ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TYNGSBOROUGH, MA · JANUARY 2025
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/tyngsborough/january-2025-report
Monthly Traffic Safety Analysis
40 CRASHES IN
TYNGSBOROUGH, MA
JANUARY 2025
In January 2025, Tyngsborough experienced 40 crashes, a slight increase of 2.56% compared to the 39 crashes reported in January 2024. The most notable shift was a significant 71.43% increase in total injuries, rising from 7 to 12 year-over-year.
40
▲ 2.6%was 39
Total Crash Events
0
Persons Killed
12
▲ 71.4%was 7
Persons Injured
3
▲ 50.0%was 2
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Tyngsborough saw a modest increase of 2.56%, rising from 39 crashes in January 2024 to 40 crashes in January 2025. This slight uptick in crash frequency was accompanied by a substantial 71.43% increase in total injuries, indicating a worsening outcome despite a small change in crash volume.
3
Hit-and-Run Crashes — January 2025
▲ 50.0% vs prior (2)
Hit-and-run crashes increased by 1, from 2 incidents in January 2024 to 3 in January 2025. This represents an increase in the hit-and-run rate from 5.1% to 7.5% of all crashes year-over-year. The trend for hit-and-run incidents is upward for the reported period.
Vulnerable Road User Casualties
0
Motorists Killed
12
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year, with the peak day moving from Tuesday in January 2024 (8 crashes) to Friday in January 2025 (10 crashes). The peak crash hour also changed, occurring at 6 PM with 7 crashes in the prior period, but shifting to 5 PM with 4 crashes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero for both January 2024 and January 2025. While serious injuries remained constant at 1 crash in both periods, minor injury crashes increased from 2 (5.1% of crashes) in January 2024 to 6 (15% of crashes) in January 2025. Consequently, the proportion of no-injury crashes decreased from 87.2% to 77.5% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record
Top Contributing Factors
"No improper driving" decreased by 4 crashes, from 15 in January 2024 to 11 in January 2025, and "Inattention" also decreased by 4 crashes, from 12 to 8. Conversely, "Driving too fast for conditions" increased by 1 crash, from 2 to 3, and "Physical impairment" increased by 1 crash, from 1 to 2. The factor "Made an improper turn" was present in the prior period with 2 crashes but not recorded in the current period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased by 9, from 20 to 29, while those in cloudy conditions decreased by 5, from 7 to 2. Similarly, crashes on dry road surfaces rose by 8, from 22 to 30, and crashes in daylight conditions increased by 5, from 16 to 21. Conversely, crashes on wet road surfaces decreased by 4, from 6 to 2, and Dusk lighting conditions, present with 4 crashes in the prior period, were not recorded in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 12, from 64 in January 2024 to 76 in January 2025. The age groups 16-20 and 26-34 saw notable increases in persons involved, with the 16-20 group rising by 7 and the 26-34 group by 5. In terms of vehicle makes, HONDA vehicles involved in crashes increased by 7 (from 9 to 16), while FORD vehicles decreased by 7 (from 14 to 7).
Top Vehicle Makes (76 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records
9 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (89 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 15 mph speed limit zone increased by 4, from 3 in January 2024 to 7 in January 2025, and crashes in the 10 mph zone increased by 3, from 1 to 4. Conversely, crashes in the 30 mph speed limit zone decreased by 5, from 9 to 4. Notably, the prior period recorded 2 crashes at 5 mph and 3 crashes at 55 mph that were not present in the current period, while the current period recorded 2 crashes at 40 mph not present in the prior period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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: 2025-01-01 through 2025-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-01-31 (31 days)
- Geographic scope: TYNGSBOROUGH, MA
- Total crash records analyzed: 40
- Total persons involved: 99
- Total vehicles involved: 76
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). "TYNGSBOROUGH, MA Crash Intelligence Report: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/tyngsborough/january-2025-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: 2025-01-01 – 2025-01-31
Generated: June 21, 2026 · All rights reserved