Monthly Traffic Safety Analysis

43 CRASHES IN
HOPKINTON, MA
JUNE 2022

All metrics benchmarked againstJune 2021

Total crashes remained stable at 43 in June 2022 and June 2021. However, hit-and-run crashes increased by 200%, from 1 to 3 incidents, marking the most notable year-over-year shift. Total injuries saw a slight decrease from 11 to 10.

43

Total Crash Events

0

Persons Killed

10

-9.1%was 11

Persons Injured

3

200.0%was 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. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes remained stable year-over-year, with 43 crashes reported in both June 2022 and June 2021. Total injuries decreased by 9.1%, from 11 to 10. Fatalities remained at zero in both periods.

3

Hit-and-Run Crashes — June 2022

200.0% vs prior (1)

Hit-and-run crashes increased significantly by 200%, rising from 1 incident in June 2021 to 3 in June 2022. Consequently, the hit-and-run rate increased from 2.3% to 7% year-over-year, indicating an upward trend.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

9

Motorists Injured

Prior: 11-18.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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 with 9 crashes in June 2021 to Thursday with 12 crashes in June 2022. The peak hour for crashes shifted from 4 PM in June 2021 to 1 PM in June 2022, with both hours recording 6 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either June 2022 or June 2021. Total injuries decreased by 9.1%, from 11 in June 2021 to 10 in June 2022. The proportion of minor injuries increased from 9.3% (4 crashes) to 18.6% (8 crashes), while serious injuries, which accounted for 2.3% (1 crash) in June 2021, were not reported in June 2022.

Outcome by Severity (Crash Events)

Minor Injury8minor injury crashes18.6%
100.0%prior 4
Possible Injury1possible injury crashes2.3%
-75.0%prior 4
No Injury32no injury crashes74.4%
3.2%prior 31

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record

Top Contributing Factors

The count of 'No improper driving' as a contributing factor increased from 12 to 13, an 8.3% rise year-over-year. Conversely, 'Followed too closely' decreased by 25%, from 8 incidents to 6. 'Failed to yield right of way' saw a 25% increase, rising from 4 to 5 crashes.

Officer-Reported Primary Contributing Cause

No improper driving13 (30.2%)8.3%prior 12
Followed too closely6 (14%)-25.0%prior 8
Failed to yield right of way5 (11.6%)
Inattention5 (11.6%)-16.7%prior 6
Failure to keep in proper lane or running off road3 (7%)
Driving too fast for conditions2 (4.7%)
Glare1 (2.3%)
Exceeded authorized speed limit1 (2.3%)
Distracted1 (2.3%)
Other improper action1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Clear weather conditions remained the most frequent, with 39 crashes in June 2022 compared to 33 in June 2021. The number of crashes occurring in rain increased from 2 to 3. Daylight conditions continued to dominate, accounting for 36 crashes in June 2022, a slight decrease from 37 in June 2021.

Weather

Clear32 (76.2%)
33.3%prior 24
Clear/Clear7 (16.7%)
-22.2%prior 9
Rain3 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash

Lighting

Daylight36 (83.7%)
-2.7%prior 37
Dark - lighted roadway2 (4.7%)
Dark - roadway not lighted2 (4.7%)
Dusk2 (4.7%)
Dawn1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field

Road Surface

Dry40 (93.0%)
2.6%prior 39
Wet3 (7.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes decreased by 8.2%, from 98 in June 2021 to 90 in June 2022. The 16-20 age group saw a 54.5% increase in persons involved, rising from 11 to 17, while the 35-44 age group increased by 56.3%, from 16 to 25. Conversely, the 55-64 age group experienced a 47.4% decrease in involvement, from 19 to 10 persons.

Top Vehicle Makes (75 vehicles)

1
TOYOTA11 (14.7%)
-21.4%prior 14
2
HONDA8 (10.7%)
33.3%prior 6
3
CHEVROLET8 (10.7%)
4
FORD7 (9.3%)
-12.5%prior 8
5
NISSAN5 (6.7%)
6
HYUNDAI5 (6.7%)
7
VOLVO3 (4%)
8
GMC2 (2.7%)
-66.7%prior 6
9
KIA2 (2.7%)
10
MITSUBISHI2 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records

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

Sex Distribution (85 persons with recorded sex)

Male45 (52.9%)
-16.7%prior 54
Female40 (47.1%)
5.3%prior 38

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 65 mph speed zones decreased by 27.8%, from 18 in June 2021 to 13 in June 2022. Conversely, crashes in 25 mph zones saw a substantial increase from 1 to 7, a 600% rise. Crashes in 30 mph zones decreased from 7 to 1, an 85.7% reduction.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-06-01 through 2022-06-30 (30 days)
  • Geographic scope: HOPKINTON, MA
  • Total crash records analyzed: 43
  • Total persons involved: 90
  • Total vehicles involved: 75

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: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hopkinton/june-2022-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 — June 2022 | ThatCarHitMe.com