ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HOPKINTON, MA · 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/hopkinton/2024-annual-report
Yearly Traffic Safety Analysis
536 CRASHES IN
HOPKINTON, MA
2024
In 2024, Hopkinton recorded 536 total crashes, a 5.1% increase from the 510 crashes reported in 2023. The most significant year-over-year change was the occurrence of two fatal crashes resulting in two fatalities in 2024, compared to zero in the prior year. The total number of injuries remained stable, with 138 in 2024 compared to 140 in 2023.
536
▲ 5.1%was 510
Total Crash Events
2
Persons Killed
138
▼ -1.4%was 140
Persons Injured
40
▼ -11.1%was 45
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 14 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes in Hopkinton increased by 5.1% from 510 in 2023 to 536 in 2024. While the number of reported injuries saw a slight decrease of 1.4% from 140 to 138, the city experienced two fatalities in 2024 after recording none in the previous year.
40
Hit-and-Run Crashes — 2024
▼ -11.1% vs prior (45)
Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. The count of hit-and-run crashes fell from 45 in 2023 to 40 in 2024. This corresponds to a drop in the hit-and-run rate from 8.8% of all crashes in the prior year to 7.5% in the current year, indicating a downward trend.
Vulnerable Road User Casualties
2
Motorists Killed
138
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Wednesday (95 incidents) in 2023 to Tuesday (94 incidents) in 2024. A more pronounced change occurred in the peak hour, which shifted from the 8 a.m. morning commute (53 crashes) in 2023 to the 3 p.m. afternoon period (63 crashes) in 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased in 2024, with two fatal crashes (0.4% of total) occurring compared to none in 2023. The count of serious injury crashes also rose from six to eight. Conversely, the proportion of minor injury crashes decreased from 12.9% of all crashes in 2023 to 9.3% in 2024, while the share of no-injury crashes increased from 78.4% to 79.5%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, with "Followed too closely" being the most cited improper driving action in both 2023 (95 crashes) and 2024 (103 crashes). The count for this factor increased by 8.4%. Crashes attributed to "Inattention" also grew from 55 to 59, and those involving "Failed to yield right of way" increased from 40 to 46. The top three rankings for improper driving actions were unchanged between the two periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across different lighting and road surface conditions remained largely stable year-over-year. In 2024, 72.8% of crashes occurred in daylight, nearly identical to the 72.2% in 2023. Similarly, crashes on dry roads accounted for 78.9% of the total in 2024 compared to 76.9% in the prior year, with the share of crashes on adverse road surfaces holding steady at approximately 21% for both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes were Toyota, Honda, and Ford in both years, though their order shifted. In 2024, Honda (123 vehicles) moved into the second position ahead of Ford (110 vehicles), while Toyota remained the most common make with 176 vehicles involved. Among persons involved in crashes, the 21-25 age group's representation increased from 9.3% of individuals in 2023 to 11.4% in 2024, while the 35-44 age group's share decreased from 21.1% to 19.5%.
Top Vehicle Makes (1,014 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
97 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,083 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 65 mph zones, the most frequent location for incidents in both years, increased from 167 in 2023 to 172 in 2024. One of the two fatal crashes in 2024 occurred in a 65 mph zone, whereas no fatalities were recorded in any specific speed zone in the prior year. Crashes in 30 mph zones also saw an increase from 69 to 77, while incidents in 40 mph zones decreased from 63 to 59.
Fatal crashes by zone: 65 mph: 1 of 172 (0.581%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: HOPKINTON, MA
- Total crash records analyzed: 536
- Total persons involved: 1,198
- Total vehicles involved: 1,014
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hopkinton/2024-annual-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved