Yearly Traffic Safety Analysis

352 CRASHES IN
SOUTHBRIDGE, MA
2023

All metrics benchmarked against2022

In 2023, Southbridge recorded 352 total traffic crashes, a 10.2% decrease from the 392 crashes reported in 2022. While overall crashes and injuries declined, the most notable year-over-year shift was the occurrence of one fatal crash in 2023, compared to zero in the prior year.

352

-10.2%was 392

Total Crash Events

1

Persons Killed

65

-12.2%was 74

Persons Injured

31

34.8%was 23

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. 19 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic incidents shows a general decrease. Total crashes fell by 10.2%, from 392 in 2022 to 352 in 2023. Similarly, the number of people injured in these crashes decreased by 12.2%, from 74 to 65. However, this downward trend is contrasted by an increase in fatalities, from zero in 2022 to one in 2023.

31

Hit-and-Run Crashes — 2023

34.8% vs prior (23)

Hit-and-run crashes showed an upward trend. The number of hit-and-run incidents increased from 23 in 2022 to 31 in 2023. The hit-and-run rate, as a percentage of total crashes, also rose from 5.9% in 2022 to 8.8% in 2023.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

6

Pedestrians Injured

Prior: 520.0%

2

Cyclists Injured

Prior: 3-33.3%

57

Motorists Injured

Prior: 66-13.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained broadly consistent year-over-year, with incidents concentrated in the mid-week afternoon. The peak day for crashes shifted from Tuesday (75 crashes) in 2022 to Wednesday (61 crashes) in 2023. The peak hour also shifted slightly later, from the 2 p.m. hour in 2022 (39 crashes) to the 3 p.m. hour in 2023 (40 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the severity profile shifted in 2023. The city experienced one fatal crash in 2023 after having none in 2022, raising the fatal crash rate from 0 to 0.28 per 100 crashes. Conversely, the number of serious injury crashes saw a significant decline, dropping from 13 in 2022 to 3 in 2023. The share of crashes resulting in no injury increased from 77.3% in 2022 to 81.0% in 2023.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
Serious Injury3serious injury crashes0.9%
-76.9%prior 13
Minor Injury38minor injury crashes10.8%
-2.6%prior 39
Possible Injury6possible injury crashes1.7%
-45.5%prior 11
No Injury285no injury crashes81%
-5.9%prior 303

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Inattention was a leading contributing factor in both periods, with its count increasing from 68 crashes in 2022 to 72 in 2023. The most significant change was in crashes attributed to a fatigued or asleep driver, which increased from 2 incidents in 2022 to 11 in 2023, a 450% increase in count. Conversely, crashes involving a distracted driver decreased from 15 to 7, and those from failure to keep in the proper lane fell from 27 to 21.

Officer-Reported Primary Contributing Cause

No improper driving106 (30.1%)-2.8%prior 109
Inattention72 (20.5%)5.9%prior 68
Failed to yield right of way29 (8.2%)11.5%prior 26
Failure to keep in proper lane or running off road21 (6%)-22.2%prior 27
Followed too closely15 (4.3%)7.1%prior 14
Other improper action15 (4.3%)-6.3%prior 16
Fatigued/asleep11 (3.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner8 (2.3%)-33.3%prior 12
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway7 (2%)-22.2%prior 9
Distracted7 (2%)-53.3%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in crash conditions between the two periods. Crashes on wet road surfaces more than doubled, increasing from 26 in 2022 to 64 in 2023, and incidents during rain increased from 10 to 27. Correspondingly, crashes on dry roads decreased from 336 to 276. The majority of crashes in both years occurred in daylight (273 in 2022, 224 in 2023) and clear weather (288 in 2022, 234 in 2023).

Weather

Clear234 (67.0%)
-18.8%prior 288
Rain27 (7.7%)
170.0%prior 10
Cloudy21 (6.0%)
-30.0%prior 30
Clear/Cloudy14 (4.0%)
40.0%prior 10
Clear/Other10 (2.9%)
0.0%prior 10
Rain/Cloudy8 (2.3%)
Snow7 (2.0%)
0.0%prior 7
Cloudy/Rain6 (1.7%)
-14.3%prior 7
Cloudy/Clear4 (1.1%)
Clear/Unknown3 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight224 (64.7%)
-17.9%prior 273
Dark - lighted roadway78 (22.5%)
-4.9%prior 82
Dark - roadway not lighted20 (5.8%)
150.0%prior 8
Dawn13 (3.8%)
Dusk8 (2.3%)
-50.0%prior 16
Other3 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry276 (79.1%)
-17.9%prior 336
Wet64 (18.3%)
146.2%prior 26
Snow5 (1.4%)
-37.5%prior 8
Ice2 (0.6%)
-90.0%prior 20
Sand, mud, dirt, oil, gravel2 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes—Toyota, Ford, and Honda—remained the same across both years. Toyota-involved crashes decreased from 145 to 110, while Honda-involved crashes saw a slight increase from 71 to 73. The age distribution of persons involved in crashes remained relatively stable, with the 26-34 age group representing the largest cohort in both 2022 (147 persons) and 2023 (124 persons).

Top Vehicle Makes (633 vehicles)

1
TOYOTA110 (17.4%)
-24.1%prior 145
2
FORD89 (14.1%)
-3.3%prior 92
3
HONDA73 (11.5%)
2.8%prior 71
4
CHEVROLET39 (6.2%)
-30.4%prior 56
5
JEEP35 (5.5%)
12.9%prior 31
6
NISSAN33 (5.2%)
-23.3%prior 43
7
SUBARU27 (4.3%)
-20.6%prior 34
8
HYUNDAI25 (3.9%)
4.2%prior 24
9
GMC23 (3.6%)
43.8%prior 16
10
ACURA14 (2.2%)
40.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (654 persons with recorded sex)

Male344 (52.6%)
-17.5%prior 417
Female310 (47.4%)
0.6%prior 308

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crash locations shifted toward lower speed zones in 2023. Crashes in 25 mph zones increased from 189 in 2022 to 209 in 2023, while those in 30 mph zones decreased from 105 to 83. The single fatal crash in 2023 occurred in a 25 mph zone. There were no fatal crashes in any speed zone in 2022.

Fatal crashes by zone: 25 mph: 1 of 209 (0.478%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: SOUTHBRIDGE, MA
  • Total crash records analyzed: 352
  • Total persons involved: 792
  • Total vehicles involved: 633

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/southbridge/2023-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

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Southbridge, MA Crash Report — 2023 | ThatCarHitMe.com