ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WAKEFIELD, MA · 2024
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/wakefield/2024-annual-report
Yearly Traffic Safety Analysis
485 CRASHES IN
WAKEFIELD, MA
2024
In Wakefield, total traffic crashes increased by 3.6% from 468 in 2023 to 485 in 2024. While total fatalities remained unchanged at two, and total injuries saw a slight decrease, the most notable year-over-year shift was a 150% increase in bicycle-involved crashes, which rose from 4 in the prior year to 10 in the current period.
485
▲ 3.6%was 468
Total Crash Events
2
Persons Killed
139
▼ -3.5%was 144
Persons Injured
42
▼ -26.3%was 57
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 19 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the data indicates a slight upward trend in the total number of crashes, which rose from 468 to 485 year-over-year. In contrast, the number of people injured in these incidents decreased by 3.5%, from 144 to 139. The number of fatalities held steady at two for both the current and prior years.
42
Hit-and-Run Crashes — 2024
▼ -26.3% vs prior (57)
Hit-and-run crashes saw a significant downward trend year-over-year. The total count of hit-and-run incidents decreased by 26.3%, from 57 in 2023 to 42 in 2024. The hit-and-run rate, which measures these incidents as a percentage of all crashes, also declined from 12.2% in the prior period to 8.7% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
6
Pedestrians Injured
7
Cyclists Injured
123
Motorists Injured
3
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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 slight shift between the two periods. In 2024, the peak day for crashes was Friday with 92 incidents, a change from the prior year when Thursday was the peak day with 77 incidents. The peak hour for crashes remained consistent, with the 5 p.m. hour having the highest frequency in both years, though the concentration of crashes in this hour increased from 41 in 2023 to 53 in 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes remained relatively stable year-over-year. Fatal crashes accounted for 0.4% of all incidents in both 2024 and 2023, with two fatal crashes recorded in each period. The proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) decreased from 23.3% in the prior year to 20.8% in the current year. Correspondingly, no-injury crashes increased their share from 69.2% to 74.8% of all incidents.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes showed some changes year-over-year. While "No improper driving" and "Inattention" remained the top two factors in both periods, "Followed too closely" moved into the third position in 2024 with 51 crashes, displacing "Failed to yield right of way" (49 crashes). The count of crashes attributed to "No improper driving" saw the largest increase, rising by 35.1% from 94 to 127 incidents. Crashes involving failure to yield the right of way decreased by 7.5% from 53 to 49.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in 2024 were more likely to occur in clear conditions compared to the previous year. The proportion of incidents happening in daylight increased from 68.6% to 70.1%, and those on dry road surfaces rose from 80.6% to 83.7%. Conversely, the share of crashes occurring on wet roads decreased from 15.2% in 2023 to 11.5% in 2024, and incidents during rainy weather also saw a proportional decline.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The vehicle makes most frequently involved in crashes shifted slightly, with Toyota (135 vehicles) overtaking Honda (116 vehicles) for the top spot in 2024, reversing their 2023 ranking. There was also a notable demographic shift among persons involved in crashes; the number of individuals aged 65 and older increased from 120 to 155. This resulted in the 65+ age group's share of total persons involved rising from 10.9% in the prior year to 13.3% in the current year.
Top Vehicle Makes (942 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
134 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,023 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes remained concentrated in lower speed zones in both periods, with the 30 mph zone seeing an increase from 222 crashes in 2023 to 243 in 2024. Incidents in the 55 mph zone saw a slight decrease from 129 to 125. All fatal crashes in both years occurred in the 30 mph speed zone, with two fatalities recorded in this zone for both 2023 and 2024.
Fatal crashes by zone: 30 mph: 2 of 243 (0.823%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: WAKEFIELD, MA
- Total crash records analyzed: 485
- Total persons involved: 1,163
- Total vehicles involved: 942
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). "WAKEFIELD, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wakefield/2024-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved