Monthly Traffic Safety Analysis

30 CRASHES IN
SOUTHBOROUGH, MA
MARCH 2026

All metrics benchmarked againstMarch 2025

In March 2026, SOUTHBOROUGH experienced 30 total crashes, marking a 36.4% increase compared to the 22 crashes reported in March 2025. The most significant year-over-year shift was a 700% rise in total injuries, from 2 in the prior period to 16 in the current period.

30

36.4%was 22

Total Crash Events

0

Persons Killed

16

700.0%was 2

Persons Injured

4

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 · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in SOUTHBOROUGH show an upward trend year-over-year, with total crashes increasing by 36.4% from 22 to 30. This rise is accompanied by a substantial increase in injuries, which grew from 2 to 16, representing a 700% increase.

4

Hit-and-Run Crashes — March 2026

13.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 2700.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted, with the peak day moving from Friday with 5 crashes in March 2025 to Tuesday with 10 crashes in March 2026. While 4 PM remained a peak hour for crashes in both periods, its count decreased from 5 in March 2025 to 4 in March 2026. Crashes on Sunday saw a notable increase from 2 to 9.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either March 2025 or March 2026. However, the number of injury crashes increased significantly, with 16 injuries reported in March 2026 compared to 2 in March 2025. This includes the emergence of 10 minor injury crashes (33.3% of current crashes) in March 2026, a category not present in the prior period, where possible injuries accounted for 9.1% of crashes.

Outcome by Severity (Crash Events)

Minor Injury10minor injury crashes33.3%
Possible Injury1possible injury crashes3.3%
-50.0%prior 2
No Injury18no injury crashes60%
-10.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record

Top Contributing Factors

The distribution of contributing factors saw notable changes; 'No improper driving' crashes increased by 500% from 2 to 12, becoming the most frequent factor. Conversely, 'Inattention' crashes decreased by 57.1%, from 7 to 3, and 'Other improper action' decreased by 66.7% from 3 to 1. Crashes attributed to 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway' increased by 200%, from 1 to 3.

Officer-Reported Primary Contributing Cause

No improper driving12 (40%)
Inattention3 (10%)-57.1%prior 7
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (10%)
Failed to yield right of way2 (6.7%)
Failure to keep in proper lane or running off road2 (6.7%)
Disregarded traffic signs, signals, road markings1 (3.3%)
Other improper action1 (3.3%)
Driving too fast for conditions1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Daylight remained the predominant lighting condition for crashes, accounting for 22 crashes in March 2026 compared to 20 in March 2025. Crashes on dry road surfaces increased from 14 to 16, while crashes on wet surfaces decreased from 8 to 7. There was a notable increase in crashes occurring on snowy and icy road surfaces in March 2026, with 5 and 2 crashes respectively, conditions not present in March 2025's road surface data.

Weather

Clear14 (46.7%)
16.7%prior 12
Clear/Clear4 (13.3%)
Cloudy4 (13.3%)
Snow/Sleet, hail (freezing rain or drizzle)3 (10.0%)
Snow2 (6.7%)
Sleet, hail (freezing rain or drizzle)/Rain1 (3.3%)
Snow/Rain1 (3.3%)
Rain1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash

Lighting

Daylight22 (73.3%)
10.0%prior 20
Dark - lighted roadway5 (16.7%)
Dusk2 (6.7%)
Dark - roadway not lighted1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field

Road Surface

Dry16 (53.3%)
14.3%prior 14
Wet7 (23.3%)
-12.5%prior 8
Snow5 (16.7%)
Ice2 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (50 vehicles)

1
TOYOTA12 (24%)
2
FORD8 (16%)
14.3%prior 7
3
HONDA5 (10%)
-50.0%prior 10
4
JEEP3 (6%)
5
CHEVROLET2 (4%)
6
DODGE2 (4%)
7
HYUNDAI2 (4%)
8
NISSAN2 (4%)
9
SUZI1 (2%)
10
ACURA1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records

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

Sex Distribution (65 persons with recorded sex)

Male33 (50.8%)
-10.8%prior 37
Female32 (49.2%)
52.4%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 40 mph speed zones increased from 3 to 7, while those in 50 mph zones decreased from 12 to 9. Crashes in 30 mph zones saw a decrease from 4 to 2, and 35 mph zones saw an increase from 1 to 2. New speed zones with recorded crashes in March 2026 include 15 mph (1 crash), 20 mph (3 crashes), and 65 mph (5 crashes), which were not present in March 2025 data.

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

Data Coverage

  • Reporting period: 2026-03-01 through 2026-03-31 (31 days)
  • Geographic scope: SOUTHBOROUGH, MA
  • Total crash records analyzed: 30
  • Total persons involved: 72
  • Total vehicles involved: 50

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