ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MASSACHUSETTS, MA · 2022
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/2022-annual-report
Yearly Traffic Safety Analysis
134,419 CRASHES IN
MASSACHUSETTS, MA
2022
In 2022, Massachusetts recorded 134,419 total crashes, a 7.4% increase from the 125,168 crashes documented in 2021. This rise was accompanied by increases across most metrics, including a 6.6% rise in total injuries from 37,824 to 40,308. The most notable year-over-year shift was a significant increase in incidents involving vulnerable road users, with pedestrian-involved crashes rising by 23.8% and bicycle-involved crashes increasing by 26.6%.
134,419
▲ 7.4%was 125,168
Total Crash Events
434
▲ 4.8%was 414
Persons Killed
40,308
▲ 6.6%was 37,824
Persons Injured
10,516
▲ 17.6%was 8,939
Hit-and-Run Crashes
Note: "Persons Killed" (434) counts individual fatalities across all crash events. "Fatal" in the severity table below (412) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 10,902 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data from 2022 indicates a rising trend in traffic incidents compared to the previous year. Total crashes increased by 7.4%, from 125,168 in 2021 to 134,419 in 2022. This upward trend was also observed in crash outcomes, with total injuries rising by 6.6% and total fatalities increasing by 4.8%.
10,516
Hit-and-Run Crashes — 2022
▲ 17.6% vs prior (8,939)
Hit-and-run incidents increased significantly in both count and rate from 2021 to 2022. The total number of hit-and-run crashes rose by 17.6%, from 8,939 to 10,516. This outpaced the overall growth in crashes, causing the hit-and-run rate to climb from 7.1% of all crashes in 2021 to 7.8% in 2022, indicating a clear upward trend.
Vulnerable Road User Casualties
98
Pedestrians Killed
9
Cyclists Killed
327
Motorists Killed
0
Other Killed
1,575
Pedestrians Injured
1,037
Cyclists Injured
37,529
Motorists Injured
167
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained consistent between 2021 and 2022. Friday was the peak day for crashes in both years, with 21,886 incidents in 2022 compared to 20,102 in 2021. Similarly, the 4 PM hour was the peak time for crashes in both periods, accounting for 10,861 crashes in 2022 and 10,233 in 2021. The overall distribution of crashes by day and hour did not show any significant shifts, maintaining the established pattern of weekday afternoon peaks.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The distribution of crash severity remained largely stable year-over-year, despite an increase in the total number of crashes. Fatal crashes accounted for 0.3% of all incidents in both 2021 and 2022, though the absolute count rose from 393 to 412. The proportion of crashes resulting in any injury was nearly unchanged, shifting from 22.4% in 2021 to 22.2% in 2022. The proportion of no-injury crashes increased slightly from 68.5% to 69.4%.
Severity is per crash event (most severe injury). 412 fatal crash events resulted in 434 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The ranking of the top five contributing factors to crashes remained unchanged from 2021 to 2022. "Inattention" was the leading improper driving factor in both years, with the count of related crashes increasing by 4.5% from 17,518 to 18,306. Crashes attributed to "Failed to yield right of way" grew by 9.6% in count (from 12,045 to 13,196), and those involving "Followed too closely" increased by 7.9% in count (from 10,664 to 11,512). While the counts for these top factors rose, their respective shares of total crashes remained relatively stable.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes predominantly occurred in clear weather and on dry roads in both 2021 and 2022. The proportion of incidents happening during daylight hours was unchanged at approximately 67%. While the share of crashes on adverse road surfaces (wet, snow, ice) held steady around 20%, the number of crashes on icy roads more than doubled, increasing from 1,403 in 2021 to 2,895 in 2022. The percentage of crashes occurring in darkness also remained consistent year-over-year at about 28%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The demographic profile of vehicles and persons involved in crashes showed high consistency between 2021 and 2022. The top five vehicle makes involved in incidents were Toyota, Honda, Ford, Chevrolet, and Nissan in both years, with their rankings unchanged. The 26-34 age group represented the largest cohort of individuals involved in crashes in both periods. There was a minor shift in age distribution, with the share of involved persons aged 65 and older increasing slightly from 9.6% in 2021 to 10.0% in 2022.
Top Vehicle Makes (247,142 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
34,656 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (267,390 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones saw some shifts between 2021 and 2022. Crashes in 25 mph zones increased notably by 18.7%, from 20,522 to 24,368, though the fatal crash rate in this zone decreased from 0.234% to 0.205%. Conversely, crashes in 65 mph zones increased by 8.9% (from 7,913 to 8,614), and the fatal crash rate within this high-speed zone also rose from 0.645% to 0.697%. Higher speed zones continued to exhibit higher fatal crash rates compared to lower speed zones.
Fatal crashes by zone: 10 mph: 1 of 2,054 (0.049%) · 15 mph: 2 of 2,065 (0.097%) · 20 mph: 4 of 3,607 (0.111%) · 25 mph: 50 of 24,368 (0.205%) · 30 mph: 96 of 36,624 (0.262%) · 35 mph: 46 of 18,216 (0.253%) · 40 mph: 33 of 9,707 (0.34%) · 45 mph: 29 of 4,958 (0.585%) · 50 mph: 18 of 2,924 (0.616%) · 55 mph: 31 of 6,690 (0.463%) · 60 mph: 5 of 630 (0.794%) · 65 mph: 60 of 8,614 (0.697%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: massachusetts, MA
- Total crash records analyzed: 134,419
- Total persons involved: 306,201
- Total vehicles involved: 247,142
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved