ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEWBURYPORT, 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/newburyport/2022-annual-report
Yearly Traffic Safety Analysis
265 CRASHES IN
NEWBURYPORT, MA
2022
In 2022, Newburyport recorded 265 total traffic crashes, an increase of 7.3% from the 247 crashes documented in 2021. While the number of fatalities decreased from 3 to 1, total injuries rose by 31.9% from 47 to 62. One of the most significant year-over-year shifts was in hit-and-run incidents, which increased by 90.9%, from 11 in 2021 to 21 in 2022.
265
▲ 7.3%was 247
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
62
▲ 31.9%was 47
Persons Injured
21
▲ 90.9%was 11
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. 18 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 crash trends in Newburyport show an increase year-over-year. The total number of crashes rose by 7.3%, from 247 in 2021 to 265 in 2022. While fatalities declined from 3 to 1, the number of people injured in these incidents increased by 31.9% from 47 to 62.
21
Hit-and-Run Crashes — 2022
▲ 90.9% vs prior (11)
The number of hit-and-run crashes increased significantly year-over-year. In 2022, there were 21 hit-and-run incidents, a 90.9% increase from the 11 recorded in 2021. Consequently, the hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, rose from 4.5% in 2021 to 7.9% in 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
4
Pedestrians Injured
1
Cyclists Injured
56
Motorists Injured
1
Other 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 a shift between 2021 and 2022. The peak day for crashes moved from Friday (47 incidents) in the prior year to Wednesday (43 incidents) in the current year. The peak hour for collisions remained consistent at 3 p.m. for both periods, with the number of crashes during that hour increasing from 27 to 32.
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
While total crashes increased, the severity profile of those crashes shifted. The number of fatal crashes decreased from 3 in 2021 to 1 in 2022, and the corresponding fatal crash share dropped from 1.2% to 0.4% of all incidents. The count of serious injury crashes remained unchanged at 4. The proportion of crashes resulting in no injuries increased from 67.6% of all crashes in 2021 to 75.1% in 2022.
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 leading contributing factors shifted between the two years. In 2022, 'Inattention' became the most cited factor, with its count increasing by 21.3% from 61 to 74 incidents, overtaking 'No improper driving' which was the top factor in 2021. The count for 'Failed to yield right of way' decreased from 21 to 17. Notably, crashes attributed to an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' more than doubled, rising from 6 incidents in 2021 to 13 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
Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring in 'Daylight' (190 in 2022 vs. 181 in 2021) and on 'Dry' road surfaces (219 vs. 195). The number of crashes during adverse weather conditions like rain or snow saw a decrease, falling from a combined 24 incidents in 2021 to 16 in 2022. Crashes occurring after dark on lighted roadways increased from 34 to 45.
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 top three vehicle makes involved in crashes remained consistent: Toyota, Ford, and Honda, with Toyota taking the top rank in 2022 with 70 vehicles involved, up from 53 in 2021. Analysis of persons involved shows the 65+ age group was the largest demographic in both years, with 89 individuals in 2022 compared to 91 in 2021. The number of persons aged 0-15 involved in crashes more than doubled, increasing from 14 in 2021 to 31 in 2022.
Top Vehicle Makes (503 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
80 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (482 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
The distribution of crashes across speed zones remained concentrated in lower-speed areas. In both years, 25 mph zones accounted for the highest number of crashes, with 118 in 2022 and 120 in 2021. Crashes in 35 mph zones saw an increase from 35 to 47. The single fatal crash in 2022 occurred in a 65 mph zone, whereas in 2021, fatal crashes were recorded in both a 25 mph zone and a 65 mph zone.
Fatal crashes by zone: 65 mph: 1 of 18 (5.556%)
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: NEWBURYPORT, MA
- Total crash records analyzed: 265
- Total persons involved: 593
- Total vehicles involved: 503
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). "NEWBURYPORT, 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/newburyport/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