Monthly Traffic Safety Analysis

306 CRASHES IN
SPRINGFIELD, MA
AUGUST 2023

All metrics benchmarked againstAugust 2022

In August 2023, Springfield, MA experienced 306 total crashes, a decrease from 345 crashes in August 2022. This represents an 11.3% reduction year-over-year. The most notable shift was the elimination of fatalities, with 0 reported in August 2023 compared to 1 fatality in August 2022.

306

-11.3%was 345

Total Crash Events

0

-100.0%was 1

Persons Killed

157

-25.9%was 212

Persons Injured

35

-14.6%was 41

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crash incidents, with total crashes falling by 11.3% from 345 in August 2022 to 306 in August 2023. Concurrently, total injuries saw a significant decline of 25.9%, dropping from 212 to 157 over the same period.

35

Hit-and-Run Crashes — August 2023

-14.6% vs prior (41)

Hit-and-run crashes decreased by 6 incidents, from 41 in August 2022 to 35 in August 2023. The hit-and-run crash rate also saw a slight decline, moving from 11.9% in August 2022 to 11.4% in August 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 1-100.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 7-57.1%

5

Cyclists Injured

Prior: 366.7%

149

Motorists Injured

Prior: 202-26.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Friday in August 2022 (65 crashes) to Wednesday in August 2023 (62 crashes). While the peak hour remained 4 p.m. in both periods, the number of crashes at this hour decreased from 37 in August 2022 to 22 in August 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities decreased from 1 in August 2022 to 0 in August 2023. Serious injuries (Severity A) saw a substantial reduction of 72.7%, from 11 to 3, while minor injuries (Severity B) decreased by 15.3%, from 85 to 72. Possible injuries (Severity C) also declined by 17.1%, from 35 to 29.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes1%
-72.7%prior 11
Minor Injury72minor injury crashes23.5%
-15.3%prior 85
Possible Injury29possible injury crashes9.5%
-17.1%prior 35
No Injury187no injury crashes61.1%
1.6%prior 184

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Inattention' saw the largest decrease in count, falling by 34 crashes from 94 in August 2022 to 60 in August 2023. Conversely, 'Failed to yield right of way' increased by 20 crashes, rising from 42 to 62. The top two contributing factors also swapped rankings, with 'Failed to yield right of way' becoming the most frequent in August 2023.

Officer-Reported Primary Contributing Cause

Failed to yield right of way62 (20.3%)47.6%prior 42
Inattention60 (19.6%)-36.2%prior 94
No improper driving42 (13.7%)-2.3%prior 43
Followed too closely20 (6.5%)11.1%prior 18
Failure to keep in proper lane or running off road18 (5.9%)12.5%prior 16
Disregarded traffic signs, signals, road markings12 (3.9%)-36.8%prior 19
Other improper action10 (3.3%)-28.6%prior 14
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner9 (2.9%)28.6%prior 7
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway8 (2.6%)-11.1%prior 9
Distracted7 (2.3%)-41.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 293 in August 2022 to 235 in August 2023. Crashes on dry road surfaces also saw a reduction, from 314 to 259, while those on wet surfaces increased from 30 to 46. Daylight crashes decreased from 254 to 214, whereas crashes in dark-lighted conditions saw a smaller decrease from 78 to 70.

Weather

Clear235 (77.0%)
-19.8%prior 293
Cloudy34 (11.1%)
88.9%prior 18
Rain12 (3.9%)
-33.3%prior 18
Cloudy/Rain8 (2.6%)
60.0%prior 5
Clear/Unknown5 (1.6%)
Rain/Cloudy5 (1.6%)
Clear/Other3 (1.0%)
Rain/Clear2 (0.7%)
Clear/Cloudy1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Weather condition at time of crash

Lighting

Daylight214 (70.2%)
-15.7%prior 254
Dark - lighted roadway70 (23.0%)
-10.3%prior 78
Dusk11 (3.6%)
Dawn5 (1.6%)
Dark - roadway not lighted4 (1.3%)
-20.0%prior 5
Other1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Lighting condition field

Road Surface

Dry259 (84.9%)
-17.5%prior 314
Wet46 (15.1%)
53.3%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased by 14.0%, from 663 in August 2022 to 570 in August 2023. Among top makes, Hyundai vehicles involved in crashes decreased by 19, from 52 to 33, and Nissan decreased by 10, from 59 to 49. The age group 35-44 saw the largest decrease in person involvement, with 40 fewer individuals, dropping from 138 to 98.

Top Vehicle Makes (570 vehicles)

1
HONDA92 (16.1%)
2.2%prior 90
2
TOYOTA83 (14.6%)
3.8%prior 80
3
FORD53 (9.3%)
-3.6%prior 55
4
NISSAN49 (8.6%)
-16.9%prior 59
5
HYUNDAI33 (5.8%)
-36.5%prior 52
6
CHEVROLET32 (5.6%)
-13.5%prior 37
7
JEEP25 (4.4%)
4.2%prior 24
8
ACURA18 (3.2%)
5.9%prior 17
9
MAZDA15 (2.6%)
36.4%prior 11
10
INFI12 (2.1%)
-7.7%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Vehicle unit records

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

Sex Distribution (687 persons with recorded sex)

Male368 (53.6%)
-12.8%prior 422
Female319 (46.4%)
-10.1%prior 355

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones decreased by 30, from 111 in August 2022 to 81 in August 2023. Crashes in 35 mph zones also saw a reduction of 11, from 89 to 78. There was 1 fatal crash recorded in a 30 mph zone in August 2022, while no fatal crashes were reported in any speed zone in August 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · 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: 2023-08-01 through 2023-08-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-08-01 through 2023-08-31 (31 days)
  • Geographic scope: SPRINGFIELD, MA
  • Total crash records analyzed: 306
  • Total persons involved: 786
  • Total vehicles involved: 570

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). "SPRINGFIELD, MA Crash Intelligence Report: August 2023." Published June 21, 2026. Reporting period: 2023-08-01 to 2023-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/august-2023-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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Springfield, MA Crash Report — August 2023 | ThatCarHitMe.com