ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SANDWICH, 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/sandwich/2024-annual-report
Yearly Traffic Safety Analysis
358 CRASHES IN
SANDWICH, MA
2024
In 2024, Sandwich recorded 358 total traffic crashes, a 15.1% increase from the 311 crashes reported in 2023. While overall collisions rose, the number of fatalities decreased from one in the prior year to zero in the current year. Total injuries remained relatively stable, increasing slightly from 82 to 86 persons injured.
358
▲ 15.1%was 311
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
86
▲ 4.9%was 82
Persons Injured
18
▲ 63.6%was 11
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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Sandwich trended upward year-over-year, with a 15.1% increase from 311 incidents in 2023 to 358 in 2024. Despite this rise in total collisions, the most severe outcomes decreased, as fatalities dropped to zero from one in the previous year. The total number of injuries saw a slight increase of 4.9%, from 82 to 86 persons injured.
18
Hit-and-Run Crashes — 2024
▲ 63.6% vs prior (11)
Hit-and-run incidents increased notably in both absolute numbers and as a proportion of total crashes. The number of hit-and-run crashes rose from 11 in 2023 to 18 in 2024, representing a 63.6% increase in count. The hit-and-run rate also trended upward, climbing from 3.5% of all crashes in the prior year to 5.0% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
2
Pedestrians Injured
1
Cyclists Injured
83
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 showed some shifts between the two years. While the 4 p.m. hour remained the peak time for collisions in both 2023 and 2024, the number of crashes during this hour increased from 28 to 39. The most frequent day for crashes changed from Wednesday (54 crashes) in 2023 to Friday (62 crashes) in 2024. Crashes during the 7 a.m. hour saw a notable decrease from 28 to 14 incidents.
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 outcomes improved year-over-year, with fatal crashes decreasing from one in 2023 to zero in 2024. The overall proportion of crashes resulting in any injury remained stable at approximately 20%. However, the number of serious injury crashes increased from 7 to 11, and their share of total crashes rose from 2.3% in 2023 to 3.1% in 2024.
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 shifted between the two periods. In 2023, 'Inattention' was the top factor, cited in 70 crashes, but it decreased to 66 crashes in 2024. 'No improper driving' became the most common factor in 2024, rising from 59 to 83 incidents. Notably, crashes attributed to 'Followed too closely' increased by 84.6% in count, from 26 incidents in 2023 to 48 in 2024. Crashes involving 'Exceeded authorized speed limit' also more than doubled, from 4 to 10.
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 conditions under which crashes occurred remained largely consistent year-over-year. In both 2023 and 2024, the majority of incidents happened during daylight hours (71.4% and 73.7% of crashes, respectively) and on dry road surfaces (75.6% and 84.6%). Crashes in unlit, dark conditions were unchanged, with 58 incidents recorded in each period. The number of crashes on wet roads decreased from 52 to 40, despite the overall increase in total crashes.
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
Toyota remained the most common vehicle make involved in crashes, with its count increasing from 96 in 2023 to 115 in 2024. While Ford was the second most frequent make in the prior year, it tied with Honda for second place in the current year, with 70 vehicles each. Demographically, the number of people aged 65+ involved in crashes saw a significant increase, rising from 100 to 147, making it a tie for the most represented age group along with the 26-34 group.
Top Vehicle Makes (655 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
41 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (809 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
The distribution of crashes across different speed zones remained consistent between 2023 and 2024. The 30 mph and 40 mph zones were the most frequent sites for collisions in both years, with 90 and 85 crashes respectively in 2023, compared to 88 and 83 in 2024. There was no significant shift in crashes toward higher or lower speed zones. Notably, the single fatal crash in 2023 occurred in a 40 mph zone, whereas 2024 recorded no fatalities in any speed zone.
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: SANDWICH, MA
- Total crash records analyzed: 358
- Total persons involved: 880
- Total vehicles involved: 655
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). "SANDWICH, 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/sandwich/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