Monthly Traffic Safety Analysis

248 CRASHES IN
FALL RIVER, MA
JULY 2024

All metrics benchmarked againstJuly 2023

In July 2024, Fall River recorded 248 crashes, an 8.82% decrease from 272 crashes in July 2023. A notable shift is the increase in total fatalities from 0 to 1 during this period. Total injuries also decreased from 136 to 99 year-over-year.

248

▼ -8.8%was 272

Total Crash Events

1

Persons Killed

99

▼ -27.2%was 136

Persons Injured

36

▲ 44.0%was 25

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. 19 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in Fall River decreased by 8.82%, from 272 in July 2023 to 248 in July 2024. This reduction was accompanied by a decrease in total injuries, which fell from 136 to 99 year-over-year, though fatalities increased from 0 to 1.

36

Hit-and-Run Crashes — July 2024

▲ 44.0% vs prior (25)

Hit-and-run crashes increased from 25 in July 2023 to 36 in July 2024, representing an increase of 11 incidents. The hit-and-run rate also rose from 9.2% to 14.5% of all crashes year-over-year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Motorists Killed

Prior: 0→0.0%

0

Other Killed

Prior: 0→0.0%

5

Pedestrians Injured

Prior: 9↓-44.4%

93

Motorists Injured

Prior: 124↓-25.0%

1

Other Injured

Prior: 1→0.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Both July 2023 and July 2024 saw Monday as the peak day for crashes and 4 PM as the peak hour. However, the number of crashes occurring on Mondays decreased from 55 to 41, and crashes at 4 PM decreased from 34 to 27.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes increased from 0 in July 2023 to 1 in July 2024, resulting in a fatal crash rate of 0.4% in the current period. Serious injuries decreased from 7 to 5, and minor injuries decreased from 69 to 50. The proportion of crashes with no injury increased from 59.6% to 63.7%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
Serious Injury5serious injury crashes2%
↓-28.6%prior 7
Minor Injury50minor injury crashes20.2%
↓-27.5%prior 69
Possible Injury15possible injury crashes6%
↓-21.1%prior 19
No Injury158no injury crashes63.7%
↓-2.5%prior 162

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' increased from 67 to 83, a 23.9% increase in count, making it the most frequent factor in July 2024. Conversely, 'Inattention' crashes decreased from 41 to 26, a 36.6% decrease in count. 'Failed to yield right of way' crashes also decreased, from 22 to 15, a 31.8% reduction in count.

Officer-Reported Primary Contributing Cause

No improper driving83 (33.5%)↑23.9%prior 67
Inattention26 (10.5%)↓-36.6%prior 41
Failure to keep in proper lane or running off road17 (6.9%)↓-29.2%prior 24
Followed too closely15 (6%)↓-21.1%prior 19
Failed to yield right of way15 (6%)↓-31.8%prior 22
Other improper action13 (5.2%)↓-27.8%prior 18
Made an improper turn7 (2.8%)↓-22.2%prior 9
Disregarded traffic signs, signals, road markings5 (2%)→0.0%prior 5
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway5 (2%)→0.0%prior 5
Illness4 (1.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather decreased from 189 to 172, while those in rain decreased from 14 to 11. Similarly, crashes on dry road surfaces decreased from 247 to 227, and wet surface crashes decreased slightly from 22 to 21. Daylight crashes also saw a reduction, from 206 to 195.

Weather

Clear172 (69.9%)
↓-9.0%prior 189
Clear/Cloudy30 (12.2%)
↓-14.3%prior 35
Rain11 (4.5%)
↓-21.4%prior 14
Clear/Unknown10 (4.1%)
↑25.0%prior 8
Cloudy9 (3.7%)
↑28.6%prior 7
Clear/Other6 (2.4%)
↓-45.5%prior 11
Cloudy/Rain4 (1.6%)
Cloudy/Clear1 (0.4%)
Rain/Clear1 (0.4%)
Rain/Cloudy1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Weather condition at time of crash

Lighting

Daylight195 (78.6%)
↓-5.3%prior 206
Dark - lighted roadway41 (16.5%)
↓-10.9%prior 46
Dusk6 (2.4%)
↓-40.0%prior 10
Dark - roadway not lighted3 (1.2%)
Dawn2 (0.8%)
Dark - unknown roadway lighting1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Lighting condition field

Road Surface

Dry227 (91.5%)
↓-8.1%prior 247
Wet21 (8.5%)
↓-4.5%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Road surface condition field

Vehicles & Demographics

The number of persons involved in crashes aged 16-20 decreased from 58 to 35, and those aged 26-34 decreased from 116 to 99. Toyota remained the top vehicle make involved in crashes, with its count increasing from 70 to 81. Meanwhile, Honda and Ford vehicles involved in crashes decreased from 60 to 47 and 57 to 39, respectively.

Top Vehicle Makes (477 vehicles)

1
TOYOTA81 (17%)
↑15.7%prior 70
2
HONDA47 (9.9%)
↓-21.7%prior 60
3
FORD39 (8.2%)
↓-31.6%prior 57
4
NISSAN34 (7.1%)
↓-30.6%prior 49
5
CHEVROLET28 (5.9%)
↓-22.2%prior 36
6
HYUNDAI27 (5.7%)
↑12.5%prior 24
7
JEEP20 (4.2%)
↓-4.8%prior 21
8
KIA18 (3.8%)
→0.0%prior 18
9
DODGE13 (2.7%)
↓-31.6%prior 19
10
GMC12 (2.5%)
↓-25.0%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Vehicle unit records

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

Sex Distribution (467 persons with recorded sex)

Male249 (53.3%)
↓-13.8%prior 289
Female218 (46.7%)
↓-2.7%prior 224

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones slightly increased from 86 to 88, and this zone recorded 1 fatal crash in the current period, compared to 0 in the prior period. Crashes in 30 mph zones decreased from 122 to 110. Overall, the majority of crashes continued to occur in 25 mph and 30 mph speed zones across both periods.

Fatal crashes by zone: 25 mph: 1 of 88 (1.136%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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: 2024-07-01 through 2024-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-07-01 through 2024-07-31 (31 days)
  • Geographic scope: FALL RIVER, MA
  • Total crash records analyzed: 248
  • Total persons involved: 603
  • Total vehicles involved: 477

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 2024." Published June 21, 2026. Reporting period: 2024-07-01 to 2024-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fall-river/july-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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Fall River, MA Crash Report — July 2024 | ThatCarHitMe.com