ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BOXBOROUGH, 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/boxborough/2023-annual-report
Yearly Traffic Safety Analysis
88 CRASHES IN
BOXBOROUGH, MA
2023
In 2023, Boxborough recorded 88 total vehicle crashes, a 17.3% increase from the 75 crashes documented in 2022. While total injuries remained stable with 21 in 2023 versus 20 in the prior year, and fatalities were zero in both periods, there was a notable shift in contributing factors. The most significant change was a surge in crashes attributed to inattention, which increased from 6 incidents in 2022 to 16 in 2023.
88
▲ 17.3%was 75
Total Crash Events
0
Persons Killed
21
▲ 5.0%was 20
Persons Injured
4
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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends in Boxborough show a year-over-year increase, with total incidents rising from 75 in 2022 to 88 in 2023, marking a 17.3% increase. The number of people injured in these crashes saw a marginal rise from 20 to 21. However, there were no fatalities reported in either 2022 or 2023.
4
Hit-and-Run Crashes — 2023
▼ 0.0% vs prior (4)
The number of hit-and-run crashes in Boxborough remained unchanged year-over-year, with 4 incidents reported in both 2022 and 2023. However, due to the overall increase in total crashes, the hit-and-run rate saw a slight decrease. The rate fell from 5.3% of all crashes in 2022 to 4.5% in 2023.
Vulnerable Road User Casualties
0
Motorists Killed
21
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 shifted between the two periods. In 2023, the peak day for crashes was Wednesday with 16 incidents, a change from 2022 when Monday and Saturday shared the peak with 16 crashes each. The peak hour for collisions also moved slightly later, from 4 PM in 2022 (11 crashes) to 5 PM in 2023 (9 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 overall severity of crashes remained relatively low, with zero fatal crashes reported in either 2022 or 2023. In 2023, one crash resulted in a serious injury, a category not present in the 2022 data. The proportion of crashes resulting in no injuries increased from 77.3% in 2022 to 84.1% in 2023, while the count of minor injury crashes decreased from 10 to 8.
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
A comparison of contributing factors reveals a significant increase in crashes due to inattention, with the count rising from 6 in 2022 to 16 in 2023. This change elevated inattention to the second most common factor, behind 'No improper driving.' Meanwhile, crashes attributed to 'Followed too closely' remained constant at 11 incidents for both years. Crashes linked to distraction also increased, from 1 in 2022 to 3 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
Crash conditions showed some year-over-year variation, although clear weather and dry roads remained the most common circumstances in both periods. Crashes on wet roads increased from 7 in 2022 to 13 in 2023, while incidents on snowy surfaces decreased from 9 to 6. Collisions in cloudy weather also saw an increase, rising from 2 incidents in 2022 to 9 in 2023.
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 makes of vehicles involved in crashes saw some shifts between 2022 and 2023. While Toyota remained a top make, its involvement decreased from 29 vehicles to 25. Conversely, Ford's involvement increased from 13 to 24 vehicles, making it the second most common make in 2023. Demographically, the number of persons aged 65 and older involved in crashes increased from 14 in 2022 to 23 in 2023.
Top Vehicle Makes (151 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (156 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
There was a notable shift in crashes toward higher speed zones in 2023 compared to the previous year. The number of crashes in 65 mph zones increased from 31 in 2022 to 45 in 2023, accounting for 51.1% of all crashes with speed data in the recent period, up from 41.3%. Incidents in other speed zones, such as 40 mph, remained relatively stable. No fatal crashes occurred in any speed zone during either period.
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: BOXBOROUGH, MA
- Total crash records analyzed: 88
- Total persons involved: 178
- Total vehicles involved: 151
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). "BOXBOROUGH, 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/boxborough/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