Monthly Traffic Safety Analysis

54 CRASHES IN
SOUTHBRIDGE, MA
JANUARY 2024

All metrics benchmarked againstJanuary 2023

Total crashes in January 2024 were 54, a substantial increase compared to 29 crashes in January 2023. This 86.2% rise was accompanied by an increase in total injuries from 5 to 12, while fatalities remained at zero. The most notable shift was the overall increase in crash incidents and associated injuries.

54

86.2%was 29

Total Crash Events

0

Persons Killed

12

140.0%was 5

Persons Injured

5

150.0%was 2

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. 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 2024-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Southbridge, MA, showed a significant upward trend year-over-year for January. Total crashes increased by 86.2%, from 29 in January 2023 to 54 in January 2024. This increase also saw total injuries more than double, rising from 5 to 12 during the same period.

5

Hit-and-Run Crashes — January 2024

150.0% vs prior (2)

Hit-and-run crashes increased from 2 incidents in January 2023 to 5 incidents in January 2024. The hit-and-run rate also rose from 6.9% to 9.3% of all crashes year-over-year. This indicates an upward trend in hit-and-run incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

12

Motorists Injured

Prior: 4200.0%

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

When Crashes Happen

In January 2024, crashes were most frequent on Sundays, Mondays, and Tuesdays, each with 11 incidents, and the peak hour was 1 PM with 6 crashes. This differs from January 2023, where Thursday was the peak day with 9 crashes and 5 PM was the peak hour with 7 crashes. The temporal distribution of crashes shifted across days of the week and peak times.

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

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

Crash Severity Breakdown

Fatalities remained at zero in both January 2023 and January 2024. Total injuries increased by 140%, from 5 in the prior period to 12 in the current period. Notably, serious injuries, coded as 'A', increased from 0 in January 2023 to 1 in January 2024.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.9%
Minor Injury8minor injury crashes14.8%
100.0%prior 4
No Injury40no injury crashes74.1%
66.7%prior 24

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

“No improper driving” remained the most cited factor, increasing from 11 crashes in January 2023 to 14 in January 2024. “Inattention” saw a significant increase, rising from 2 crashes to 10 crashes year-over-year. Conversely, crashes where “Failed to yield right of way” was a factor decreased from 6 to 2 incidents.

Officer-Reported Primary Contributing Cause

No improper driving14 (25.9%)27.3%prior 11
Inattention10 (18.5%)
Failure to keep in proper lane or running off road5 (9.3%)
Driving too fast for conditions4 (7.4%)
Failed to yield right of way2 (3.7%)-66.7%prior 6
Other improper action2 (3.7%)
Visibility obstructed2 (3.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.9%)
Distracted1 (1.9%)
Over-correcting/over-steering1 (1.9%)

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

Road & Environmental Conditions

Crashes occurring in “Clear” weather conditions increased from 20 in January 2023 to 25 in January 2024. Crashes on “Snow” covered roads were 12 in January 2024, while there were no “Snow” crashes reported in January 2023. Crashes occurring during “Daylight” hours increased from 15 to 31 year-over-year.

Weather

Clear25 (46.3%)
25.0%prior 20
Cloudy9 (16.7%)
Snow4 (7.4%)
Cloudy/Clear2 (3.7%)
Snow/Blowing sand, snow2 (3.7%)
Snow/Rain2 (3.7%)
Rain/Cloudy1 (1.9%)
Sleet, hail (freezing rain or drizzle)1 (1.9%)
Snow/Cloudy1 (1.9%)
Blowing sand, snow1 (1.9%)

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

Lighting

Daylight31 (58.5%)
106.7%prior 15
Dark - lighted roadway14 (26.4%)
75.0%prior 8
Dusk3 (5.7%)
Dark - roadway not lighted2 (3.8%)
Dark - unknown roadway lighting1 (1.9%)
Dawn1 (1.9%)
Other1 (1.9%)

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

Road Surface

Dry24 (44.4%)
26.3%prior 19
Snow12 (22.2%)
Wet9 (16.7%)
-10.0%prior 10
Slush5 (9.3%)
Ice4 (7.4%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 52 in January 2023 to 95 in January 2024. Toyota remained the top make involved, increasing from 11 to 15 vehicles, while Honda vehicles increased from 8 to 9. The age group 35-44 experienced the largest increase in persons involved, rising from 10 to 22, and the 0-15 age group also saw a notable rise from 6 to 17.

Top Vehicle Makes (95 vehicles)

1
TOYOTA15 (15.8%)
36.4%prior 11
2
FORD11 (11.6%)
57.1%prior 7
3
NISSAN9 (9.5%)
4
HONDA9 (9.5%)
12.5%prior 8
5
CHEVROLET8 (8.4%)
6
JEEP6 (6.3%)
7
SUBARU6 (6.3%)
8
VOLKSWAGEN5 (5.3%)
9
GMC4 (4.2%)
10
MITS3 (3.2%)

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

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

Sex Distribution (104 persons with recorded sex)

Female53 (51.0%)
112.0%prior 25
Male51 (49.0%)
59.4%prior 32

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

Speed Limit Zones

Crashes in 25 mph zones increased from 17 in January 2023 to 20 in January 2024. Crashes in 30 mph zones nearly doubled, rising from 10 to 19 incidents year-over-year. Fatal crashes remained at zero across all speed zones in both periods.

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

Data Coverage

  • Reporting period: 2024-01-01 through 2024-01-31 (31 days)
  • Geographic scope: SOUTHBRIDGE, MA
  • Total crash records analyzed: 54
  • Total persons involved: 127
  • Total vehicles involved: 95

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: January 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/southbridge/january-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 — January 2024 | ThatCarHitMe.com