ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TEWKSBURY, 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/tewksbury/2023-annual-report
Yearly Traffic Safety Analysis
550 CRASHES IN
TEWKSBURY, MA
2023
In 2023, Tewksbury recorded 550 total vehicle crashes, a 14.9% decrease from the 646 crashes reported in 2022. During this period, total fatalities fell from two to one, and total injuries decreased from 149 to 136. The most significant year-over-year change was the reduction in pedestrian-involved incidents, which saw crashes drop from 7 to 3 and fatalities fall from two to zero.
550
▼ -14.9%was 646
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
136
▼ -8.7%was 149
Persons Injured
45
▼ -16.7%was 54
Hit-and-Run Crashes
Note: "Persons Killed" (1) 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. 10 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, traffic crashes in Tewksbury showed a downward trend from 2022 to 2023. The total number of crashes decreased by 14.9%, from 646 to 550. This decline was also reflected in crash outcomes, with total injuries falling by 8.7% from 149 to 136 and fatalities decreasing from two to one.
45
Hit-and-Run Crashes — 2023
▼ -16.7% vs prior (54)
Hit-and-run incidents saw a slight decrease from 2022 to 2023. The total number of hit-and-run crashes fell from 54 to 45. The hit-and-run rate, representing the percentage of total crashes that were hit-and-runs, also saw a marginal decline from 8.4% in 2022 to 8.2% in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
3
Pedestrians Injured
3
Cyclists Injured
130
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. While Friday remained the peak day for crashes in both years, the number of Friday crashes decreased from 118 to 104. The peak hour for collisions shifted from the 3 p.m. hour in 2022, which saw 63 crashes, to a three-way tie at the 2 p.m., 3 p.m., and 5 p.m. hours in 2023, each with 49 crashes.
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 improved year-over-year, with fatal crashes decreasing from two in 2022 to one in 2023. The number of serious injury crashes also fell from seven to five. While the count of minor injury crashes rose from 71 to 80, the number of possible injury crashes dropped from 40 to 26. Overall, the proportion of crashes resulting in no injury decreased slightly from 78.5% in 2022 to 77.8% in 2023.
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
The leading contributing factors for crashes shifted between 2022 and 2023. The count of crashes attributed to 'Inattention' dropped by 39.3% from 122 to 74, causing it to fall from the second to the third most common factor. 'Failed to yield right of way' rose to become the second-ranked factor, with its count holding steady at 86 crashes compared to 85 in the prior year. Notably, crashes attributed to 'Followed too closely' increased in count by 42.9%, from 35 in 2022 to 50 in 2023.
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
The environmental conditions under which crashes occurred saw some year-over-year changes. The proportion of crashes happening in daylight decreased from 68.1% of all crashes in 2022 to 64.5% in 2023, while the share on dark but lighted roadways increased from 17.8% to 20.7%. Similarly, the share of crashes on dry road surfaces fell from 77.9% to 75.8%, with a corresponding increase in the share of crashes on wet roads from 13.6% to 18.9%.
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 changed order between periods. Honda (165 vehicles) surpassed Toyota (158 vehicles) as the most common make in 2023; in 2022, Toyota led with 180 vehicles to Honda's 163. The 26-34 age group remained the largest cohort of persons involved in crashes in both years, though its count decreased from 225 to 211. The 16-20 age group saw a notable reduction in involvement, falling from 178 individuals in 2022 to 135 in 2023.
Top Vehicle Makes (1,048 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
90 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,197 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 distribution of crashes across speed zones remained relatively consistent, with the 35 mph zone accounting for the most incidents in both 2022 (263 crashes) and 2023 (230 crashes). In 2023, the sole fatal crash occurred in a 35 mph zone. This contrasts with 2022, where one fatality occurred in a 35 mph zone and another occurred in a 65 mph zone. Crashes in 65 mph zones increased from 75 to 87, though with no associated fatalities in 2023.
Fatal crashes by zone: 35 mph: 1 of 230 (0.435%)
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: TEWKSBURY, MA
- Total crash records analyzed: 550
- Total persons involved: 1,296
- Total vehicles involved: 1,048
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: 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/tewksbury/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