ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TEWKSBURY, MA · DECEMBER 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/tewksbury/december-2024-report
Monthly Traffic Safety Analysis
71 CRASHES IN
TEWKSBURY, MA
DECEMBER 2024
In December 2024, TEWKSBURY experienced 71 crashes, an increase from 65 crashes in December 2023. This represents a 9.23% rise in total crash incidents year-over-year. The most notable shift was a 100% increase in hit-and-run crashes, rising from 5 in the prior period to 10 in the current period.
71
▲ 9.2%was 65
Total Crash Events
0
Persons Killed
15
▼ -16.7%was 18
Persons Injured
10
▲ 100.0%was 5
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. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash incidents in TEWKSBURY increased from 65 in December 2023 to 71 in December 2024, marking an upward trend of 9.23%. Despite the rise in total crashes, the number of total injuries decreased by 16.67%, from 18 to 15, while total fatalities remained at 0 in both periods.
10
Hit-and-Run Crashes — December 2024
▲ 100.0% vs prior (5)
Hit-and-run crashes increased substantially from 5 in December 2023 to 10 in December 2024, representing a 100% increase. The hit-and-run rate also rose from 7.7% of total crashes in the prior period to 14.1% in the current period, indicating an upward trend in such incidents.
Vulnerable Road User Casualties
0
Motorists Killed
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Friday in both periods, with 17 crashes in December 2024 compared to 16 in December 2023. The peak hour shifted from 6 PM with 8 crashes in the prior period to 5 PM with 12 crashes in the current period. Tuesday also saw an increase in crashes, rising from 10 to 14, while Saturday crashes decreased from 11 to 7.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either December 2023 or December 2024. The total number of injured persons decreased from 18 in the prior period to 15 in the current period. In December 2024, there was 1 serious injury crash, which was not present in the prior period's data. Minor injury crashes remained at 9 in both periods, while possible injury crashes decreased from 6 to 4.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'Failed to yield right of way' increased from 7 in December 2023 to 11 in December 2024, a 57.14% increase in count. Conversely, 'Followed too closely' crashes decreased from 7 to 4, a 42.86% decrease in count. 'Inattention' crashes saw a slight decrease from 9 to 8, while 'No improper driving' crashes increased from 17 to 19.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in snowy weather conditions increased significantly, from 0 in December 2023 to 10 in December 2024. Correspondingly, crashes on snow-covered road surfaces also rose from 0 to 9, and crashes on wet road surfaces increased from 14 to 20. The number of crashes in clear weather conditions slightly decreased from 39 to 37, while those on dry road surfaces decreased from 51 to 40.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 130 in December 2023 to 136 in December 2024. TOYOTA, which was the top make in the prior period with 23 vehicles, became the second most involved with 20 vehicles, while HONDA rose to the top with 22 vehicles. Crashes involving persons aged 35-44 increased from 20 to 30, whereas those involving persons aged 65+ decreased from 16 to 7.
Top Vehicle Makes (136 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records
15 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (132 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones increased from 14 in December 2023 to 20 in December 2024. Similarly, 35 mph zones saw an increase from 28 to 33 crashes year-over-year. In contrast, crashes in 65 mph speed zones decreased from 12 to 6, and 40 mph zones decreased from 6 to 4.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 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: 2024-12-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-12-01 through 2024-12-31 (31 days)
- Geographic scope: TEWKSBURY, MA
- Total crash records analyzed: 71
- Total persons involved: 148
- Total vehicles involved: 136
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). "TEWKSBURY, MA Crash Intelligence Report: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/tewksbury/december-2024-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: 2024-12-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved