ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BOXFORD, 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/boxford/2023-annual-report
Yearly Traffic Safety Analysis
127 CRASHES IN
BOXFORD, MA
2023
In 2023, Boxford recorded 127 total traffic crashes, a 5.8% increase from the 120 crashes reported in 2022. While total crashes saw a modest rise, the most significant change was the occurrence of 2 fatal crashes resulting in 2 fatalities in 2023, compared to zero in the prior year. Total reported injuries decreased from 62 in 2022 to 43 in 2023.
127
▲ 5.8%was 120
Total Crash Events
2
Persons Killed
43
▼ -30.6%was 62
Persons Injured
7
▲ 250.0%was 2
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 17 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
The overall trend in Boxford shows a 5.8% increase in total crashes, rising from 120 in 2022 to 127 in 2023. Despite the rise in crashes, the number of people injured decreased by 30.6% from 62 to 43. However, 2023 saw 2 fatalities, whereas none were recorded in 2022.
7
Hit-and-Run Crashes — 2023
▲ 250.0% vs prior (2)
The number of hit-and-run incidents increased from 2 in 2022 to 7 in 2023, a more than threefold rise in the absolute count. The hit-and-run rate, which measures the proportion of total crashes that were hit-and-runs, also trended upward, increasing from 1.7% in 2022 to 5.5% in 2023.
Vulnerable Road User Casualties
0
Cyclists Killed
2
Motorists Killed
1
Cyclists Injured
42
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 timing of crashes in Boxford shifted between 2022 and 2023. The peak day for collisions moved from Friday (21 crashes) in 2022 to Monday (28 crashes) in 2023. Similarly, the peak hour for crashes occurred slightly earlier, shifting from 3 p.m. in 2022 (12 crashes) to 2 p.m. in 2023 (13 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
Crash severity in 2023 was marked by the appearance of 2 fatal incidents, which were absent in 2022, causing the fatal crash rate to rise from 0% to 1.6%. While the number of serious injury crashes remained stable at 4, the proportion of crashes involving possible injuries decreased from 15.8% in 2022 (19 crashes) to 7.9% in 2023 (10 crashes). Correspondingly, the share of non-injury crashes increased from 50.8% to 61.4% of all incidents.
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
While 'No improper driving' remained the most cited factor in both years, its count slightly decreased from 34 in 2022 to 32 in 2023. Several other factors saw notable increases in their crash counts. Crashes attributed to 'Inattention' more than doubled, rising from 4 to 9, and incidents involving 'Driving too fast for conditions' increased from 5 to 9. The count of crashes related to 'Followed too closely' tripled from 2 in 2022 to 6 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
Crashes on non-dry road surfaces increased significantly in 2023. Incidents on wet roads more than doubled from 12 to 29, and crashes on snowy roads increased from 5 to 13. This shift is mirrored in weather conditions, with fewer crashes occurring in clear weather (75 in 2023 vs. 92 in 2022). Crashes in darkness on unlit roadways also saw a slight increase from 37 to 41 incidents.
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, with Honda, Ford, and Toyota leading in both years, though their rankings shifted. The number of Ford vehicles in crashes grew from 18 to 27. The demographic profile of persons involved also changed; there was a notable increase in the 35-44 and 45-54 age groups, while the number of persons in the 26-34 age group decreased from 49 to 28.
Top Vehicle Makes (191 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
18 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (199 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
In 2023, there was an increase in crashes within several speed zones compared to 2022, notably in 25 mph zones (23 vs. 15 crashes), 40 mph zones (21 vs. 15 crashes), and 65 mph zones (47 vs. 42 crashes). The two fatal crashes recorded in 2023 occurred in areas with posted speed limits of 35 mph and 40 mph. No fatal crashes were reported in any speed zone during the prior year.
Fatal crashes by zone: 35 mph: 1 of 10 (10%) · 40 mph: 1 of 21 (4.762%)
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: BOXFORD, MA
- Total crash records analyzed: 127
- Total persons involved: 249
- Total vehicles involved: 191
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). "BOXFORD, 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/boxford/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