ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BOSTON, MA · NOVEMBER 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/boston/november-2023-report
Monthly Traffic Safety Analysis
549 CRASHES IN
BOSTON, MA
NOVEMBER 2023
In November 2023, Boston experienced 549 total crashes, an increase of 12.27% compared to the 489 crashes reported in November 2022. This period saw a significant and concerning increase in fatalities, rising from 0 in the prior year to 2 in the current month. Total injuries also rose substantially, from 122 to 180, marking a 47.54% increase.
549
▲ 12.3%was 489
Total Crash Events
2
Persons Killed
180
▲ 47.5%was 122
Persons Injured
83
▲ 43.1%was 58
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 29 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a rise in crash incidents and severity year-over-year. Total crashes increased by 12.27%, from 489 to 549, and total injuries increased by 47.54%, from 122 to 180. Additionally, there was an increase in total fatalities from 0 to 2.
83
Hit-and-Run Crashes — November 2023
▲ 43.1% vs prior (58)
Hit-and-run crashes increased significantly year-over-year, rising from 58 incidents in November 2022 to 83 in November 2023, a 43.1% increase. Consequently, the hit-and-run rate also trended upwards, increasing from 11.9% to 15.1% of all crashes.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
16
Pedestrians Injured
3
Cyclists Injured
161
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Wednesday in both periods, with 103 crashes in November 2023 compared to 98 in November 2022. The peak hour for crashes also remained 5 PM, though the number of crashes at this hour decreased from 40 in November 2022 to 36 in November 2023. Notably, crashes on Thursdays saw a significant increase from 64 to 97, and Saturdays from 69 to 89.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution shows a concerning shift, with the fatal crash rate increasing from 0% in November 2022 to 0.18% in November 2023, reflecting an absolute increase of 1 fatal crash. Serious injury crashes increased from 5 to 7, while minor injury crashes rose from 66 to 94. Possible injury crashes also increased from 28 to 44, indicating a general increase across all injury severity categories.
Severity is per crash event (most severe injury). 1 fatal crash events resulted in 2 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors, 'No improper driving', 'Followed too closely', and 'Failed to yield right of way', remained the highest ranked, all increasing in count. 'No improper driving' crashes increased from 88 to 109, and 'Followed too closely' crashes rose from 58 to 64. 'Inattention' and 'Disregarded traffic signs, signals, road markings' saw substantial increases in count, rising from 16 to 34 and 18 to 33 respectively, leading to a change in their rankings. Conversely, 'Exceeded authorized speed limit' crashes decreased from 24 to 16, and 'Driving too fast for conditions' dropped from 18 to 12.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 344 to 416, while crashes in rainy conditions decreased from 67 to 43. The number of crashes on wet road surfaces also decreased, from 85 to 63. Crashes occurring during daylight hours increased from 198 to 235, and those in 'Dark - lighted roadway' conditions increased from 225 to 237.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field
Vehicles & Demographics
Toyota remained the most frequently involved vehicle make, increasing from 177 to 211 vehicles, while Honda remained stable at 153 vehicles. Ford saw a slight decrease in involvement, from 115 to 111 vehicles. The age distribution of persons involved in crashes showed increases across several groups, notably for those aged 26-34 (from 261 to 293) and 65+ (from 64 to 84).
Top Vehicle Makes (1,095 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records
191 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,103 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones increased from 184 to 204, with this zone reporting 1 fatal crash in the current period compared to none in the prior period. Crashes in 55 mph zones also increased from 51 to 61. There was a notable shift away from crashes in the highest speed zones, with no crashes reported in 60 mph or 65 mph zones in the current period, compared to 1 and 3 crashes respectively in the prior period.
Fatal crashes by zone: 25 mph: 1 of 204 (0.49%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-11-01 through 2023-11-30 (30 days)
- Geographic scope: BOSTON, MA
- Total crash records analyzed: 549
- Total persons involved: 1,306
- Total vehicles involved: 1,095
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). "BOSTON, MA Crash Intelligence Report: November 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/boston/november-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: 2023-11-01 – 2023-11-30
Generated: June 21, 2026 · All rights reserved