ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WATERTOWN, MA · 2023
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/watertown/2023-annual-report
Yearly Traffic Safety Analysis
331 CRASHES IN
WATERTOWN, MA
2023
In 2023, Watertown recorded 331 total traffic crashes, a 6.8% increase from the 310 crashes in 2022. While total fatalities remained unchanged at one death in each year, the number of injuries rose by 21.3% from 108 to 131. The most significant year-over-year change was a 116.7% increase in bicycle-involved crashes, which grew from 6 in 2022 to 13 in 2023.
331
▲ 6.8%was 310
Total Crash Events
1
Persons Killed
131
▲ 21.3%was 108
Persons Injured
4
▼ -55.6%was 9
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 6 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 collisions in Watertown trended upward from 2022 to 2023, with total crashes increasing by 6.8% from 310 to 331. The number of people injured in these incidents also saw a significant rise of 21.3%, from 108 to 131. The number of fatalities remained stable, with one person killed in each year.
4
Hit-and-Run Crashes — 2023
▼ -55.6% vs prior (9)
The number of hit-and-run crashes decreased significantly, falling by 55.6% from 9 incidents in 2022 to 4 in 2023. Consequently, the hit-and-run rate, representing the percentage of total crashes that were hit-and-runs, also trended down. The rate dropped from 2.9% of all crashes in 2022 to 1.2% in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
12
Pedestrians Injured
13
Cyclists Injured
105
Motorists Injured
1
Other Injured
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 timing of crashes shifted between the two years. In 2023, the peak day for crashes was Wednesday with 64 incidents, whereas in 2022 it was Friday with 60 incidents. Similarly, the peak hour for collisions moved from the 5 PM evening commute in 2022 (37 crashes) to the 1 PM hour in 2023 (29 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
The number of fatal crashes remained constant with one incident in both 2023 and 2022, resulting in a nearly stable fatal crash rate of 0.3% and 0.32% respectively. The composition of injury crashes changed, with 'Serious Injury' crashes decreasing from 7 to 2, while 'Possible Injury' crashes increased from 26 to 46. The proportion of crashes resulting in any type of injury increased from 30.6% of all crashes in 2022 to 35.0% in 2023.
Outcome by Severity (Crash Events)
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
In 2023, 'Failed to yield right of way' became the top contributing factor with 84 crashes, representing a 47.4% increase in count from 57 in 2022 when it was the second-leading factor. 'Inattention', the top factor in 2022 with 61 crashes, saw its count decrease slightly to 59 in 2023. Crashes attributed to distraction also saw a notable drop, decreasing by 50% from 14 incidents in 2022 to 7 in 2023.
Officer-Reported Primary Contributing Cause
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
Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring in 'Daylight' (236 in 2023 vs. 216 in 2022) and on 'Dry' road surfaces (258 vs. 259). However, there was a notable increase in crashes on 'Wet' roads, which rose from 46 in 2022 to 67 in 2023. Crashes during 'Rain' also increased from 21 to 27 over the same period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent across both years: Toyota (141 in 2023 vs. 118 in 2022), Honda (88 vs. 79), and Ford (67 vs. 51). In terms of persons involved, the 26-34 age group was the most represented in both periods, with an identical count of 147 individuals. The most significant demographic shift occurred in the 35-44 age group, which saw its involvement in crashes increase by 27.4%, from 106 people in 2022 to 135 in 2023.
Top Vehicle Makes (616 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
65 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (698 persons with recorded sex)
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
The vast majority of crashes in both periods occurred in 30 MPH speed zones, with the count rising from 284 in 2022 to 303 in 2023. This zone was also the location of the single fatal crash recorded in each respective year. The distribution of crashes across other speed zones, such as 25 MPH and 35 MPH, showed only minor fluctuations between the two years.
Fatal crashes by zone: 30 mph: 1 of 303 (0.33%)
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: WATERTOWN, MA
- Total crash records analyzed: 331
- Total persons involved: 758
- Total vehicles involved: 616
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). "WATERTOWN, 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/watertown/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved