ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MASSACHUSETTS, MA · DECEMBER 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/december-2023-report
Monthly Traffic Safety Analysis
12,322 CRASHES IN
MASSACHUSETTS, MA
DECEMBER 2023
In December 2023, there were 12,322 total crashes, a 6.1% decrease from the 13,125 crashes recorded in December 2022. While total fatalities also saw a slight decrease from 37 to 34, the number of persons injured increased by 1.6%. One of the most notable shifts was a dramatic reduction in crashes occurring on snow and ice, which fell from a combined 1,314 incidents in the prior period to 195 in the current period.
12,322
▼ -6.1%was 13,125
Total Crash Events
34
▼ -8.1%was 37
Persons Killed
3,652
▲ 1.6%was 3,593
Persons Injured
1,095
▲ 8.4%was 1,010
Hit-and-Run Crashes
Note: "Persons Killed" (34) counts individual fatalities across all crash events. "Fatal" in the severity table below (29) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 685 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year, total traffic crashes in Massachusetts decreased by 6.1%, from 13,125 in December 2022 to 12,322 in December 2023. While total fatalities also declined from 37 to 34, the number of persons injured saw a slight increase of 1.6% from 3,593 to 3,652.
1,095
Hit-and-Run Crashes — December 2023
▲ 8.4% vs prior (1,010)
Despite an overall decrease in total crashes, hit-and-run incidents increased year-over-year. The number of hit-and-run crashes rose by 8.4% from 1,010 in December 2022 to 1,095 in December 2023. Consequently, the hit-and-run rate, which is the proportion of all crashes that were hit-and-runs, trended upward from 7.7% to 8.9%.
Vulnerable Road User Casualties
8
Pedestrians Killed
1
Cyclists Killed
25
Motorists Killed
0
Other Killed
187
Pedestrians Injured
40
Cyclists Injured
3,411
Motorists Injured
14
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · 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 broadly consistent year-over-year. Friday was the peak day for crashes in both December 2023 (2,339 crashes) and December 2022 (2,401 crashes), and the 5 PM hour remained the peak time in both periods. However, there was a shift in the daily distribution, with Thursday crashes decreasing significantly from 2,160 in the prior period to 1,670 in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes decreased from 35 in December 2022 to 29 in December 2023, with their share of all crashes falling from 0.3% to 0.2%. The count and proportion of serious injury crashes also declined, from 204 (1.6% share) to 176 (1.4% share). Conversely, minor injury crashes saw an increase in both count, from 1,539 to 1,632, and their share of all crashes, from 11.7% to 13.2%.
Severity is per crash event (most severe injury). 29 fatal crash events resulted in 34 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors remained largely consistent, with 'Inattention' (1,536 crashes) and 'Failed to yield right of way' (1,372 crashes) being the most common after 'No improper driving'. The count of crashes attributed to 'Driving too fast for conditions' decreased significantly by 34.6%, from 552 to 361, causing it to drop from the 5th to the 7th most cited factor. In contrast, crashes involving 'Failure to keep in proper lane or running off road' increased in count from 539 to 580.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A significant year-over-year change occurred in road surface conditions at the time of crashes. Crashes on snow-covered roads plummeted from 825 in December 2022 to just 55 in December 2023, while crashes on icy roads fell from 489 to 140. Crashes in daylight conditions accounted for 48.5% of all incidents in December 2023, a slight increase in share from 47.2% in the prior year, while crashes on dark, lighted roadways decreased in count from 4,633 to 4,181.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The composition of vehicles involved in crashes showed little change year-over-year. Toyota (3,751 vehicles), Honda (2,938), and Ford (2,439) remained the top three most frequently involved vehicle makes in December 2023, consistent with the prior year's rankings. Similarly, the age distribution of persons involved in crashes was stable, with the 26-34 age group representing the largest cohort in both periods, accounting for 4,657 individuals in the current period compared to 4,937 in the prior period.
Top Vehicle Makes (22,644 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Vehicle unit records
2,915 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (25,039 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones remained similar, with 30 mph zones having the highest volume in both periods (3,360 in 2023 vs. 3,577 in 2022). The 65 mph zone recorded 7 fatal crashes in both December 2022 and December 2023. Notably, fatal crashes in 25 mph zones increased from 4 to 7 year-over-year, while fatal crashes in 35 mph zones decreased from 6 to 1.
Fatal crashes by zone: 15 mph: 1 of 183 (0.546%) · 25 mph: 7 of 2,336 (0.3%) · 30 mph: 3 of 3,360 (0.089%) · 35 mph: 1 of 1,702 (0.059%) · 40 mph: 3 of 940 (0.319%) · 45 mph: 3 of 456 (0.658%) · 50 mph: 1 of 301 (0.332%) · 55 mph: 2 of 615 (0.325%) · 65 mph: 7 of 797 (0.878%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 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: 2023-12-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-12-01 through 2023-12-31 (31 days)
- Geographic scope: massachusetts, MA
- Total crash records analyzed: 12,322
- Total persons involved: 28,353
- Total vehicles involved: 22,644
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 2023." Published June 21, 2026. Reporting period: 2023-12-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/december-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: 2023-12-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved