Monthly Traffic Safety Analysis

42 CRASHES IN
HOPKINTON, MA
OCTOBER 2022

All metrics benchmarked againstOctober 2021

In October 2022, the city of HOPKINTON experienced 42 total crashes, a notable increase from the 26 crashes reported in October 2021. This represents a 61.5% rise in overall crash incidents year-over-year. The most significant shift was the substantial increase in total crashes, coupled with a rise in hit-and-run incidents.

42

61.5%was 26

Total Crash Events

0

Persons Killed

7

-12.5%was 8

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Total crashes in HOPKINTON increased from 26 in October 2021 to 42 in October 2022. This represents a 61.5% increase, indicating a clear upward trend in crash frequency year-over-year.

3

Hit-and-Run Crashes — October 2022

200.0% vs prior (1)

The number of hit-and-run crashes increased from 1 in October 2021 to 3 in October 2022. This resulted in the hit-and-run rate rising from 3.8% of total crashes in the prior period to 7.1% in the current period, indicating an upward trend in such incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 8-12.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · 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 Friday in October 2021, which recorded 12 incidents, to Wednesday in October 2022, with 9 incidents. Similarly, the peak crash hour moved from 4 p.m. with 4 crashes in the prior period to 6 a.m. with 6 crashes in the current period, suggesting a change in daily crash patterns.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Neither October 2021 nor October 2022 reported any fatalities or fatal crashes. Total injuries decreased slightly from 8 in October 2021 to 7 in October 2022, despite the overall increase in crash volume. The prior period included 2 serious injuries (7.7% of crashes), while the current period reported no serious injuries, with minor injuries accounting for 7.1% and possible injuries for 4.8% of crashes.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes7.1%
50.0%prior 2
Possible Injury2possible injury crashes4.8%
0.0%prior 2
No Injury37no injury crashes88.1%
85.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'No improper driving' increased from 6 crashes in October 2021 to 9 crashes in October 2022. 'Followed too closely' also rose from 5 crashes to 7 crashes, while 'Inattention' decreased from 5 crashes to 3 crashes. 'Fatigued/asleep' emerged with 3 crashes in October 2022, whereas it was not a top factor in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving9 (21.4%)50.0%prior 6
Followed too closely7 (16.7%)40.0%prior 5
Inattention3 (7.1%)-40.0%prior 5
Fatigued/asleep3 (7.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (4.8%)
Failed to yield right of way2 (4.8%)
Failure to keep in proper lane or running off road2 (4.8%)
Driving too fast for conditions2 (4.8%)
Other improper action2 (4.8%)
Made an improper turn1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 19 in October 2021 to 28 in October 2022. Incidents on wet road surfaces saw a notable rise from 5 in the prior period to 13 in the current period. Crashes during daylight hours increased from 15 to 28, while those in dark conditions remained constant at 9 crashes.

Weather

Clear22 (53.7%)
29.4%prior 17
Clear/Clear6 (14.6%)
Cloudy6 (14.6%)
Rain/Fog, smog, smoke2 (4.9%)
Rain2 (4.9%)
-60.0%prior 5
Rain/Cloudy2 (4.9%)
Cloudy/Rain1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Weather condition at time of crash

Lighting

Daylight28 (66.7%)
86.7%prior 15
Dark - roadway not lighted4 (9.5%)
-20.0%prior 5
Dark - unknown roadway lighting3 (7.1%)
Dawn3 (7.1%)
Dark - lighted roadway2 (4.8%)
Dusk2 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Lighting condition field

Road Surface

Dry28 (68.3%)
33.3%prior 21
Wet13 (31.7%)
160.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (77 vehicles)

1
TOYOTA11 (14.3%)
57.1%prior 7
2
FORD8 (10.4%)
60.0%prior 5
3
JEEP7 (9.1%)
4
HONDA7 (9.1%)
-22.2%prior 9
5
CHEVROLET6 (7.8%)
6
HYUNDAI5 (6.5%)
7
SUBARU4 (5.2%)
8
NISSAN4 (5.2%)
9
AUDI3 (3.9%)
10
BMW3 (3.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Vehicle unit records

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

Sex Distribution (83 persons with recorded sex)

Male50 (60.2%)
28.2%prior 39
Female33 (39.8%)
0.0%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 65 mph speed zones increased from 12 in October 2021 to 15 in October 2022. Conversely, crashes in the 40 mph zone decreased from 8 to 3 year-over-year. New crash occurrences were observed in the 15 mph (2 crashes) and 25 mph (4 crashes) zones in October 2022, which had no reported crashes in the prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · 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: 2022-10-01 through 2022-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-10-01 through 2022-10-31 (31 days)
  • Geographic scope: HOPKINTON, MA
  • Total crash records analyzed: 42
  • Total persons involved: 87
  • Total vehicles involved: 77

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: October 2022." Published June 21, 2026. Reporting period: 2022-10-01 to 2022-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hopkinton/october-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 — October 2022 | ThatCarHitMe.com