ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WARE, 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/ware/2024-annual-report
Yearly Traffic Safety Analysis
193 CRASHES IN
WARE, MA
2024
In 2024, Ware recorded 193 total traffic crashes, a 14.9% increase from the 168 crashes reported in 2023. Total injuries saw a slight rise from 37 to 41 year-over-year. The most significant change was the occurrence of one fatal crash in 2024, whereas none were recorded in the prior year.
193
▲ 14.9%was 168
Total Crash Events
1
Persons Killed
41
▲ 10.8%was 37
Persons Injured
4
▼ -42.9%was 7
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 5 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
Crash data for Ware indicates an upward trend in 2024 compared to the previous year. Total crashes increased by 14.9%, rising from 168 to 193. Similarly, the number of people injured in these incidents grew by 10.8% from 37 to 41, and one fatality was recorded in 2024 after zero in 2023.
4
Hit-and-Run Crashes — 2024
▼ -42.9% vs prior (7)
The incidence of hit-and-run crashes decreased in 2024 compared to the previous year. The total number of hit-and-run incidents fell from 7 in 2023 to 4 in 2024. Consequently, the hit-and-run rate, representing the percentage of total crashes that were hit-and-runs, dropped from 4.2% to 2.1%.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Motorists Killed
1
Pedestrians Injured
40
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. In 2024, Tuesday became the day with the most incidents, accounting for 41 crashes, a change from Friday which was the peak day in 2023 with 30 crashes. The peak hour for collisions also shifted slightly earlier, moving from the 5 p.m. hour in 2023 (18 crashes) to the 4 p.m. hour in 2024 (22 crashes).
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
In 2024, Ware experienced one fatal crash, resulting in a fatal crash rate of 0.52 per 100 crashes, up from zero fatal crashes in 2023. The proportion of crashes resulting in any form of injury decreased from 16.1% in 2023 to 14.5% in 2024. While the total number of injury-involved crashes was nearly identical (27 in 2023 vs. 28 in 2024), the count of serious injury crashes decreased from 4 to 1.
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 cited in crashes remained consistent year-over-year, with 'No improper driving,' 'Inattention,' and 'Failed to yield right of way' as the top three in both 2023 and 2024. The count of crashes attributed to 'No improper driving' increased from 65 to 80, while 'Inattention' held steady with 20 incidents in both periods. Crashes involving distraction increased from 4 to 7, while those linked to erratic or reckless operation decreased from 10 to 6.
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 majority of crashes in both years occurred in clear conditions on dry roads during daylight hours. In 2024, 70.5% of crashes happened in daylight, a proportion similar to the 69.6% recorded in 2023. There was an increase in the share of crashes on adverse road surfaces, which accounted for 22.3% of incidents in 2024 (43 crashes) compared to 19.0% in 2023 (32 crashes). This was driven primarily by an increase in crashes on snowy roads, which rose from 2 in 2023 to 17 in 2024.
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 vehicle makes involved in crashes remained largely consistent, with Ford, Chevrolet, and Toyota being the most common in both years; Ford (45 vehicles) narrowly surpassed Chevrolet (44 vehicles) for the top spot in 2024 after being second in 2023. An analysis of persons involved in crashes shows a shift in age demographics. The proportion of individuals in the 16-20 age group decreased from 11.7% of persons in 2023 to 8.3% in 2024, while the 26-34 age group's representation increased from 14.5% to 16.8%.
Top Vehicle Makes (331 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
23 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (383 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 speed zones shifted toward lower-speed areas in 2024. The number of incidents in zones with posted speed limits of 35 mph or less increased from 85 in 2023 to 111 in 2024. Conversely, crashes in zones with speed limits of 40 mph or higher decreased from 26 to 17. The single fatal crash recorded in 2024 occurred in a 45 mph zone.
Fatal crashes by zone: 45 mph: 1 of 7 (14.286%)
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: WARE, MA
- Total crash records analyzed: 193
- Total persons involved: 410
- Total vehicles involved: 331
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). "WARE, 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/ware/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