Monthly Traffic Safety Analysis

155 CRASHES IN
SPRINGFIELD, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

Total crashes in Springfield, MA decreased by 40.4% from 260 in March 2024 to 155 in March 2025. A notable shift is the increase in total fatalities from 0 in March 2024 to 2 in March 2025. Total injuries also saw a significant decrease, falling by 49.3% from 134 to 68.

155

▼ -40.4%was 260

Total Crash Events

2

Persons Killed

68

▼ -49.3%was 134

Persons Injured

33

▼ -23.3%was 43

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 12 crashes with unreported severity are not shown in the severity breakdown.

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 Springfield, MA show a significant downward trend year-over-year, decreasing by 105 crashes from 260 in March 2024 to 155 in March 2025. This represents a 40.4% reduction in total crashes for the period.

33

Hit-and-Run Crashes — March 2025

▼ -23.3% vs prior (43)

Hit-and-run crashes decreased in count from 43 in March 2024 to 33 in March 2025. However, the hit-and-run rate increased from 16.5% of total crashes in March 2024 to 21.3% in March 2025.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 0→%

0

Other Killed

Prior: 0→0.0%

4

Pedestrians Injured

Prior: 6↓-33.3%

3

Cyclists Injured

Prior: 4↓-25.0%

60

Motorists Injured

Prior: 124↓-51.6%

1

Other Injured

Prior: 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 shifted from Friday with 48 crashes in March 2024 to Saturday with 28 crashes in March 2025. The peak crash hour remained 4 p.m. for both periods, though the count decreased from 27 crashes in March 2024 to 15 crashes in March 2025.

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

Fatalities increased from 0 in March 2024 to 2 in March 2025, with fatal crashes also rising from 0 to 2. Total injuries decreased by 49.3%, from 134 to 68. Serious injury crashes dropped from 7 (2.7% share) to 2 (1.3% share), while minor injury crashes decreased from 51 to 36.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.3%
Serious Injury2serious injury crashes1.3%
↓-71.4%prior 7
Minor Injury36minor injury crashes23.2%
↓-29.4%prior 51
Possible Injury13possible injury crashes8.4%
↓-56.7%prior 30
No Injury90no injury crashes58.1%
↓-41.9%prior 155

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

Inattention remained the leading contributing factor, decreasing by 27 crashes from 62 in March 2024 to 35 in March 2025. Failed to yield right of way also saw a reduction of 26 crashes, from 44 to 18. 'No improper driving' decreased by 5 crashes, from 30 to 25.

Officer-Reported Primary Contributing Cause

Inattention35 (22.6%)↓-43.5%prior 62
No improper driving25 (16.1%)↓-16.7%prior 30
Failed to yield right of way18 (11.6%)↓-59.1%prior 44
Followed too closely15 (9.7%)↑25.0%prior 12
Failure to keep in proper lane or running off road14 (9%)↓-44.0%prior 25
Disregarded traffic signs, signals, road markings5 (3.2%)↓-44.4%prior 9
Made an improper turn4 (2.6%)↓-20.0%prior 5
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (2.6%)↓-42.9%prior 7
Exceeded authorized speed limit3 (1.9%)↓-57.1%prior 7
Driving too fast for conditions3 (1.9%)↓-66.7%prior 9

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 clear weather conditions decreased from 178 to 97, and those in rainy conditions decreased from 34 to 19. Similarly, crashes on dry road surfaces dropped from 201 to 124, and those in daylight conditions decreased from 159 to 94.

Weather

Clear97 (63.8%)
↓-45.5%prior 178
Rain19 (12.5%)
↓-44.1%prior 34
Cloudy17 (11.2%)
↓-37.0%prior 27
Clear/Clear8 (5.3%)
Cloudy/Cloudy4 (2.6%)
Rain/Rain2 (1.3%)
Clear/Cloudy2 (1.3%)
Clear/Unknown1 (0.7%)
Cloudy/Rain1 (0.7%)
↓-88.9%prior 9
Rain/Cloudy1 (0.7%)

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

Lighting

Daylight94 (61.8%)
↓-40.9%prior 159
Dark - lighted roadway50 (32.9%)
↓-38.3%prior 81
Dusk4 (2.6%)
↓-60.0%prior 10
Dark - roadway not lighted2 (1.3%)
Dark - unknown roadway lighting1 (0.7%)
Dawn1 (0.7%)

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

Road Surface

Dry124 (81.0%)
↓-38.3%prior 201
Wet29 (19.0%)
↓-50.0%prior 58

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

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 483 in March 2024 to 291 in March 2025. Honda remained the top make involved, though its count decreased from 78 to 42, and Toyota vehicles involved dropped from 61 to 36. All listed age groups saw a reduction in person counts involved in crashes, with the 26-34 age group showing the largest decrease from 134 to 54 persons.

Top Vehicle Makes (291 vehicles)

1
HONDA42 (14.4%)
↓-46.2%prior 78
2
TOYOTA36 (12.4%)
↓-41.0%prior 61
3
NISSAN25 (8.6%)
↓-34.2%prior 38
4
HYUNDAI24 (8.2%)
↓-20.0%prior 30
5
FORD19 (6.5%)
↓-53.7%prior 41
6
CHEVROLET14 (4.8%)
↓-33.3%prior 21
7
KIA10 (3.4%)
↓-33.3%prior 15
8
ACURA9 (3.1%)
↓-47.1%prior 17
9
JEEP8 (2.7%)
↓-42.9%prior 14
10
INFI6 (2.1%)
↓-60.0%prior 15

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

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

Sex Distribution (313 persons with recorded sex)

Male196 (62.6%)
↓-35.3%prior 303
Female117 (37.4%)
↓-57.9%prior 278

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

Crashes in 25 mph zones decreased from 88 to 40, and in 30 mph zones from 83 to 42. Notably, crashes in 35 mph zones saw an increase in fatalities from 0 to 2, resulting in a fatal crash rate of 6.452% in this zone for March 2025 compared to 0% in March 2024.

Fatal crashes by zone: 35 mph: 2 of 31 (6.452%)

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: SPRINGFIELD, MA
  • Total crash records analyzed: 155
  • Total persons involved: 386
  • Total vehicles involved: 291

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: 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/springfield/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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Springfield, MA Crash Report — March 2025 | ThatCarHitMe.com