Monthly Traffic Safety Analysis

22 CRASHES IN
UPTON, MA
JANUARY 2025

All metrics benchmarked againstJanuary 2024

In January 2025, Upton experienced 22 total crashes, an increase of 15.8% compared to the 19 crashes recorded in January 2024. Total injuries decreased by 50%, from 4 in the prior year to 2 in the current year, while fatalities remained at 0 for both periods. A notable shift is the emergence of 1 hit-and-run crash in January 2025, where none were recorded in January 2024.

22

▲ 15.8%was 19

Total Crash Events

0

Persons Killed

2

▼ -50.0%was 4

Persons Injured

1

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.

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, the number of crashes in Upton increased year-over-year, rising from 19 crashes in January 2024 to 22 crashes in January 2025, representing a 15.8% increase. Despite this rise in total crashes, the number of total injuries decreased by 50%, from 4 to 2, and no fatalities were reported in either period.

1

Hit-and-Run Crashes — January 2025

4.5% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

2

Motorists Injured

Prior: 4↓-50.0%

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 pattern of crashes shifted significantly year-over-year, with the peak crash day moving from Tuesday (5 crashes) in January 2024 to Saturday (9 crashes) in January 2025. The peak crash hour remained at 3 PM for both periods, but the number of crashes during this hour increased from 3 in January 2024 to 4 in January 2025.

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

Fatalities remained at 0 for both January 2024 and January 2025. Total injuries decreased from 4 in January 2024 to 2 in January 2025, a 50% reduction. The proportion of crashes resulting in any injury (Minor or Possible) decreased from 15.8% (3 crashes) in January 2024 to 9.1% (2 crashes) in January 2025.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes9.1%
↑100.0%prior 1
No Injury20no injury crashes90.9%
↑25.0%prior 16

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

Among contributing factors, 'No improper driving' increased by 2 crashes, from 3 in January 2024 to 5 in January 2025. 'Driving too fast for conditions' saw a decrease of 3 crashes, falling from 5 in January 2024 to 2 in January 2025. 'Failed to yield right of way' increased by 1 crash, from 1 to 2, and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' also increased by 1 crash, from 2 to 3.

Officer-Reported Primary Contributing Cause

No improper driving5 (22.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (13.6%)
Failed to yield right of way2 (9.1%)
Driving too fast for conditions2 (9.1%)↓-60.0%prior 5
Followed too closely2 (9.1%)
Glare1 (4.5%)
Exceeded authorized speed limit1 (4.5%)
Failure to keep in proper lane or running off road1 (4.5%)
Distracted1 (4.5%)
Other improper action1 (4.5%)

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 significantly from 7 in January 2024 to 15 in January 2025. Similarly, crashes on 'Dry' road surfaces more than doubled, rising from 6 to 12. Conversely, crashes in 'Dark - roadway not lighted' conditions decreased from 4 in January 2024 to 2 in January 2025, and crashes on 'Wet' road surfaces decreased from 4 to 2.

Weather

Clear15 (68.2%)
↑114.3%prior 7
Snow4 (18.2%)
Blowing sand, snow1 (4.5%)
Clear/Clear1 (4.5%)
Clear/Snow1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash

Lighting

Daylight13 (59.1%)
↑8.3%prior 12
Dark - lighted roadway3 (13.6%)
Dawn3 (13.6%)
Dark - roadway not lighted2 (9.1%)
Dark - unknown roadway lighting1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field

Road Surface

Dry12 (54.5%)
↑100.0%prior 6
Snow7 (31.8%)
↓-12.5%prior 8
Wet2 (9.1%)
Ice1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (33 vehicles)

1
TOYOTA7 (21.2%)
↑40.0%prior 5
2
HONDA4 (12.1%)
↓-20.0%prior 5
3
JEEP4 (12.1%)
4
RAM3 (9.1%)
5
FORD3 (9.1%)
6
NISSAN2 (6.1%)
7
FRHT1 (3%)
8
LEXUS1 (3%)
9
ACURA1 (3%)
10
PLSR1 (3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records

3 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (36 persons with recorded sex)

Male21 (58.3%)
↓-12.5%prior 24
Female15 (41.7%)
↑150.0%prior 6

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 30 mph zones saw a substantial increase, rising from 5 in January 2024 to 11 in January 2025. Conversely, crashes in 40 mph zones decreased from 5 to 2, and in 45 mph zones from 2 to 1. The number of crashes in 25 mph zones remained stable at 2 for both periods.

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: UPTON, MA
  • Total crash records analyzed: 22
  • Total persons involved: 39
  • Total vehicles involved: 33

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). "UPTON, 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/upton/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

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Upton, MA Crash Report — January 2025 | ThatCarHitMe.com