ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LEXINGTON, 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/lexington/2023-annual-report
Yearly Traffic Safety Analysis
554 CRASHES IN
LEXINGTON, MA
2023
In 2023, Lexington recorded 554 total crashes, a 3.9% increase from the 533 crashes documented in 2022. Total injuries rose from 124 to 137, while total fatalities increased from one to two. A notable year-over-year shift was the 43.1% increase in crashes involving speeding, which rose from 51 incidents in 2022 to 73 in 2023.
554
▲ 3.9%was 533
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
137
▲ 10.5%was 124
Persons Injured
48
▲ 11.6%was 43
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. 13 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
Crash data for Lexington indicates a rising trend in collisions and their severity from 2022 to 2023. The total number of crashes increased by 3.9% from 533 to 554. Concurrently, total injuries increased by 10.5% from 124 to 137, and fatalities doubled from one to two.
48
Hit-and-Run Crashes — 2023
▲ 11.6% vs prior (43)
Hit-and-run crashes in Lexington trended upward from 2022 to 2023. The absolute number of hit-and-run incidents increased from 43 to 48. This rise also reflects an increase in the hit-and-run rate, which grew from 8.1% of all crashes in 2022 to 8.7% in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
5
Pedestrians Injured
8
Cyclists Injured
124
Motorists 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
The temporal distribution of crashes shifted between the two years, with the peak day for incidents moving from Wednesday (92 crashes) in 2022 to Tuesday (107 crashes) in 2023. The peak hour for collisions remained consistent at 8 a.m. for both periods, though the number of crashes during this hour increased from 47 to 52. Weekend crashes also saw an increase, with Sunday incidents rising from 40 to 51.
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
While the number of fatal crashes remained stable at one incident in both 2022 and 2023, the number of resulting fatalities doubled from one to two. The count of crashes involving serious injuries also doubled, increasing from 4 in 2022 to 8 in 2023, raising their share of total crashes from 0.8% to 1.4%. Crashes resulting in minor injuries increased from 64 to 69 incidents year-over-year.
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 · 2023-01-01 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
In 2023, 'Followed too closely' became the most cited contributing factor with 98 incidents, an 11.4% increase in count from 88 in 2022, overtaking 'No improper driving' which saw its count decrease from 109 to 89. The most significant change was a 69.4% increase in the count of crashes attributed to 'Driving too fast for conditions,' which rose from 36 to 61 incidents. The number of crashes due to inattention decreased from 61 to 51.
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
While most crashes in both years occurred in clear weather on dry roads, 2023 saw a higher number of incidents in adverse conditions compared to 2022. Crashes during rainy weather increased from 38 to 61, and collisions on wet road surfaces rose from 103 to 123. The proportion of crashes occurring in daylight remained stable, accounting for 69.1% of crashes in 2023 versus 70.7% in 2022.
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 vehicle makes involved in crashes were consistent, with Toyota (173 incidents) and Honda (128 incidents) leading in 2023, up from 170 and 116 respectively in 2022. An analysis of persons involved in crashes shows a notable increase in the 16-20 age group, which grew from 117 individuals in 2022 to 134 in 2023. Conversely, the number of persons in the 26-34 age group decreased from 210 to 184.
Top Vehicle Makes (981 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
77 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,029 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 55 mph speed zone continued to have the highest number of crashes, increasing from 221 incidents in 2022 to 232 in 2023. The single fatal crash of 2023 occurred in a 55 mph zone, a shift from 2022 when the fatal crash occurred in a 25 mph zone. Crashes in 25 mph zones saw a significant increase, rising from 54 incidents in 2022 to 76 in 2023.
Fatal crashes by zone: 55 mph: 1 of 232 (0.431%)
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: LEXINGTON, MA
- Total crash records analyzed: 554
- Total persons involved: 1,168
- Total vehicles involved: 981
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). "LEXINGTON, 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/lexington/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