Monthly Traffic Safety Analysis

22 CRASHES IN
SOUTHBOROUGH, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

In March 2025, SOUTHBOROUGH experienced 22 crashes, an increase of 15.79% compared to 19 crashes in March 2024. Fatalities remained at 0 in both periods, while total injuries also held steady at 2. The most notable shift was a 100% decrease in hit-and-run crashes, falling from 3 in March 2024 to 0 in March 2025.

22

15.8%was 19

Total Crash Events

0

Persons Killed

2

Persons Injured

0

-100.0%was 3

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in SOUTHBOROUGH increased year-over-year, rising from 19 crashes in March 2024 to 22 crashes in March 2025. This represents a 15.79% increase in total crash incidents. Despite this rise in total crashes, the number of reported injuries remained unchanged at 2 in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both March 2024 and March 2025, with 5 crashes reported on that day each year. However, the peak hour shifted from 5 PM with 3 crashes in March 2024 to 4 PM with 5 crashes in March 2025. Notably, crashes on Mondays increased from 2 to 4, and crashes on Saturdays increased from 2 to 4 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero for both March 2024 and March 2025, and the total number of injuries also stayed constant at 2. The distribution of injury severity shifted, with March 2024 reporting 1 serious injury (A) and 1 minor injury (B), while March 2025 reported 2 possible injuries (C). The proportion of crashes resulting in any injury slightly decreased from 10.6% in March 2024 to 9.1% in March 2025.

Outcome by Severity (Crash Events)

Possible Injury2possible injury crashes9.1%
No Injury20no injury crashes90.9%
17.6%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor shifted from 'No improper driving' in March 2024 to 'Inattention' in March 2025. Crashes attributed to 'Inattention' increased from 5 to 7, a 40% rise, making it the top factor. Conversely, crashes with 'No improper driving' as a factor decreased significantly from 8 to 2, representing a 75% reduction. 'Followed too closely' crashes doubled from 1 to 2 year-over-year.

Officer-Reported Primary Contributing Cause

Inattention7 (31.8%)40.0%prior 5
Other improper action3 (13.6%)
Followed too closely2 (9.1%)
No improper driving2 (9.1%)-75.0%prior 8
Disregarded traffic signs, signals, road markings2 (9.1%)
Driving too fast for conditions1 (4.5%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.5%)
Made an improper turn1 (4.5%)
Visibility obstructed1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in adverse weather conditions, such as rain or fog, increased from 4 crashes (21.1%) in March 2024 to 7 crashes (31.8%) in March 2025. Crashes on wet road surfaces increased from 5 to 8, while crashes on icy roads, which accounted for 2 incidents in March 2024, were not reported in March 2025. The number of crashes occurring during daylight hours increased from 14 to 20 year-over-year, while those in dark or dusk conditions decreased from 5 to 2.

Weather

Clear12 (54.5%)
20.0%prior 10
Cloudy3 (13.6%)
-40.0%prior 5
Cloudy/Rain2 (9.1%)
Rain/Cloudy2 (9.1%)
Rain1 (4.5%)
Rain/Fog, smog, smoke1 (4.5%)
Clear/Severe crosswinds1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash

Lighting

Daylight20 (90.9%)
42.9%prior 14
Dark - lighted roadway1 (4.5%)
Dusk1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field

Road Surface

Dry14 (63.6%)
16.7%prior 12
Wet8 (36.4%)
60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (44 vehicles)

1
HONDA10 (22.7%)
2
FORD7 (15.9%)
3
BMW4 (9.1%)
4
TOYOTA4 (9.1%)
-33.3%prior 6
5
SUBARU2 (4.5%)
6
MERCEDES-BENZ2 (4.5%)
7
JEEP2 (4.5%)
8
NISSAN2 (4.5%)
9
MAZDA1 (2.3%)
10
RAM1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records

Sex Distribution (58 persons with recorded sex)

Male37 (63.8%)
54.2%prior 24
Female21 (36.2%)
23.5%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events

Speed Limit Zones

The majority of crashes in both periods occurred in 50 mph speed zones, increasing from 9 crashes in March 2024 to 12 crashes in March 2025. Crashes in 30 mph zones doubled from 2 to 4, and those in 25 mph zones increased from 1 to 2. Notably, 2 crashes occurred in 20 mph zones and 2 crashes in 65 mph zones in March 2024, which were not observed in March 2025, while 1 crash occurred in a 35 mph zone in March 2025 that was not present in the prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-03-01 through 2025-03-31 (31 days)
  • Geographic scope: SOUTHBOROUGH, MA
  • Total crash records analyzed: 22
  • Total persons involved: 58
  • Total vehicles involved: 44

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). "SOUTHBOROUGH, MA Crash Intelligence Report: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/southborough/march-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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Southborough, MA Crash Report — March 2025 | ThatCarHitMe.com