Monthly Traffic Safety Analysis

354 CRASHES IN
SPRINGFIELD, MA
APRIL 2022

All metrics benchmarked againstApril 2021

Total crashes in Springfield, MA increased from 296 in April 2021 to 354 in April 2022, representing a 19.59% rise. This period also saw a significant shift in fatalities, with 1 fatality recorded in April 2022 compared to 0 in the prior year. Overall injuries also increased by 15.03%, from 153 to 176.

354

19.6%was 296

Total Crash Events

1

Persons Killed

176

15.0%was 153

Persons Injured

42

35.5%was 31

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in crash activity year-over-year in Springfield, MA. Total crashes rose by 19.59%, from 296 in April 2021 to 354 in April 2022. This upward trend also extended to total injuries, which increased by 15.03%.

42

Hit-and-Run Crashes — April 2022

35.5% vs prior (31)

Hit-and-run crashes increased by 35.48%, rising from 31 incidents in April 2021 to 42 in April 2022. The hit-and-run rate also saw an increase, moving from 10.5% of total crashes in the prior period to 11.9% in the current period.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

4

Pedestrians Injured

Prior: 333.3%

3

Cyclists Injured

Prior: 250.0%

169

Motorists Injured

Prior: 14814.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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 Thursday in April 2021 (65 crashes) to Friday in April 2022 (63 crashes). However, the peak hour remained consistent at 4 PM in both periods, with 36 crashes in April 2021 increasing to 39 crashes in April 2022. Tuesday also saw a notable increase in crashes, rising from 23 to 59 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes increased from 0 in April 2021 to 1 in April 2022, resulting in a fatal rate of 0.28% of total crashes in the current period. Total injuries rose by 15.03%, from 153 to 176. The proportion of 'Serious Injury' crashes slightly increased from 1.7% to 2%, while 'No Injury' crashes saw a notable rise in their share, from 50.7% to 60.2%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
Serious Injury7serious injury crashes2%
40.0%prior 5
Minor Injury72minor injury crashes20.3%
18.0%prior 61
Possible Injury41possible injury crashes11.6%
17.1%prior 35
No Injury213no injury crashes60.2%
42.0%prior 150

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw notable count increases year-over-year. 'No improper driving' increased by 100%, from 18 to 36 crashes, and 'Exceeded authorized speed limit' increased by 150%, from 4 to 10 crashes. Conversely, 'Disregarded traffic signs, signals, road markings' decreased by 35%, from 20 to 13 crashes, and 'Driving too fast for conditions' decreased by 50%, from 12 to 6 crashes.

Officer-Reported Primary Contributing Cause

Inattention97 (27.4%)10.2%prior 88
Failed to yield right of way56 (15.8%)30.2%prior 43
No improper driving36 (10.2%)100.0%prior 18
Failure to keep in proper lane or running off road31 (8.8%)40.9%prior 22
Followed too closely15 (4.2%)36.4%prior 11
Disregarded traffic signs, signals, road markings13 (3.7%)-35.0%prior 20
Exceeded authorized speed limit10 (2.8%)
Other improper action9 (2.5%)28.6%prior 7
Made an improper turn8 (2.3%)0.0%prior 8
Distracted7 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased by 39.68%, from 189 in April 2021 to 264 in April 2022. Similarly, crashes under 'Daylight' conditions rose by 18.45%, from 206 to 244. Crashes on 'Dry' road surfaces increased by 23.81%, from 231 to 286, while those on 'Wet' surfaces saw an 8.06% increase, from 62 to 67.

Weather

Clear264 (75.0%)
39.7%prior 189
Cloudy37 (10.5%)
-9.8%prior 41
Rain28 (8.0%)
0.0%prior 28
Cloudy/Rain10 (2.8%)
-58.3%prior 24
Rain/Cloudy5 (1.4%)
Clear/Cloudy3 (0.9%)
Cloudy/Clear2 (0.6%)
Rain/Clear1 (0.3%)
Clear/Rain1 (0.3%)
Clear/Clear1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash

Lighting

Daylight244 (69.1%)
18.4%prior 206
Dark - lighted roadway93 (26.3%)
25.7%prior 74
Dusk7 (2.0%)
Dawn5 (1.4%)
Dark - roadway not lighted4 (1.1%)
-33.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field

Road Surface

Dry286 (81.0%)
23.8%prior 231
Wet67 (19.0%)
8.1%prior 62

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 21.07%, from 560 to 678 year-over-year. The 35-44 age group saw the largest increase in persons involved, rising from 100 to 143. Among vehicle makes, NISSAN showed a significant increase in involvement, rising from 45 to 71 vehicles.

Top Vehicle Makes (678 vehicles)

1
HONDA100 (14.7%)
17.6%prior 85
2
TOYOTA80 (11.8%)
15.9%prior 69
3
NISSAN71 (10.5%)
57.8%prior 45
4
FORD52 (7.7%)
6.1%prior 49
5
HYUNDAI52 (7.7%)
48.6%prior 35
6
CHEVROLET50 (7.4%)
22.0%prior 41
7
ACURA27 (4%)
80.0%prior 15
8
JEEP24 (3.5%)
41.2%prior 17
9
SUBARU22 (3.2%)
57.1%prior 14
10
KIA17 (2.5%)
30.8%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records

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

Sex Distribution (785 persons with recorded sex)

Male405 (51.6%)
20.9%prior 335
Female380 (48.4%)
21.8%prior 312

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 MPH zones increased by 10.91% (from 110 to 122), while those in 30 MPH zones rose by 26.09% (from 92 to 116). Crashes in 35 MPH zones also saw a 36.84% increase, from 57 to 78. A fatal crash occurred in a 55 MPH zone in April 2022, where none were recorded in the prior year.

Fatal crashes by zone: 55 mph: 1 of 21 (4.762%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-04-01 through 2022-04-30 (30 days)
  • Geographic scope: SPRINGFIELD, MA
  • Total crash records analyzed: 354
  • Total persons involved: 901
  • Total vehicles involved: 678

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: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/april-2022-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 — April 2022 | ThatCarHitMe.com