Yearly Traffic Safety Analysis

368 CRASHES IN
SOUTHBOROUGH, MA
2024

All metrics benchmarked against2023

In Southborough, total traffic crashes remained relatively stable, decreasing by less than 1% from 371 in 2023 to 368 in 2024. The total number of injuries was unchanged at 100 for both years. The most significant change was the occurrence of one fatal crash in 2024, following a year with zero traffic fatalities.

368

-0.8%was 371

Total Crash Events

1

Persons Killed

100

Persons Injured

15

-28.6%was 21

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 4 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 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall number of crashes in Southborough saw a slight year-over-year decline, falling by 0.8% from 371 in 2023 to 368 in 2024. While the total number of injuries remained constant at 100, the city recorded one fatality in 2024, compared to zero in the prior year. This indicates a stable trend in crash frequency but an increase in the most severe outcomes.

15

Hit-and-Run Crashes — 2024

-28.6% vs prior (21)

The number of hit-and-run incidents in Southborough decreased from 2023 to 2024. There were 15 hit-and-run crashes recorded in 2024, down from 21 in the prior year. This represents a 28.6% reduction in the count of such events. The hit-and-run rate, as a percentage of total crashes, also declined from 5.7% in 2023 to 4.1% in 2024.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

100

Motorists Injured

Prior: 982.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns show that while Tuesday remained the peak day for crashes in both 2023 (68 crashes) and 2024 (64 crashes), the most dangerous hour shifted significantly. In 2023, the peak was the 8 a.m. morning commute hour with 35 crashes. In 2024, the peak moved to the 4 p.m. evening commute hour, which saw 42 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened in 2024 compared to the previous year. Southborough recorded one fatal crash in 2024 after having none in 2023. The proportion of serious injury crashes also increased, rising from 1.3% (5 crashes) in 2023 to 2.2% (8 crashes) in 2024. Conversely, the share of crashes resulting in minor injuries decreased from 15.1% to 13.3%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
Serious Injury8serious injury crashes2.2%
60.0%prior 5
Minor Injury49minor injury crashes13.3%
-12.5%prior 56
Possible Injury16possible injury crashes4.3%
45.5%prior 11
No Injury290no injury crashes78.8%
-1.4%prior 294

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors remained consistent year-over-year, with 'No improper driving' (118 crashes) and 'Inattention' (59 crashes) being the top two cited causes in 2024. However, the count of crashes attributed to 'Driving too fast for conditions' saw a significant decrease, falling from 22 incidents in 2023 to just 8 in 2024. In contrast, crashes involving 'Distraction' increased in count from 8 in 2023 to 13 in 2024.

Officer-Reported Primary Contributing Cause

No improper driving118 (32.1%)4.4%prior 113
Inattention59 (16%)-6.3%prior 63
Followed too closely34 (9.2%)13.3%prior 30
Failed to yield right of way21 (5.7%)-4.5%prior 22
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner17 (4.6%)13.3%prior 15
Distracted13 (3.5%)62.5%prior 8
Other improper action12 (3.3%)0.0%prior 12
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway8 (2.2%)-33.3%prior 12
Failure to keep in proper lane or running off road8 (2.2%)-52.9%prior 17
Driving too fast for conditions8 (2.2%)-63.6%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In 2024, a higher number of crashes occurred on dry roads (282) and in clear weather (263) compared to 2023 (262 and 242, respectively). Correspondingly, there was a notable decrease in crashes occurring on wet roads, which fell from 77 in 2023 to 51 in 2024. Crashes during daylight hours increased from 250 to 257, representing a slightly larger share of the total (69.8% in 2024 vs. 67.4% in 2023).

Weather

Clear263 (71.9%)
8.7%prior 242
Cloudy42 (11.5%)
35.5%prior 31
Rain20 (5.5%)
-33.3%prior 30
Snow11 (3.0%)
-31.3%prior 16
Snow/Sleet, hail (freezing rain or drizzle)10 (2.7%)
42.9%prior 7
Cloudy/Rain4 (1.1%)
-73.3%prior 15
Cloudy/Snow3 (0.8%)
-40.0%prior 5
Clear/Clear2 (0.5%)
Snow/Cloudy2 (0.5%)
Fog, smog, smoke2 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight257 (69.8%)
2.8%prior 250
Dark - lighted roadway58 (15.8%)
-13.4%prior 67
Dark - roadway not lighted30 (8.2%)
11.1%prior 27
Dusk13 (3.5%)
30.0%prior 10
Dawn9 (2.4%)
-30.8%prior 13
Dark - unknown roadway lighting1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry282 (76.8%)
7.6%prior 262
Wet51 (13.9%)
-33.8%prior 77
Snow22 (6.0%)
4.8%prior 21
Ice11 (3.0%)
83.3%prior 6
Other1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained Toyota, Honda, and Ford in both years, though the count of Hondas increased from 78 to 92. Subaru, which was the fourth most common make in 2023 with 38 vehicles, dropped to seventh in 2024 with 26 vehicles. Analysis of persons involved shows a demographic shift, with the 35-44 age group's representation growing from 16.2% of all persons in 2023 to 20.2% in 2024.

Top Vehicle Makes (680 vehicles)

1
TOYOTA105 (15.4%)
-0.9%prior 106
2
HONDA92 (13.5%)
17.9%prior 78
3
FORD73 (10.7%)
-5.2%prior 77
4
CHEVROLET40 (5.9%)
21.2%prior 33
5
JEEP36 (5.3%)
38.5%prior 26
6
NISSAN27 (4%)
-12.9%prior 31
7
SUBARU26 (3.8%)
-31.6%prior 38
8
VOLKSWAGEN24 (3.5%)
84.6%prior 13
9
HYUNDAI22 (3.2%)
-8.3%prior 24
10
GMC17 (2.5%)
-5.6%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (800 persons with recorded sex)

Male482 (60.3%)
2.6%prior 470
Female318 (39.8%)
7.8%prior 295

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones shifted between the two years. There was a significant decrease in crashes within 65 mph zones, which fell from 78 incidents in 2023 to 47 in 2024. Conversely, crashes in 40 mph zones increased from 28 to 40, and crashes in 50 mph zones rose from 138 to 145. The single fatal crash in 2024 occurred in a zone with a posted speed limit of 35 mph.

Fatal crashes by zone: 35 mph: 1 of 19 (5.263%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: SOUTHBOROUGH, MA
  • Total crash records analyzed: 368
  • Total persons involved: 832
  • Total vehicles involved: 680

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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/southborough/2024-annual-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

ThatCarHitMe.com · An Injuria.ai Company

Southborough, MA Crash Report — 2024 | ThatCarHitMe.com