ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MASSACHUSETTS, MA · APRIL 2024
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-2024-report
Monthly Traffic Safety Analysis
10,260 CRASHES IN
MASSACHUSETTS, MA
APRIL 2024
In April 2024, there were 10,260 total traffic crashes, a 5.3% increase from the 9,740 crashes recorded in April 2023. While total collisions rose, the number of fatalities decreased from 26 to 21. The most significant year-over-year shift was a sharp increase in crashes involving speeding, with those attributed to 'driving too fast for conditions' more than doubling from 163 to 346 incidents.
10,260
▲ 5.3%was 9,740
Total Crash Events
21
▼ -19.2%was 26
Persons Killed
3,007
▼ -3.4%was 3,113
Persons Injured
973
▲ 1.9%was 955
Hit-and-Run Crashes
Note: "Persons Killed" (21) counts individual fatalities across all crash events. "Fatal" in the severity table below (21) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 527 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes increased by 5.3% in April 2024 compared to the same month in the previous year, rising from 9,740 to 10,260. Despite this increase in collision volume, both total fatalities (21 vs. 26) and total injuries (3,007 vs. 3,113) saw a year-over-year decline. This suggests a trend towards a higher frequency of less severe crashes.
973
Hit-and-Run Crashes — April 2024
▲ 1.9% vs prior (955)
The total number of hit-and-run crashes increased from 955 in April 2023 to 973 in April 2024. However, because the total number of crashes grew at a faster rate, the hit-and-run rate as a proportion of all collisions trended down slightly. The rate decreased from 9.8% in the prior period to 9.5% in the current period.
Vulnerable Road User Casualties
3
Pedestrians Killed
0
Cyclists Killed
17
Motorists Killed
1
Other Killed
93
Pedestrians Injured
54
Cyclists Injured
2,844
Motorists Injured
16
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed a shift in the peak day of the week, moving from Saturday (1,623 crashes) in April 2023 to Thursday (1,777 crashes) in April 2024. The peak hour for collisions remained in the afternoon commute window but shifted slightly earlier, from 4 PM in the prior year to 3 PM in the current period. Weekday crash volumes, particularly on Monday and Tuesday, were notably higher in April 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes was lower in April 2024 compared to the prior year. The proportion of fatal crashes decreased from 0.3% to 0.2% of all incidents, and serious injury crashes fell from 1.9% to 1.5%. Consequently, the share of crashes resulting in no injury increased from 70.1% in April 2023 to 72.9% in April 2024, indicating a higher volume of property-damage-only collisions.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors remained consistent, with 'Inattention' and 'Failed to yield right of way' ranking as the leading driver errors after 'No improper driving'. However, the count of crashes involving speed-related factors grew significantly; incidents attributed to 'Driving too fast for conditions' increased by 112% from 163 to 346. The count of crashes involving 'Followed too closely' also rose from 866 to 1,025.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A greater share of crashes occurred under adverse conditions in April 2024 compared to the previous year. The proportion of crashes on dry road surfaces decreased from 84.2% to 74.8%, while collisions on wet surfaces increased from 14.1% to 18.4% of the total. This corresponds with a higher number of crashes occurring during rain (821 in 2024 vs. 655 in 2023). Lighting conditions for crashes remained stable, with daylight accounting for the majority in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field
Vehicles & Demographics
Vehicle and person demographics remained stable year-over-year. Toyota, Honda, and Ford were the top three vehicle makes involved in crashes in both periods, with their counts increasing in line with the overall trend. The age distribution of persons involved in crashes also showed little change, with the 26-34 age group consistently representing the largest share of individuals involved in both April 2023 (16.2%) and April 2024 (16.9%).
Top Vehicle Makes (19,127 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records
2,367 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (20,725 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones was largely consistent, with zones posted at 30 mph or less accounting for approximately 60% of incidents in both periods. There was a minor shift towards higher speed corridors, with the proportion of crashes in zones 55 mph or greater increasing from 13.0% to 14.5% year-over-year. Fatal crashes were more concentrated in 25-30 mph and 65 mph zones in 2023, while in 2024 they were more broadly distributed across various speed limits.
Fatal crashes by zone: 25 mph: 3 of 2,046 (0.147%) · 30 mph: 3 of 2,841 (0.106%) · 35 mph: 5 of 1,369 (0.365%) · 40 mph: 1 of 724 (0.138%) · 45 mph: 4 of 361 (1.108%) · 50 mph: 2 of 244 (0.82%) · 55 mph: 1 of 566 (0.177%) · 65 mph: 1 of 746 (0.134%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-04-01 through 2024-04-30 (30 days)
- Geographic scope: massachusetts, MA
- Total crash records analyzed: 10,260
- Total persons involved: 23,434
- Total vehicles involved: 19,127
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 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/april-2024-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: 2024-04-01 – 2024-04-30
Generated: June 21, 2026 · All rights reserved