ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · FALL RIVER, MA · JULY 2023
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/fall-river/july-2023-report
Monthly Traffic Safety Analysis
272 CRASHES IN
FALL RIVER, MA
JULY 2023
In July 2023, FALL RIVER, MA experienced 272 total crashes, an 18.8% increase compared to the 229 crashes reported in July 2022. The most notable year-over-year shift was in hit-and-run incidents, which more than doubled from 12 crashes to 25 crashes, increasing the hit-and-run rate from 5.2% to 9.2%.
272
▲ 18.8%was 229
Total Crash Events
0
Persons Killed
136
▲ 29.5%was 105
Persons Injured
25
▲ 108.3%was 12
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. 15 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Total crashes in FALL RIVER, MA increased by 43, from 229 in July 2022 to 272 in July 2023, representing an 18.8% rise. This upward trend was also reflected in total injuries, which rose by 31 from 105 to 136, a 29.5% increase year-over-year.
25
Hit-and-Run Crashes — July 2023
▲ 108.3% vs prior (12)
Hit-and-run crashes increased significantly from 12 in July 2022 to 25 in July 2023, representing a 108.3% rise in count. The hit-and-run rate also increased from 5.2% of total crashes to 9.2% year-over-year, indicating an upward trend in these incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
9
Pedestrians Injured
2
Cyclists Injured
124
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Saturday, with 46 crashes in July 2022, to Monday, with 55 crashes in July 2023. Additionally, the peak hour for crashes moved from 3 PM, with 21 incidents in the prior period, to 4 PM, with 34 incidents in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both July 2022 and July 2023, indicating no change in this critical metric. The number of crashes resulting in serious injuries increased from 6 to 7, while minor injury crashes rose from 54 to 69, contributing to an overall increase of 31 total injuries.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to "Inattention" increased by 8, from 33 to 41, and "Failure to keep in proper lane or running off road" crashes rose by 10, from 14 to 24. Conversely, "Failed to yield right of way" crashes decreased by 5, from 27 to 22. "No improper driving" remained the most cited factor, increasing from 63 to 67 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather conditions increased by 9, from 180 to 189, and those under "Daylight" lighting conditions rose from 179 to 206. A notable shift was observed in crashes on "Wet" road surfaces, which saw a substantial increase of 19, rising from 3 in July 2022 to 22 in July 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 463 to 521 year-over-year. Toyota, Honda, and Ford continued to be the top three vehicle makes involved in crashes, all showing increases in counts. Among persons involved, the 16-20 age group saw a notable increase of 22 persons, from 36 to 58, and the 55-64 age group increased by 25 persons, from 37 to 62.
Top Vehicle Makes (521 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Vehicle unit records
119 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (513 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones experienced the largest increase, rising by 34 from 52 to 86. Crashes in 55 mph speed zones also increased by 7, from 5 to 12. There were no fatal crashes reported in any speed zone during either the current or prior period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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: 2023-07-01 through 2023-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-07-01 through 2023-07-31 (31 days)
- Geographic scope: FALL RIVER, MA
- Total crash records analyzed: 272
- Total persons involved: 660
- Total vehicles involved: 521
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). "FALL RIVER, MA Crash Intelligence Report: July 2023." Published June 21, 2026. Reporting period: 2023-07-01 to 2023-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fall-river/july-2023-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: 2023-07-01 – 2023-07-31
Generated: June 21, 2026 · All rights reserved