ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MASSACHUSETTS, MA · DECEMBER 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/december-2022-report
Monthly Traffic Safety Analysis
13,125 CRASHES IN
MASSACHUSETTS, MA
DECEMBER 2022
In December 2022, there were 13,125 total crashes, a 12.5% increase from the 11,664 crashes recorded in December 2021. Despite the rise in total collisions, the number of fatalities decreased by 17.8%, from 45 in the prior period to 37 in the current period.
13,125
▲ 12.5%was 11,664
Total Crash Events
37
▼ -17.8%was 45
Persons Killed
3,593
▲ 10.6%was 3,250
Persons Injured
1,010
▲ 11.2%was 908
Hit-and-Run Crashes
Note: "Persons Killed" (37) counts individual fatalities across all crash events. "Fatal" in the severity table below (35) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 824 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume shows a rising trend year-over-year. Total crashes increased by 12.5% from 11,664 in December 2021 to 13,125 in December 2022. Similarly, the number of people injured rose by 10.6% from 3,250 to 3,593, while total fatalities decreased from 45 to 37.
1,010
Hit-and-Run Crashes — December 2022
▲ 11.2% vs prior (908)
The number of hit-and-run incidents increased from 908 in December 2021 to 1,010 in December 2022, representing an 11.2% rise in count. Despite this increase in the absolute number of events, the hit-and-run rate as a percentage of total crashes remained stable, moving from 7.8% to 7.7%. This indicates that the growth in hit-and-run crashes was proportional to the overall increase in collisions during the period.
Vulnerable Road User Casualties
8
Pedestrians Killed
2
Cyclists Killed
27
Motorists Killed
0
Other Killed
203
Pedestrians Injured
35
Cyclists Injured
3,348
Motorists Injured
7
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 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 showed a shift in the peak day of the week, moving from Thursday (2,137 crashes) in December 2021 to Friday (2,401 crashes) in December 2022. The peak hour for collisions remained consistent at 5 PM for both periods. However, the number of crashes during the 5 PM hour increased by 30.2%, from 1,127 to 1,467, reflecting the overall rise in crash volume.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution of crashes shifted slightly between the two periods. The proportion of fatal crashes decreased from 0.4% in December 2021 to 0.3% in December 2022, with the total number of fatal crashes falling from 44 to 35. The share of crashes resulting in any injury (serious, minor, or possible) remained relatively stable, moving from 20.9% to 20.3%. Consequently, the proportion of crashes with no reported injuries increased from 70.3% to 73.1% year-over-year.
Severity is per crash event (most severe injury). 35 fatal crash events resulted in 37 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, with 'Inattention', 'Failed to yield right of way', and 'Followed too closely' being the top three cited driver actions after 'No improper driving' in both periods. There was a notable increase in crashes attributed to 'Driving too fast for conditions,' for which the count rose by 48.0% from 373 incidents in December 2021 to 552 in December 2022. Crashes involving 'Inattention' also increased in count by 9.3% year-over-year, from 1,477 to 1,614.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in December 2022 occurred more frequently under adverse road and weather conditions compared to the prior year. The proportion of collisions on wet, snowy, or icy road surfaces increased from a combined 27.6% in December 2021 to 33.5% in December 2022. This corresponds with an increase in the share of crashes during rain (from 7.4% to 11.5%) and snow (from 2.5% to 5.3%).
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The composition of vehicles involved in crashes remained consistent year-over-year. The top five most frequently involved vehicle makes were Toyota, Honda, Ford, Chevrolet, and Nissan in both December 2022 and December 2021, with no change in their ranking. The age distribution of all persons involved in crashes also showed high stability, with the proportional share of each age group, such as the 26-34 bracket (16.6% vs. 16.8%), changing by less than one percentage point.
Top Vehicle Makes (24,065 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records
2,899 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (26,417 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones scaled proportionally with the overall increase in collisions, with no significant shift toward higher or lower speed limit areas. Crashes in 25-30 mph zones increased by 13.3%, and collisions in 55-65 mph zones rose by 13.2%, both in line with the total crash increase. However, the rate of fatal crashes within specific zones changed; for instance, the fatality rate in 30 mph zones decreased from 0.30% to 0.11%, while the rate in 65 mph zones increased from 0.74% to 0.85%.
Fatal crashes by zone: 25 mph: 4 of 2,401 (0.167%) · 30 mph: 4 of 3,577 (0.112%) · 35 mph: 6 of 1,839 (0.326%) · 40 mph: 4 of 1,000 (0.4%) · 45 mph: 3 of 487 (0.616%) · 55 mph: 4 of 634 (0.631%) · 60 mph: 1 of 60 (1.667%) · 65 mph: 7 of 824 (0.85%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 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: 2022-12-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-12-01 through 2022-12-31 (31 days)
- Geographic scope: massachusetts, MA
- Total crash records analyzed: 13,125
- Total persons involved: 29,678
- Total vehicles involved: 24,065
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: December 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/december-2022-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: 2022-12-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved