Yearly Traffic Safety Analysis

1,456 CRASHES IN
WALTHAM, MA
2023

All metrics benchmarked against2022

In Waltham, total traffic crashes decreased by 9.1% from 1,602 in the prior year (2022) to 1,456 in the current year (2023). While total fatalities remained stable at three persons, total injuries fell by 17.5% from 360 to 297. The most significant year-over-year shift was a 36.3% decrease in the count of crashes attributed to inattention, which dropped from 295 to 188 incidents.

1,456

-9.1%was 1,602

Total Crash Events

3

Persons Killed

297

-17.5%was 360

Persons Injured

277

-14.8%was 325

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 112 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Waltham show improvement year-over-year. Total crashes declined by 9.1% from 1,602 to 1,456. This was accompanied by a 17.5% reduction in total injuries (from 360 to 297), while the number of fatalities held constant at three.

277

Hit-and-Run Crashes — 2023

-14.8% vs prior (325)

Hit-and-run incidents decreased year-over-year. The total count of hit-and-run crashes fell by 14.8%, from 325 in the prior period to 277 in the current period. The hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also trended downward, declining from 20.3% to 19.0%.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 1100.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 2-50.0%

0

Other Killed

Prior: 00.0%

32

Pedestrians Injured

Prior: 2718.5%

13

Cyclists Injured

Prior: 22-40.9%

251

Motorists Injured

Prior: 311-19.3%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained broadly similar between the two periods. Friday was the peak day for crashes in both the current year (244 crashes) and the prior year (267 crashes). However, the peak hour for crashes shifted later in the day, from 3 p.m. in the prior year (167 crashes) to 5 p.m. in the current year (150 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity showed a mixed but generally stable profile year-over-year. The number of fatal crashes decreased from 3 to 2, with the fatal crash rate declining from 0.19% to 0.14%. While the absolute count of serious injury crashes increased slightly from 138 to 143, their share of all crashes rose from 8.6% to 9.8% as total crashes decreased. The share of no-injury crashes also increased, from 72.5% to 76.1% of all incidents.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.1%
-33.3%prior 3
Serious Injury143serious injury crashes9.8%
3.6%prior 138
Minor Injury31minor injury crashes2.1%
0.0%prior 31
Possible Injury60possible injury crashes4.1%
-43.9%prior 107
No Injury1,108no injury crashes76.1%
-4.6%prior 1,162

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The ranking of top contributing factors shifted between periods. In the prior year, 'Inattention' was the leading factor with 295 crashes, but its count dropped by 36.3% to 188 crashes in the current year, making it the second-leading factor. 'No improper driving' became the most cited factor in the current year, with its count increasing by 12.0% from 284 to 318. Crashes attributed to 'Failed to yield right of way' also decreased in count by 11.4%, from 166 to 147.

Officer-Reported Primary Contributing Cause

No improper driving318 (21.8%)12.0%prior 284
Inattention188 (12.9%)-36.3%prior 295
Failed to yield right of way147 (10.1%)-11.4%prior 166
Followed too closely126 (8.7%)-3.8%prior 131
Failure to keep in proper lane or running off road69 (4.7%)13.1%prior 61
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner58 (4%)-30.1%prior 83
Disregarded traffic signs, signals, road markings53 (3.6%)12.8%prior 47
Other improper action44 (3%)57.1%prior 28
Over-correcting/over-steering37 (2.5%)131.3%prior 16
Made an improper turn35 (2.4%)133.3%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Year-over-year data indicates a slight shift in crash conditions. The proportion of crashes occurring on wet road surfaces increased from 14.9% to 17.9%, while the share on dry surfaces decreased from 80.4% to 78.0%. Similarly, crashes in daylight conditions accounted for a smaller share of the total in the current year (63.7%) compared to the prior year (69.4%), while crashes on dark, lighted roadways saw their share increase from 21.7% to 24.9%.

Weather

Clear920 (64.2%)
-19.1%prior 1,137
Cloudy203 (14.2%)
-4.7%prior 213
Rain130 (9.1%)
30.0%prior 100
Clear/Clear58 (4.1%)
114.8%prior 27
Snow27 (1.9%)
22.7%prior 22
Cloudy/Rain23 (1.6%)
27.8%prior 18
Rain/Cloudy22 (1.5%)
46.7%prior 15
Sleet, hail (freezing rain or drizzle)11 (0.8%)
37.5%prior 8
Clear/Cloudy6 (0.4%)
Cloudy/Snow4 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight927 (64.6%)
-16.6%prior 1,112
Dark - lighted roadway363 (25.3%)
4.6%prior 347
Dusk61 (4.3%)
56.4%prior 39
Dark - roadway not lighted55 (3.8%)
71.9%prior 32
Dawn16 (1.1%)
6.7%prior 15
Dark - unknown roadway lighting11 (0.8%)
22.2%prior 9
Other1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry1,136 (79.2%)
-11.8%prior 1,288
Wet260 (18.1%)
9.2%prior 238
Snow26 (1.8%)
-18.8%prior 32
Ice9 (0.6%)
-60.9%prior 23
Slush2 (0.1%)
Water (standing, moving)1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

Vehicle and person demographics involved in crashes remained largely consistent year-over-year. Toyota, Honda, and Ford were the top three vehicle makes involved in crashes in both periods, with their rank order unchanged. The age distribution of persons involved in crashes also showed no significant shifts, with all age groups seeing a decrease in involvement that aligns with the overall reduction in total persons involved in crashes.

Top Vehicle Makes (2,803 vehicles)

1
TOYOTA515 (18.4%)
12.7%prior 457
2
HONDA357 (12.7%)
9.5%prior 326
3
FORD268 (9.6%)
5.9%prior 253
4
CHEVROLET145 (5.2%)
9.0%prior 133
5
NISSAN143 (5.1%)
38.8%prior 103
6
JEEP118 (4.2%)
24.2%prior 95
7
SUBARU98 (3.5%)
5.4%prior 93
8
HYUNDAI75 (2.7%)
38.9%prior 54
9
BMW66 (2.4%)
15.8%prior 57
10
MAZDA62 (2.2%)
87.9%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (2,847 persons with recorded sex)

Male1,683 (59.1%)
-8.2%prior 1,833
Female1,163 (40.9%)
-9.4%prior 1,283
X / Unspecified1 (0.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone, the most frequent location for incidents, decreased from 1,108 in the prior year to 912 in the current year. The number of fatal crashes in this zone also dropped from two to one. Conversely, crashes in the 55 mph zone saw a slight increase from 139 to 146 incidents, though the single fatality recorded in that zone in the prior year was not repeated.

Fatal crashes by zone: 30 mph: 1 of 912 (0.11%) · 45 mph: 1 of 9 (11.111%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: WALTHAM, MA
  • Total crash records analyzed: 1,456
  • Total persons involved: 3,766
  • Total vehicles involved: 2,803

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/waltham/2023-annual-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 — 2023 | ThatCarHitMe.com