ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MASSACHUSETTS, 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/statewide/2023-annual-report
Yearly Traffic Safety Analysis
135,367 CRASHES IN
MASSACHUSETTS, MA
2023
In 2023, there were 135,367 total traffic crashes, representing a 0.7% increase from the 134,419 crashes recorded in 2022. While the overall crash volume was stable, the most significant year-over-year change was a 21.0% decrease in total fatalities, which fell from 434 in 2022 to 343 in 2023. Another notable shift was an 18.8% increase in the number of hit-and-run crashes.
135,367
▲ 0.7%was 134,419
Total Crash Events
343
▼ -21.0%was 434
Persons Killed
42,034
▲ 4.3%was 40,308
Persons Injured
12,491
▲ 18.8%was 10,516
Hit-and-Run Crashes
Note: "Persons Killed" (343) counts individual fatalities across all crash events. "Fatal" in the severity table below (325) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 8,052 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 total number of crashes remained relatively stable, increasing by 0.7% from 134,419 in 2022 to 135,367 in 2023. While overall crash volume was steady, the outcomes shifted; total injuries rose by 4.3% to 42,034, whereas total fatalities saw a significant decrease of 21.0%, dropping from 434 to 343.
12,491
Hit-and-Run Crashes — 2023
▲ 18.8% vs prior (10,516)
The incidence of hit-and-run crashes increased from 2022 to 2023. The total count of hit-and-run incidents rose by 18.8%, from 10,516 to 12,491. This pushed the hit-and-run rate, which measures the percentage of all crashes that are hit-and-runs, from 7.8% in 2022 to 9.2% in 2023, indicating an upward trend.
Vulnerable Road User Casualties
66
Pedestrians Killed
8
Cyclists Killed
267
Motorists Killed
2
Other Killed
1,629
Pedestrians Injured
1,116
Cyclists Injured
39,075
Motorists Injured
214
Other 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
Temporal crash patterns showed high consistency year-over-year. In both 2023 and 2022, Friday was the peak day for crashes, with 21,135 and 21,886 incidents, respectively. Similarly, the peak hour for collisions remained the 4 p.m. hour in both periods, recording 10,925 crashes in 2023 and 10,861 in 2022. The overall distribution of crashes by day of the week and hour of the day did not exhibit significant shifts between the two years.
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 severity of crashes shifted between the two periods, with a notable decrease in fatal outcomes. The number of fatal crashes decreased by 21.1%, from 412 in 2022 to 325 in 2023, causing their share of all crashes to fall from 0.3% to 0.2%. The proportion of crashes resulting in serious injury remained stable at 1.8%. Crashes involving minor injuries increased their share from 12.9% to 13.8%, and the proportion of no-injury crashes also rose from 69.4% to 71.0%.
Severity is per crash event (most severe injury). 325 fatal crash events resulted in 343 persons killed.
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
The ranking of the top five contributing factors for crashes was unchanged from 2022 to 2023, with 'No improper driving' cited most frequently in both years. However, the counts for several key factors shifted, with crashes attributed to 'Failed to yield right of way' increasing by 9.6% in count, from 13,196 to 14,469. Similarly, the count of crashes involving 'Followed too closely' grew by 6.7% (from 11,512 to 12,288). Conversely, crashes attributed to 'Inattention' saw a slight decrease in count of 0.5%, from 18,306 to 18,218.
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
Environmental conditions showed some notable shifts between 2022 and 2023. The proportion of crashes occurring on wet roads increased from 14.2% of all crashes in 2022 to 17.5% in 2023, representing a 24.3% increase in the number of such incidents (from 19,023 to 23,650). Correspondingly, crashes during rainy weather grew from 5.7% to 7.6% of the total, a 32.8% increase in count. In contrast, lighting conditions remained consistent, with daylight crashes accounting for approximately 67% of the total in both years.
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 five vehicle makes involved in crashes—Toyota, Honda, Ford, Chevrolet, and Nissan—remained unchanged in their rankings from 2022 to 2023. The age distribution of persons involved in crashes also showed broad stability, with most age groups' share of the total remaining consistent. However, the number of individuals aged 65 and older involved in crashes increased by 8.7%, from 30,459 to 33,121, and this group's representation grew from 10.0% to 10.5% of all persons involved in collisions.
Top Vehicle Makes (250,130 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
34,697 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (276,001 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
The distribution of crashes across different speed zones remained largely consistent year-over-year, with minor increases in crash counts in zones posted at 30 mph or less and 60 mph or more. A more significant trend was the decrease in the rate of fatal crashes across all speed categories. In zones with speed limits of 60 mph or higher, the rate of fatal crashes dropped from 0.70 per 100 crashes in 2022 to 0.55 in 2023. Similarly, the fatal rate in medium-speed zones (35-55 mph) decreased from 0.37 to 0.30, and in low-speed zones (30 mph or less) it fell from 0.22 to 0.18.
Fatal crashes by zone: 5 mph: 1 of 1,431 (0.07%) · 10 mph: 1 of 1,940 (0.052%) · 15 mph: 2 of 1,977 (0.101%) · 20 mph: 7 of 3,779 (0.185%) · 25 mph: 54 of 26,562 (0.203%) · 30 mph: 65 of 36,385 (0.179%) · 35 mph: 49 of 18,051 (0.271%) · 40 mph: 33 of 9,822 (0.336%) · 45 mph: 18 of 4,871 (0.37%) · 50 mph: 10 of 3,054 (0.327%) · 55 mph: 16 of 6,728 (0.238%) · 60 mph: 4 of 625 (0.64%) · 65 mph: 49 of 8,965 (0.547%)
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: massachusetts, MA
- Total crash records analyzed: 135,367
- Total persons involved: 315,124
- Total vehicles involved: 250,130
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: 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/statewide/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