ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WATERTOWN, MA · 2022
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/2022-annual-report
Yearly Traffic Safety Analysis
310 CRASHES IN
WATERTOWN, MA
2022
In 2022, Watertown experienced 310 total traffic crashes, a 17% increase from the 265 crashes recorded in 2021. While the total number of injuries remained stable at 108 for both years, the most notable shift was the occurrence of one fatal crash in 2022, compared to none in the prior year. The number of crashes resulting in serious injuries also increased from 2 in 2021 to 7 in 2022.
310
▲ 17.0%was 265
Total Crash Events
1
Persons Killed
108
Persons Injured
9
▲ 12.5%was 8
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. 8 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic crashes in Watertown trended upward year-over-year, with a 17% rise from 265 incidents in 2021 to 310 in 2022. Despite this increase in total collisions, the number of resulting injuries held constant at 108 persons injured in both periods. However, the year saw the introduction of one fatality, where the prior year had none.
9
Hit-and-Run Crashes — 2022
▲ 12.5% vs prior (8)
The number of hit-and-run crashes saw a minor increase from 8 incidents in 2021 to 9 in 2022, representing a 12.5% rise in count. However, due to the overall increase in total crashes, the hit-and-run rate as a percentage of all crashes saw a slight decrease, moving from 3.0% in 2021 to 2.9% in 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Cyclists Killed
0
Motorists Killed
13
Pedestrians Injured
5
Cyclists Injured
90
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between the two years. The peak hour for crashes remained the 5 p.m. hour in both 2022 and 2021, though the number of crashes during this hour increased from 27 to 37. The most common day for crashes changed, shifting from a tie between Monday and Thursday (46 crashes each) in 2021 to Friday (60 crashes) in 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased in 2022 compared to 2021. The city recorded one fatal crash in 2022, whereas there were none in the prior year. The count of serious injury crashes more than tripled, rising from 2 in 2021 to 7 in 2022, increasing the share of crashes resulting in serious injury from 0.8% to 2.3% of all incidents.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The ranking of top contributing factors shifted between periods. In 2022, 'Inattention' became the leading factor with 61 crashes, an increase of 32.6% from its 2021 count of 46. 'Failed to yield right of way,' the top factor in 2021 with 50 crashes, increased its count to 57 in 2022 but fell to the second position. The count of crashes attributed to 'Failure to keep in proper lane or running off road' nearly doubled, from 11 in 2021 to 21 in 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across different environmental conditions remained largely consistent year-over-year. In both 2022 and 2021, crashes predominantly occurred in clear weather and on dry road surfaces. Crashes on wet roads were nearly identical, with 46 in 2022 and 45 in 2021. Similarly, the vast majority of incidents in both periods happened during daylight hours.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in crashes were consistent across both years, with Toyota, Honda, and Ford being the top three in both 2022 and 2021. The total number of vehicles involved in crashes increased from 493 to 600, corresponding to the rise in total crashes. The age distribution of persons involved also remained stable, with the 26-34 age group representing the largest cohort in both periods, accounting for 147 individuals in 2022 and 103 in 2021.
Top Vehicle Makes (600 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
85 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (621 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes remained concentrated in the 30 mph speed zone in both years, with the count increasing from 244 in 2021 to 284 in 2022. This zone accounted for over 91% of all crashes with a recorded speed limit in 2022. The single fatal crash in 2022 occurred within a 30 mph zone, whereas no fatal crashes were recorded in any speed zone during 2021.
Fatal crashes by zone: 30 mph: 1 of 284 (0.352%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: WATERTOWN, MA
- Total crash records analyzed: 310
- Total persons involved: 705
- Total vehicles involved: 600
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/watertown/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved