Monthly Traffic Safety Analysis

38 CRASHES IN
HOPKINTON, MA
SEPTEMBER 2022

All metrics benchmarked againstSeptember 2021

Total crashes in HOPKINTON decreased from 42 in September 2021 to 38 in September 2022, representing a 9.5% reduction. The most significant year-over-year shift was a 75% decrease in total injuries, falling from 24 to 6. Neither period recorded any fatalities.

38

-9.5%was 42

Total Crash Events

0

Persons Killed

6

-75.0%was 24

Persons Injured

4

100.0%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 · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in HOPKINTON saw a decline year-over-year, with total incidents decreasing by 9.5% from 42 to 38. This reduction was accompanied by a substantial 75% decrease in total injuries, falling from 24 to 6.

4

Hit-and-Run Crashes — September 2022

100.0% vs prior (2)

Hit-and-run crashes doubled year-over-year, increasing from 2 incidents in September 2021 to 4 in September 2022. Consequently, the hit-and-run rate rose from 4.8% of all crashes in the prior period to 10.5% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 24-75.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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 10 incidents in September 2021 to Friday with 7 incidents in September 2022. Similarly, the peak hour for crashes moved from 2 PM to 4 PM, with both hours recording 7 incidents in their respective periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either September 2021 or September 2022. Total injuries decreased significantly by 75%, from 24 persons injured in the prior period to 6 in the current period. The proportion of crashes resulting in 'No Injury' increased from 59.5% to 89.5% year-over-year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.6%
-50.0%prior 2
Minor Injury1minor injury crashes2.6%
-88.9%prior 9
Possible Injury1possible injury crashes2.6%
-75.0%prior 4
No Injury34no injury crashes89.5%
36.0%prior 25

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'Followed too closely', decreased from 10 crashes in September 2021 to 6 crashes in September 2022. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' saw a notable decrease from 5 crashes to 1 crash. Conversely, 'Inattention' increased from 3 crashes to 4 crashes.

Officer-Reported Primary Contributing Cause

Followed too closely6 (15.8%)-40.0%prior 10
No improper driving5 (13.2%)-16.7%prior 6
Inattention4 (10.5%)
Failure to keep in proper lane or running off road3 (7.9%)
Failed to yield right of way3 (7.9%)
Other improper action2 (5.3%)
Disregarded traffic signs, signals, road markings2 (5.3%)
Distracted1 (2.6%)
Exceeded authorized speed limit1 (2.6%)
Fatigued/asleep1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on dry road surfaces decreased from 34 to 27, while those on wet surfaces increased from 7 to 10. The number of crashes in 'Dark - roadway not lighted' conditions tripled from 2 in September 2021 to 6 in September 2022. The proportion of crashes in clear weather conditions remained dominant in both periods.

Weather

Clear/Clear14 (37.8%)
Clear13 (35.1%)
-53.6%prior 28
Rain5 (13.5%)
Clear/Rain2 (5.4%)
Cloudy1 (2.7%)
Cloudy/Cloudy1 (2.7%)
Cloudy/Rain1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash

Lighting

Daylight28 (73.7%)
-6.7%prior 30
Dark - roadway not lighted6 (15.8%)
Dark - lighted roadway4 (10.5%)
-50.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field

Road Surface

Dry27 (73.0%)
-20.6%prior 34
Wet10 (27.0%)
42.9%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 87 to 68 year-over-year. The age group '0-15' was involved in 39 incidents in the prior period but was not represented in the current period's data. Toyota and Ford remained the top two vehicle makes involved, each with 12 vehicles in both periods.

Top Vehicle Makes (68 vehicles)

1
TOYOTA12 (17.6%)
0.0%prior 12
2
FORD12 (17.6%)
0.0%prior 12
3
HONDA7 (10.3%)
4
CHEVROLET4 (5.9%)
-50.0%prior 8
5
BMW4 (5.9%)
6
GMC2 (2.9%)
7
DODGE2 (2.9%)
8
JEEP2 (2.9%)
-75.0%prior 8
9
HYUNDAI2 (2.9%)
10
THMS2 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records

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

Sex Distribution (69 persons with recorded sex)

Male47 (68.1%)
-26.6%prior 64
Female22 (31.9%)
-60.0%prior 55

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone decreased from 19 incidents in September 2021 to 16 in September 2022. Crashes in the 45 mph speed zone also saw a decrease from 7 to 2 incidents. Conversely, crashes in the 40 mph speed zone increased slightly from 4 to 5 incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-09-01 through 2022-09-30 (30 days)
  • Geographic scope: HOPKINTON, MA
  • Total crash records analyzed: 38
  • Total persons involved: 77
  • Total vehicles involved: 68

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: September 2022." Published June 21, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hopkinton/september-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 — September 2022 | ThatCarHitMe.com