ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MASSACHUSETTS, MA · APRIL 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/statewide/april-2023-report
Monthly Traffic Safety Analysis
9,740 CRASHES IN
MASSACHUSETTS, MA
APRIL 2023
In April 2023, there were 9,740 total crashes, a 1.3% increase from the 9,614 crashes recorded in April 2022. The most notable year-over-year change was a 32.1% increase in hit-and-run incidents, which rose from 723 to 955. Overall fatalities increased from 23 to 26, and injuries rose from 2,952 to 3,113.
9,740
▲ 1.3%was 9,614
Total Crash Events
26
▲ 13.0%was 23
Persons Killed
3,113
▲ 5.5%was 2,952
Persons Injured
955
▲ 32.1%was 723
Hit-and-Run Crashes
Note: "Persons Killed" (26) counts individual fatalities across all crash events. "Fatal" in the severity table below (26) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 600 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends show a slight increase year-over-year. Total crashes rose by 1.3%, from 9,614 in April 2022 to 9,740 in April 2023. This was accompanied by a 5.5% increase in total injuries (from 2,952 to 3,113) and a 13.0% increase in fatalities (from 23 to 26).
955
Hit-and-Run Crashes — April 2023
▲ 32.1% vs prior (723)
Hit-and-run crashes increased significantly between April 2022 and April 2023. The total count of hit-and-run incidents rose by 32.1%, from 723 to 955. The hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also trended upward, increasing from 7.5% to 9.8% over the same period.
Vulnerable Road User Casualties
7
Pedestrians Killed
1
Cyclists Killed
18
Motorists Killed
0
Other Killed
89
Pedestrians Injured
79
Cyclists Injured
2,928
Motorists Injured
17
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The time of day with the most crashes remained consistent, with the 4 p.m. hour being the peak period in both April 2023 (816 crashes) and April 2022 (802 crashes). However, the peak day of the week for crashes shifted. In April 2022, Friday was the busiest day with 1,960 crashes, whereas in April 2023, Saturday saw the most incidents with 1,623 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate saw a slight increase, moving from 0.24% in April 2022 to 0.27% in April 2023, with the number of fatal crashes rising from 23 to 26. The proportion of crashes resulting in serious injury remained stable at 1.9% (183 incidents) compared to 1.8% (174 incidents) the previous year. Crashes involving minor injuries increased slightly as a share of the total, from 13.4% in the prior period to 13.9% in the current period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors remained consistent year-over-year, with 'No improper driving' and 'Inattention' leading in both periods. However, the counts for some key factors shifted notably. Crashes attributed to 'Inattention' decreased by 7.9% in count, from 1,457 incidents in April 2022 to 1,342 in April 2023. Conversely, crashes involving 'Failed to yield right of way' increased by 17.7% in count (from 896 to 1,055), and those related to 'Failure to keep in proper lane' rose by 30.5% in count (from 406 to 530).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across lighting conditions remained stable, with approximately 73% of incidents in both April 2023 and April 2022 occurring during daylight. There was a minor shift in road surface conditions, as the proportion of crashes on dry roads decreased from 86.0% to 84.2% year-over-year. Correspondingly, the share of crashes occurring on wet roads increased from 12.3% in the prior period to 14.1% in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained unchanged: Toyota, Honda, and Ford held the top spots in both April 2022 and April 2023. Toyota involvement increased from 2,841 vehicles to 2,996, and Honda from 2,280 to 2,394. Analysis of persons involved shows a largely stable age distribution, though the share of individuals aged 65 and older increased from 9.6% of all persons in April 2022 to 10.4% in April 2023.
Top Vehicle Makes (18,142 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records
2,600 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (20,092 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones, the most frequent location, decreased slightly from 2,707 to 2,685 year-over-year. In contrast, incidents in 65 mph zones increased from 550 to 616. A notable shift occurred in the distribution of fatal crashes by speed zone. Fatalities in 65 mph zones tripled, rising from 2 in April 2022 to 6 in April 2023, while fatalities in 30 mph zones increased from 5 to 7.
Fatal crashes by zone: 5 mph: 1 of 96 (1.042%) · 25 mph: 6 of 1,900 (0.316%) · 30 mph: 7 of 2,685 (0.261%) · 35 mph: 3 of 1,238 (0.242%) · 40 mph: 1 of 702 (0.142%) · 50 mph: 1 of 204 (0.49%) · 65 mph: 6 of 616 (0.974%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-04-01 through 2023-04-30 (30 days)
- Geographic scope: massachusetts, MA
- Total crash records analyzed: 9,740
- Total persons involved: 22,964
- Total vehicles involved: 18,142
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). "massachusetts, MA Crash Intelligence Report: April 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/april-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: 2023-04-01 – 2023-04-30
Generated: June 21, 2026 · All rights reserved