ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ANDOVER, MA · FEBRUARY 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/andover/february-2023-report
Monthly Traffic Safety Analysis
64 CRASHES IN
ANDOVER, MA
FEBRUARY 2023
In February 2023, Andover experienced a decrease in total crashes compared to the previous year, with 64 crashes recorded versus 90 in February 2022. This represents a 28.9% reduction in overall crash incidents. The most notable year-over-year shift was a 100% increase in hit-and-run crashes, rising from 6 to 12 incidents.
64
▼ -28.9%was 90
Total Crash Events
0
Persons Killed
10
▼ -47.4%was 19
Persons Injured
12
▲ 100.0%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. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a significant decrease in crash activity year-over-year, with total crashes falling from 90 in February 2022 to 64 in February 2023. This represents a 28.9% reduction in the total number of reported crashes. Fatalities remained at 0 in both periods, while total injuries decreased from 19 to 10.
12
Hit-and-Run Crashes — February 2023
▲ 100.0% vs prior (6)
Hit-and-run crashes increased significantly year-over-year, from 6 incidents in February 2022 to 12 incidents in February 2023, representing a 100% increase. The hit-and-run rate also more than doubled, rising from 6.7% of all crashes in the prior period to 18.8% in the current period, indicating a notable upward trend.
Vulnerable Road User Casualties
0
Motorists Killed
10
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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 Friday in February 2022, which saw 23 incidents, to Thursday in February 2023, with 16 crashes. Similarly, the peak hour for crashes moved from 3 p.m. (12 crashes) in the prior period to 8 a.m. (8 crashes) in the current period. These changes suggest a shift in the timing of peak crash activity.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at 0 in both February 2022 and February 2023. The total number of injuries decreased from 19 in the prior period to 10 in the current period. The proportion of crashes resulting in any injury also decreased, from 21.1% of all crashes in February 2022 to 15.6% in February 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record
Top Contributing Factors
The count of crashes where 'Followed too closely' was a factor saw a 50% decrease, dropping from 14 in February 2022 to 7 in February 2023. Crashes attributed to 'No improper driving' decreased by 2, from 19 to 17, while 'Inattention' also decreased by 2, from 11 to 9. Conversely, 'Failed to yield right of way' crashes increased from 3 to 5, a 66.7% rise year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather decreased from 47 in February 2022 to 35 in February 2023, and those on 'Dry' road surfaces decreased from 54 to 42. While the number of crashes under 'Daylight' conditions decreased from 60 to 39, the proportion of crashes occurring in 'Dark - roadway not lighted' conditions remained relatively stable, representing 14.4% (13 of 90) in the prior period and 15.6% (10 of 64) in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 149 in February 2022 to 113 in February 2023. Honda remained the most frequently involved vehicle make, though its count decreased from 29 to 23. The age group 35-44 consistently had the highest number of persons involved in crashes in both periods, with 29 in February 2022 and 28 in February 2023.
Top Vehicle Makes (113 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (111 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events
Speed Limit Zones
The highest number of crashes in both periods occurred in the 65 mph speed limit zone, decreasing from 35 crashes in February 2022 to 23 crashes in February 2023. Crashes in the 30 mph zone also decreased from 18 to 11. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-02-01 through 2023-02-28 (28 days)
- Geographic scope: ANDOVER, MA
- Total crash records analyzed: 64
- Total persons involved: 124
- Total vehicles involved: 113
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). "ANDOVER, MA Crash Intelligence Report: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/andover/february-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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-02-01 – 2023-02-28
Generated: June 21, 2026 · All rights reserved