Monthly Traffic Safety Analysis

24 CRASHES IN
SOUTHBRIDGE, MA
JUNE 2025

All metrics benchmarked againstJune 2024

Total crashes in Southbridge decreased by 31.4% year-over-year, from 35 crashes in June 2024 to 24 crashes in June 2025. This period saw a notable reduction in hit-and-run incidents, which decreased by 66.7% from the prior year.

24

▼ -31.4%was 35

Total Crash Events

0

Persons Killed

13

▲ 30.0%was 10

Persons Injured

2

▼ -66.7%was 6

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 · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Southbridge showed a downward trend, decreasing from 35 incidents in June 2024 to 24 incidents in June 2025, representing a 31.4% reduction. While total crashes decreased, the number of injured persons increased from 10 to 13, a 30% rise, with no fatalities reported in either period.

2

Hit-and-Run Crashes — June 2025

▼ -66.7% vs prior (6)

Hit-and-run crashes decreased substantially year-over-year, from 6 incidents in June 2024 to 2 incidents in June 2025. This reduction resulted in the hit-and-run rate falling from 17.1% of all crashes in June 2024 to 8.3% in June 2025, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

13

Motorists Injured

Prior: 8↑62.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted year-over-year. In June 2025, the peak day for crashes was Saturday with 6 incidents, compared to Tuesday with 9 incidents in June 2024. The peak hour also changed, with 3 crashes occurring at 3 PM in June 2025, whereas 5 crashes occurred at 4 PM in June 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either period. In June 2025, there was 1 crash involving a serious injury, which was not present in June 2024. Crashes resulting in minor injuries decreased from 7 (20% share) in June 2024 to 3 (12.5% share) in June 2025, while possible injury crashes decreased from 2 (5.7% share) to 1 (4.2% share).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.2%
Minor Injury3minor injury crashes12.5%
↓-57.1%prior 7
Possible Injury1possible injury crashes4.2%
↓-50.0%prior 2
No Injury17no injury crashes70.8%
↓-26.1%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

The number of crashes attributed to 'No improper driving' decreased significantly from 11 in June 2024 to 4 in June 2025, a 63.6% reduction in count. 'Inattention' related crashes decreased from 6 to 5, a 16.7% reduction in count. 'Failed to yield right of way' crashes decreased from 3 to 2, a 33.3% reduction in count. 'Other improper action' and 'Driving too fast for conditions' appeared as contributing factors in June 2025 with 2 and 1 crash counts respectively, while they were not listed in June 2024.

Officer-Reported Primary Contributing Cause

Inattention5 (20.8%)↓-16.7%prior 6
No improper driving4 (16.7%)↓-63.6%prior 11
Failure to keep in proper lane or running off road3 (12.5%)
Failed to yield right of way2 (8.3%)
Other improper action2 (8.3%)
Made an improper turn1 (4.2%)
Followed too closely1 (4.2%)
History heart/epilepsy/fainting1 (4.2%)
Driving too fast for conditions1 (4.2%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Both periods were predominantly affected by 'Clear' weather conditions, accounting for 21 crashes in June 2025 and 31 in June 2024. Crashes occurring in 'Rain' conditions decreased from 2 in June 2024 to 0 in June 2025. Similarly, crashes on 'Wet' road surfaces decreased from 2 to 1. The proportion of crashes occurring during 'Daylight' decreased from 32 (91.4% share) in June 2024 to 19 (79.2% share) in June 2025.

Weather

Clear21 (91.3%)
↓-32.3%prior 31
Clear/Other1 (4.3%)
Cloudy1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight19 (82.6%)
↓-40.6%prior 32
Dark - lighted roadway3 (13.0%)
Dawn1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry22 (95.7%)
↓-33.3%prior 33
Wet1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (45 vehicles)

1
TOYOTA8 (17.8%)
→0.0%prior 8
2
FORD5 (11.1%)
↓-28.6%prior 7
3
NISSAN4 (8.9%)
↓-20.0%prior 5
4
CHEVROLET3 (6.7%)
5
JEEP3 (6.7%)
6
DODGE3 (6.7%)
7
MERCEDES-BENZ3 (6.7%)
8
BMW3 (6.7%)
9
ACURA2 (4.4%)
10
VOLVO1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

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

Sex Distribution (51 persons with recorded sex)

Male31 (60.8%)
→0.0%prior 31
Female20 (39.2%)
↑11.1%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes at the 25 mph speed limit remained the most frequent in both periods, decreasing slightly from 22 crashes in June 2024 to 21 crashes in June 2025. Crashes at 30 mph and 40 mph, which accounted for 6 and 3 incidents respectively in June 2024, were not reported in June 2025. Conversely, 1 crash occurred at a 45 mph speed limit in June 2025, a category not present in June 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: SOUTHBRIDGE, MA
  • Total crash records analyzed: 24
  • Total persons involved: 60
  • Total vehicles involved: 45

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: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/southbridge/june-2025-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 — June 2025 | ThatCarHitMe.com