Monthly Traffic Safety Analysis

46 CRASHES IN
HOPKINTON, MA
AUGUST 2024

All metrics benchmarked againstAugust 2023

Total crashes in HOPKINTON, MA increased by 7.0% from 43 in August 2023 to 46 in August 2024. Total injuries also rose by 37.5%, from 8 to 11. A significant shift was observed in contributing factors, with 'Followed too closely' crashes increasing by 142.9%.

46

7.0%was 43

Total Crash Events

0

Persons Killed

11

37.5%was 8

Persons Injured

4

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 · 2024-08-01 to 2024-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for HOPKINTON, MA shows an upward trend year-over-year. Total crashes increased from 43 to 46, representing a 7.0% rise. Concurrently, the total number of injuries increased by 37.5%, from 8 to 11, indicating a worsening outcome for those involved in crashes.

4

Hit-and-Run Crashes — August 2024

0.0% vs prior (4)

The number of hit-and-run crashes remained constant at 4 in both August 2023 and August 2024. However, the hit-and-run rate decreased slightly from 9.3% to 8.7% due to an increase in the overall number of crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

11

Motorists Injured

Prior: 837.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Thursday in both periods, increasing from 10 crashes in August 2023 to 12 in August 2024. The peak hour also remained consistent at 3 PM, with 6 crashes in both periods. Notable shifts include Wednesday crashes doubling from 6 to 12, and Saturday crashes decreasing from 4 to 0.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either August 2023 or August 2024. The number of serious injury crashes remained stable at 1 for both periods. While minor injury crashes decreased from 5 to 4, possible injury crashes increased from 1 to 2, and crashes with no injuries increased from 35 to 39.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.2%
0.0%prior 1
Minor Injury4minor injury crashes8.7%
-20.0%prior 5
Possible Injury2possible injury crashes4.3%
100.0%prior 1
No Injury39no injury crashes84.8%
11.4%prior 35

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor shifted from 'Failed to yield right of way' (8 crashes) in August 2023 to 'Followed too closely' (17 crashes) in August 2024. Crashes attributed to 'Followed too closely' increased by 10, a 142.9% rise in count, and its share of crashes grew from 16.3% to 37.0%. Conversely, 'Failed to yield right of way' crashes decreased by 7, an 87.5% reduction in count, dropping its share from 18.6% to 2.2%.

Officer-Reported Primary Contributing Cause

Followed too closely17 (37%)142.9%prior 7
No improper driving7 (15.2%)0.0%prior 7
Inattention3 (6.5%)
Fatigued/asleep3 (6.5%)
Made an improper turn2 (4.3%)
Driving too fast for conditions2 (4.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (4.3%)
Other improper action2 (4.3%)
Failed to yield right of way1 (2.2%)-87.5%prior 8
Over-correcting/over-steering1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' or 'Clear/Clear' weather conditions increased from 26 in August 2023 to 36 in August 2024. Concurrently, crashes during 'Rain' or 'Cloudy/Rain' conditions decreased from 8 to 3. Regarding road surface, crashes on dry roads increased from 30 to 40, while those on wet surfaces decreased from 12 to 5.

Weather

Clear29 (64.4%)
26.1%prior 23
Clear/Clear7 (15.6%)
Cloudy4 (8.9%)
-20.0%prior 5
Rain2 (4.4%)
Rain/Cloudy1 (2.2%)
Cloudy/Cloudy1 (2.2%)
Cloudy/Rain1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Weather condition at time of crash

Lighting

Daylight36 (80.0%)
16.1%prior 31
Dark - roadway not lighted4 (8.9%)
-33.3%prior 6
Dusk4 (8.9%)
Dark - lighted roadway1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Lighting condition field

Road Surface

Dry40 (88.9%)
33.3%prior 30
Wet5 (11.1%)
-58.3%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 74 to 85 year-over-year. Toyota became the most frequently involved make, increasing from 11 to 13, surpassing Honda which decreased from 11 to 10. The age groups 35-44 and 45-54 saw decreases in persons involved by 5 and 4 respectively, while male involvement increased by 9 (16.4%) and female involvement decreased by 9 (23.1%).

Top Vehicle Makes (85 vehicles)

1
TOYOTA13 (15.3%)
18.2%prior 11
2
HONDA10 (11.8%)
-9.1%prior 11
3
FORD9 (10.6%)
12.5%prior 8
4
HYUNDAI5 (5.9%)
5
JEEP5 (5.9%)
6
CHEVROLET5 (5.9%)
7
NISSAN4 (4.7%)
-20.0%prior 5
8
RAM3 (3.5%)
9
FREIGHTLINER3 (3.5%)
10
GMC3 (3.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Vehicle unit records

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

Sex Distribution (94 persons with recorded sex)

Male64 (68.1%)
16.4%prior 55
Female30 (31.9%)
-23.1%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone saw a substantial increase, rising from 9 in August 2023 to 19 in August 2024. Conversely, crashes in the 40 mph zone decreased significantly from 8 to 2. There was also an increase in crashes at 55 mph (from 1 to 5) and 25 mph (from 2 to 4), indicating a shift towards crashes occurring in both higher and some lower speed zones.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · 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: 2024-08-01 through 2024-08-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-08-01 through 2024-08-31 (31 days)
  • Geographic scope: HOPKINTON, MA
  • Total crash records analyzed: 46
  • Total persons involved: 104
  • Total vehicles involved: 85

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: August 2024." Published June 21, 2026. Reporting period: 2024-08-01 to 2024-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hopkinton/august-2024-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 — August 2024 | ThatCarHitMe.com