Monthly Traffic Safety Analysis

25 CRASHES IN
NEWBURYPORT, MA
DECEMBER 2023

All metrics benchmarked againstDecember 2022

In December 2023, Newburyport experienced 25 total crashes, an 8.7% increase from the 23 crashes reported in December 2022. A notable year-over-year shift was the significant increase in crashes attributed to inattention, rising from 3 in the prior period to 8 in the current period.

25

8.7%was 23

Total Crash Events

0

Persons Killed

7

16.7%was 6

Persons Injured

4

-33.3%was 6

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 1 crash with unreported severity is not shown in the severity breakdown.

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

Trend Summary

Overall crash activity in Newburyport showed a slight increase year-over-year, with total crashes rising by 8.7% from 23 in December 2022 to 25 in December 2023. Concurrently, total injuries increased by 16.7%, from 6 to 7 during the same period.

4

Hit-and-Run Crashes — December 2023

-33.3% vs prior (6)

The number of hit-and-run crashes decreased from 6 in December 2022 to 4 in December 2023, representing a decrease of 2 crashes. This resulted in the hit-and-run crash rate falling from 26.1% of all crashes in the prior period to 16% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 616.7%

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

When Crashes Happen

The peak day for crashes shifted from Saturday with 4 crashes in December 2022 to Thursday and Sunday, each with 5 crashes, in December 2023. The peak crash hour also changed, moving from 6 PM with 3 crashes in the prior period to 5 PM with 6 crashes in the current period. Crashes in the current period show a higher concentration around 9 AM and 5 PM compared to the prior period's more distributed afternoon peaks.

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

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

Crash Severity Breakdown

Fatal crashes remained at zero in both December 2022 and December 2023. The current period saw one serious injury (A) crash, which was not present in the prior period. Minor injury (B) crashes remained constant at 3, while possible injury (C) crashes also remained stable at 2 for both periods, despite an overall increase in total crashes.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4%
Minor Injury3minor injury crashes12%
0.0%prior 3
Possible Injury2possible injury crashes8%
0.0%prior 2
No Injury18no injury crashes72%
12.5%prior 16

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

The number of crashes attributed to 'Inattention' significantly increased from 3 in December 2022 to 8 in December 2023, representing a 166.7% change in count. Conversely, crashes with 'No improper driving' as a factor decreased by 2, from 9 to 7, a 22.2% change in count. The factor 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased by 1 crash, from 2 to 1.

Officer-Reported Primary Contributing Cause

Inattention8 (32%)
No improper driving7 (28%)-22.2%prior 9
Other improper action2 (8%)
Failed to yield right of way2 (8%)
Followed too closely1 (4%)
Failure to keep in proper lane or running off road1 (4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4%)

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

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions slightly increased from 11 in December 2022 to 12 in December 2023. Crashes on 'Wet' road surfaces increased from 5 in the prior period to 9 in the current period, while 'Dry' road surface crashes decreased by 1, from 17 to 16. There was a notable increase in crashes occurring in 'Dark - lighted roadway' conditions, rising from 5 to 12, matching the 12 crashes that occurred during 'Daylight' in the current period.

Weather

Clear12 (48.0%)
9.1%prior 11
Cloudy/Rain3 (12.0%)
Cloudy2 (8.0%)
Rain2 (8.0%)
Clear/Cloudy1 (4.0%)
Fog, smog, smoke1 (4.0%)
Rain/Cloudy1 (4.0%)
Clear/Other1 (4.0%)
Snow1 (4.0%)
Cloudy/Other1 (4.0%)

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

Lighting

Dark - lighted roadway12 (48.0%)
140.0%prior 5
Daylight12 (48.0%)
0.0%prior 12
Dusk1 (4.0%)

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

Road Surface

Dry16 (64.0%)
-5.9%prior 17
Wet9 (36.0%)
80.0%prior 5

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

Vehicles & Demographics

Top Vehicle Makes (48 vehicles)

1
TOYOTA6 (12.5%)
20.0%prior 5
2
FORD5 (10.4%)
3
NISSAN4 (8.3%)
4
CHEVROLET4 (8.3%)
-42.9%prior 7
5
AUDI4 (8.3%)
6
HONDA4 (8.3%)
7
JEEP4 (8.3%)
-20.0%prior 5
8
DODGE2 (4.2%)
9
SUBARU2 (4.2%)
10
RAM2 (4.2%)

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

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

Sex Distribution (48 persons with recorded sex)

Male25 (52.1%)
38.9%prior 18
Female23 (47.9%)
-8.0%prior 25

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

Speed Limit Zones

Crashes occurring in 25 mph speed zones increased from 10 in December 2022 to 12 in December 2023. The number of crashes in 35 mph zones remained constant at 4 for both periods. Crashes in 65 mph zones, present in the prior period with 2 crashes, were not reported in the current period, while a new speed zone of 40 mph appeared with 1 crash.

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

Data Coverage

  • Reporting period: 2023-12-01 through 2023-12-31 (31 days)
  • Geographic scope: NEWBURYPORT, MA
  • Total crash records analyzed: 25
  • Total persons involved: 58
  • Total vehicles involved: 48

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

Newburyport, MA Crash Report — December 2023 | ThatCarHitMe.com