Monthly Traffic Safety Analysis

43 CRASHES IN
HOPKINTON, MA
APRIL 2026

All metrics benchmarked againstApril 2025

Total crashes in April 2026 decreased to 43, a 12.2% reduction from the 49 crashes reported in April 2025. A notable shift is the absence of DUI and speeding-related crashes in the current period, compared to 2 DUI and 3 speeding crashes in the prior year.

43

▼ -12.2%was 49

Total Crash Events

0

Persons Killed

15

▼ -25.0%was 20

Persons Injured

4

▲ 33.3%was 3

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 · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for April 2026 shows a positive trend with a decrease in total crashes and injuries compared to April 2025. Total crashes fell by 12.2%, from 49 to 43, while total injuries decreased by 25%, from 20 to 15.

4

Hit-and-Run Crashes — April 2026

▲ 33.3% vs prior (3)

Hit-and-run crashes increased by 33.3% in count, from 3 in April 2025 to 4 in April 2026. Consequently, the hit-and-run rate rose from 6.1% to 9.3% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

15

Motorists Injured

Prior: 19↓-21.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Wednesday (11 crashes) in April 2025 to Tuesday (10 crashes) in April 2026. The peak crash hour also changed, moving from 4 PM (6 crashes) in the prior period to 9 AM (6 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either April 2025 or April 2026. Total injuries decreased from 20 in the prior period to 15 in the current period, representing a 25% reduction. The number of serious injuries increased from 0 to 1, while minor injuries decreased from 9 to 7, and possible injuries decreased from 10 to 7.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.3%
Minor Injury6minor injury crashes14%
↓-40.0%prior 10
Possible Injury4possible injury crashes9.3%
→0.0%prior 4
No Injury31no injury crashes72.1%
↓-6.1%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'Followed too closely,' remained stable at 10 crashes in both periods. 'No improper driving' crashes decreased by 41.7% in count, from 12 to 7, while 'Inattention' crashes decreased by 42.9% in count, from 7 to 4. Conversely, 'Failure to keep in proper lane or running off road' crashes doubled in count, from 2 to 4.

Officer-Reported Primary Contributing Cause

Followed too closely10 (23.3%)→0.0%prior 10
No improper driving7 (16.3%)↓-41.7%prior 12
Failure to keep in proper lane or running off road4 (9.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (9.3%)
Inattention4 (9.3%)↓-42.9%prior 7
Failed to yield right of way3 (7%)
Other improper action3 (7%)
Over-correcting/over-steering2 (4.7%)
Illness1 (2.3%)
Distracted1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased slightly from 33 to 35, while those in rainy conditions decreased by 50% in count, from 10 to 5. Crashes in dark conditions (lighted or not lighted) also saw a reduction, decreasing from 10 in the prior period to 5 in the current period.

Weather

Clear/Clear26 (60.5%)
↑30.0%prior 20
Clear9 (20.9%)
↓-30.8%prior 13
Rain/Cloudy3 (7.0%)
Cloudy/Rain2 (4.7%)
Cloudy/Fog, smog, smoke1 (2.3%)
Cloudy1 (2.3%)
Snow/Sleet, hail (freezing rain or drizzle)1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash

Lighting

Daylight36 (83.7%)
↑2.9%prior 35
Dark - lighted roadway4 (9.3%)
↓-33.3%prior 6
Dark - roadway not lighted1 (2.3%)
Dawn1 (2.3%)
Other1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field

Road Surface

Dry36 (83.7%)
→0.0%prior 36
Wet7 (16.3%)
↓-30.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field

Vehicles & Demographics

The number of persons aged 55-64 involved in crashes significantly decreased from 19 in April 2025 to 8 in April 2026. Among vehicle makes, SUBARU crashes increased by 4 in count, from 2 to 6, while HONDA crashes decreased by 3 in count, from 8 to 5.

Top Vehicle Makes (83 vehicles)

1
TOYOTA13 (15.7%)
↑8.3%prior 12
2
FORD11 (13.3%)
↑22.2%prior 9
3
CHEVROLET6 (7.2%)
↓-14.3%prior 7
4
SUBARU6 (7.2%)
5
HONDA5 (6%)
↓-37.5%prior 8
6
NISSAN4 (4.8%)
↓-20.0%prior 5
7
JEEP3 (3.6%)
8
GMC3 (3.6%)
9
BMW3 (3.6%)
10
TESL3 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Vehicle unit records

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

Sex Distribution (89 persons with recorded sex)

Male63 (70.8%)
↓-1.6%prior 64
Female26 (29.2%)
↓-38.1%prior 42

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Person-level records linked to crash events

Speed Limit Zones

There was a notable shift in crashes towards lower speed zones, with crashes in the 25 mph zone increasing by 400% in count, from 1 to 5. Conversely, crashes in the 65 mph zone decreased by 3 in count, from 13 to 10, and crashes in the 30 mph zone decreased by 2 in count, from 8 to 6.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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: 2026-04-01 through 2026-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2026-04-01 through 2026-04-30 (30 days)
  • Geographic scope: HOPKINTON, MA
  • Total crash records analyzed: 43
  • Total persons involved: 101
  • Total vehicles involved: 83

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). "HOPKINTON, MA Crash Intelligence Report: April 2026." Published June 21, 2026. Reporting period: 2026-04-01 to 2026-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hopkinton/april-2026-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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Hopkinton, MA Crash Report — April 2026 | ThatCarHitMe.com