-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 — September 2023 | ThatCarHitMe.com