ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GLOUCESTER, 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/gloucester/2023-annual-report
Yearly Traffic Safety Analysis
609 CRASHES IN
GLOUCESTER, MA
2023
In 2023, Gloucester recorded 609 total traffic crashes, an increase of 10.1% from the 553 crashes reported in 2022. While total reported injuries saw a slight decrease, the most significant year-over-year change was the occurrence of one fatal crash in 2023, compared to zero in the prior year.
609
▲ 10.1%was 553
Total Crash Events
1
Persons Killed
112
▼ -5.1%was 118
Persons Injured
57
▼ -10.9%was 64
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. 69 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
Crash trends in Gloucester show an increase in total incidents year-over-year. Total crashes rose by 10.1%, from 553 in 2022 to 609 in 2023. Despite this increase in crash volume, the total number of persons injured decreased by 5.1% from 118 to 112.
57
Hit-and-Run Crashes — 2023
▼ -10.9% vs prior (64)
Hit-and-run incidents decreased in both absolute numbers and as a proportion of total crashes. The number of hit-and-run crashes fell from 64 in 2022 to 57 in 2023. This represents a downward trend in the hit-and-run rate, which dropped from 11.6% to 9.4% of all crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
8
Pedestrians Injured
6
Cyclists Injured
98
Motorists 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 temporal patterns of crashes in Gloucester shifted between 2022 and 2023. In 2023, the peak days for crashes were Tuesday and Friday, each with 102 incidents, whereas Friday was the sole peak day in 2022 with 92 crashes. The peak hour for crashes also shifted from 12 PM in 2022 (48 crashes) to 3 PM in 2023 (55 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 severity of crashes changed notably, with one fatal crash recorded in 2023 compared to none in 2022, increasing the fatal crash rate from 0 to 0.16 per 100 crashes. The proportion of injury-related crashes decreased, with serious injuries accounting for 0.8% of crashes in 2023, down from 1.3% in 2022. Crashes resulting in no injury made up a larger share of the total, increasing from 72.9% in 2022 to 74.2% 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
The leading contributing factors for crashes remained largely consistent, with 'No improper driving' cited most often in both years, increasing in count from 168 in 2022 to 184 in 2023. Crashes attributed to 'Failed to yield right of way' saw a notable increase in count from 17 to 26, moving from the fifth to the third most common factor. Conversely, crashes involving 'Inattention' saw a slight decrease in count from 57 to 55, though it remained the second-ranked factor.
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
While most crashes in both periods occurred in clear weather on dry roads, there was a shift in adverse conditions. In 2023, 16.9% of crashes occurred on non-dry surfaces (103 crashes), up from 15.0% in 2022 (83 crashes), primarily due to an increase in crashes on wet roads from 57 to 86. Crashes in non-daylight conditions also saw a slight proportional increase, accounting for 25.5% of incidents in 2023 compared to 24.1% in 2022.
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 vehicle makes involved in crashes remained consistent, with Toyota, Ford, Honda, and Chevrolet leading in both years. In 2023, Jeep replaced Nissan as the fifth most common make, with its involvement increasing from 55 to 83 vehicles. Analysis of persons involved shows an increase in crash involvement for several age groups, most notably for those aged 16-20 (from 83 to 110 persons) and those 65 and older (from 175 to 201 persons).
Top Vehicle Makes (1,129 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
242 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (975 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 distribution of crashes across speed zones shifted, with a significant increase in incidents within 25 mph zones, which rose from 182 crashes in 2022 to 250 in 2023. Conversely, crashes in 55 mph zones decreased from 36 to 27. The single fatal crash recorded in 2023 occurred in a 20 mph speed zone; no fatal crashes were reported in any speed zone in 2022.
Fatal crashes by zone: 20 mph: 1 of 53 (1.887%)
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: GLOUCESTER, MA
- Total crash records analyzed: 609
- Total persons involved: 1,236
- Total vehicles involved: 1,129
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). "GLOUCESTER, 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/gloucester/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