Monthly Traffic Safety Analysis

30 CRASHES IN
SOUTHBRIDGE, MA
APRIL 2024

All metrics benchmarked againstApril 2023

Total crashes in SOUTHBRIDGE, MA increased from 26 in April 2023 to 30 in April 2024, representing a 15.4% rise. The most notable shift was in total injuries, which increased from 0 in April 2023 to 9 in April 2024.

30

15.4%was 26

Total Crash Events

0

Persons Killed

9

Persons Injured

3

-40.0%was 5

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in SOUTHBRIDGE, MA showed an upward trend year-over-year. Total crashes increased by 15.4%, from 26 in April 2023 to 30 in April 2024. Total injuries also saw a significant increase, rising from 0 in April 2023 to 9 in April 2024, while total fatalities remained at 0 in both periods.

3

Hit-and-Run Crashes — April 2024

-40.0% vs prior (5)

Hit-and-run crashes decreased from 5 in April 2023 to 3 in April 2024. Consequently, the hit-and-run rate trended downward, falling from 19.2% of total crashes in April 2023 to 10% in April 2024.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

8

Motorists Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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 Sunday with 6 crashes in April 2023 to Thursday with 7 crashes in April 2024. The peak hour also changed, moving from 7 p.m. with 3 crashes in April 2023 to 3 p.m. with 4 crashes in April 2024, indicating a shift in peak activity times.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.3%
Minor Injury5minor injury crashes16.7%
No Injury23no injury crashes76.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record

Top Contributing Factors

Among common contributing factors, 'No improper driving' increased from 8 crashes in April 2023 to 9 crashes in April 2024. 'Other improper action' increased from 1 crash to 3 crashes, while 'Inattention' decreased significantly from 6 crashes to 1 crash. 'Failure to keep in proper lane or running off road' also decreased from 3 crashes to 1 crash year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving9 (30%)12.5%prior 8
Other improper action3 (10%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (6.7%)
Failure to keep in proper lane or running off road1 (3.3%)
Disregarded traffic signs, signals, road markings1 (3.3%)
Operating defective equipment1 (3.3%)
Inattention1 (3.3%)-83.3%prior 6
Driving too fast for conditions1 (3.3%)
Exceeded authorized speed limit1 (3.3%)
Failed to yield right of way1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In April 2024, 'Clear' weather conditions were associated with 23 crashes, a slight increase from 20 crashes in April 2023. Crashes occurring in 'Wet' road surface conditions increased from 1 in April 2023 to 4 in April 2024. For lighting, 'Daylight' crashes saw a minor increase from 21 to 22, while crashes in 'Dark - lighted roadway' doubled from 2 to 4.

Weather

Clear23 (76.7%)
15.0%prior 20
Sleet, hail (freezing rain or drizzle)2 (6.7%)
Clear/Other1 (3.3%)
Rain/Sleet, hail (freezing rain or drizzle)1 (3.3%)
Sleet, hail (freezing rain or drizzle)/Snow1 (3.3%)
Rain1 (3.3%)
Clear/Cloudy1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash

Lighting

Daylight22 (73.3%)
4.8%prior 21
Dark - lighted roadway4 (13.3%)
Dawn2 (6.7%)
Dark - roadway not lighted1 (3.3%)
Dark - unknown roadway lighting1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field

Road Surface

Dry23 (76.7%)
-4.2%prior 24
Wet4 (13.3%)
Ice1 (3.3%)
Sand, mud, dirt, oil, gravel1 (3.3%)
Slush1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (51 vehicles)

1
FORD9 (17.6%)
28.6%prior 7
2
TOYOTA8 (15.7%)
14.3%prior 7
3
NISSAN4 (7.8%)
4
JEEP4 (7.8%)
5
SUBARU2 (3.9%)
6
LEXUS2 (3.9%)
7
DODGE2 (3.9%)
8
HYUNDAI2 (3.9%)
9
INFI2 (3.9%)
10
RAM2 (3.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records

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

Sex Distribution (50 persons with recorded sex)

Male30 (60.0%)
87.5%prior 16
Female20 (40.0%)
-4.8%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 25 mph speed zones increased from 12 in April 2023 to 18 in April 2024. Conversely, crashes in 30 mph zones decreased from 9 to 6. There were no recorded fatalities in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-04-01 through 2024-04-30 (30 days)
  • Geographic scope: SOUTHBRIDGE, MA
  • Total crash records analyzed: 30
  • Total persons involved: 58
  • Total vehicles involved: 51

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). "SOUTHBRIDGE, MA Crash Intelligence Report: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/southbridge/april-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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Southbridge, MA Crash Report — April 2024 | ThatCarHitMe.com