ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONCORD, 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/concord/2023-annual-report
Yearly Traffic Safety Analysis
399 CRASHES IN
CONCORD, MA
2023
In 2023, Concord experienced 399 total crashes, an 11.8% increase from the 357 crashes recorded in 2022. While fatalities remained at zero in both years, total injuries rose from 114 to 124. The most notable year-over-year shift was the doubling of crashes resulting in serious injuries, which increased from 3 to 6.
399
▲ 11.8%was 357
Total Crash Events
0
Persons Killed
124
▲ 8.8%was 114
Persons Injured
27
▲ 68.8%was 16
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 8 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
Overall crash trends in Concord show an increase from 2022 to 2023. Total crashes rose by 11.8%, from 357 to 399. Similarly, the number of people injured in these incidents increased by 8.8%, from 114 to 124, though no fatalities were recorded in either year.
27
Hit-and-Run Crashes — 2023
▲ 68.8% vs prior (16)
Hit-and-run incidents increased significantly in 2023 compared to the prior year. The total count of hit-and-run crashes rose from 16 to 27, a year-over-year increase of 68.8%. This pushed the hit-and-run rate, as a percentage of total crashes, from 4.5% in 2022 to 6.8% in 2023, indicating an upward trend for this crash type.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
5
Pedestrians Injured
5
Cyclists Injured
114
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 patterns of crashes showed some shifts between 2022 and 2023. The peak day for crashes moved from Tuesday (68 crashes) in 2022 to a tie between Thursday and Friday (70 crashes each) in 2023. While the 3 PM hour remained the busiest time in both years, the number of crashes during that hour increased from 34 to 40.
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
Crash severity saw a notable change in 2023, despite fatalities remaining at zero for both years. The number of crashes classified as causing a 'Serious Injury' doubled, increasing from 3 in 2022 to 6 in 2023. This raised the serious injury crash share from 0.8% to 1.5% of all crashes. The counts of minor and possible injury crashes also rose, from 66 to 70 and 17 to 20, respectively.
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
An analysis of contributing factors shows shifts in behaviors cited in crashes. Crashes attributed to an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' saw an 81.8% increase in count, rising from 11 to 20 incidents. Similarly, crashes involving 'Failed to yield right of way' increased by 42.3% in count (from 26 to 37 incidents). Conversely, crashes citing 'Inattention' as a factor decreased in count from 58 to 54.
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
Environmental conditions at the time of crashes remained largely consistent between 2022 and 2023. In both years, the majority of crashes occurred in daylight (71.2% in 2023 vs. 73.1% in 2022) and on dry roads (81.2% in 2023 vs. 79.6% in 2022). There was a slight increase in the number of crashes occurring on dark but lighted roadways, which rose from 49 incidents in 2022 to 63 in 2023.
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 number of vehicles involved in crashes increased from 654 in 2022 to 726 in 2023. The most common vehicle makes remained consistent, with Toyota, Ford, and Honda leading in both periods. Analysis of all persons involved shows notable demographic shifts, with a 60% increase in individuals aged 0-15 (from 35 to 56) and a 40% increase in those aged 35-44 (from 100 to 140).
Top Vehicle Makes (726 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
79 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (743 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
Crashes shifted between different speed zones from 2022 to 2023. There was a significant increase in crashes occurring in 35 mph zones, which rose by 74.1% from 27 to 47 incidents. Crashes in 25 mph zones also increased notably by 37.8%, from 82 to 113. Conversely, the number of crashes in 45 mph zones decreased by 19.5%, from 77 to 62. No fatal crashes were recorded in any speed zone during either period.
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: CONCORD, MA
- Total crash records analyzed: 399
- Total persons involved: 861
- Total vehicles involved: 726
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). "CONCORD, 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/concord/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