Monthly Traffic Safety Analysis

389 CRASHES IN
SPRINGFIELD, MA
DECEMBER 2022

All metrics benchmarked againstDecember 2021

Total crashes in Springfield, MA decreased slightly from 393 in December 2021 to 389 in December 2022, representing a 1.02% reduction. The most notable year-over-year shift was a 58.3% decrease in pedestrian crashes, falling from 24 to 10.

389

-1.0%was 393

Total Crash Events

2

Persons Killed

186

-4.1%was 194

Persons Injured

42

-8.7%was 46

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in Springfield, MA showed a slight downward trend year-over-year, decreasing from 393 crashes in December 2021 to 389 crashes in December 2022. This represents a modest 1.02% reduction in total crash incidents for the month.

42

Hit-and-Run Crashes — December 2022

-8.7% vs prior (46)

Hit-and-run crashes decreased from 46 in December 2021 to 42 in December 2022, a reduction of 4 incidents. The hit-and-run rate also decreased year-over-year, falling from 11.7% to 10.8% of all crashes.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 2-50.0%

1

Motorists Killed

Prior: 0%

8

Pedestrians Injured

Prior: 19-57.9%

178

Motorists Injured

Prior: 1723.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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 80 incidents in December 2021 to Thursday with 69 incidents in December 2022. Similarly, the peak hour for crashes changed from 5 p.m. with 53 incidents in the prior period to 4 p.m. with 41 incidents in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained stable with 2 incidents in both December 2021 and December 2022, maintaining a fatal crash rate of 0.51%. Total injuries decreased from 194 to 186 year-over-year. Minor injury crashes (severity B) decreased from 81 to 62, while possible injury crashes (severity C) increased from 46 to 51.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.5%
0.0%prior 2
Serious Injury9serious injury crashes2.3%
0.0%prior 9
Minor Injury62minor injury crashes15.9%
-23.5%prior 81
Possible Injury51possible injury crashes13.1%
10.9%prior 46
No Injury242no injury crashes62.2%
11.0%prior 218

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Inattention" increased by 11 incidents, from 75 to 86, representing a 14.7% rise in count. Conversely, crashes with "No improper driving" as a factor decreased by 25 incidents, from 64 to 39, a 39% reduction in count. "Driving too fast for conditions" crashes increased by 13 incidents (from 23 to 36), a 56.5% increase in count.

Officer-Reported Primary Contributing Cause

Inattention86 (22.1%)14.7%prior 75
Failed to yield right of way57 (14.7%)18.8%prior 48
No improper driving39 (10%)-39.1%prior 64
Driving too fast for conditions36 (9.3%)56.5%prior 23
Followed too closely22 (5.7%)-12.0%prior 25
Failure to keep in proper lane or running off road19 (4.9%)-26.9%prior 26
Disregarded traffic signs, signals, road markings13 (3.3%)-35.0%prior 20
Exceeded authorized speed limit11 (2.8%)-8.3%prior 12
Distracted11 (2.8%)22.2%prior 9
Other improper action10 (2.6%)11.1%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring during "Daylight" conditions increased from 169 to 185, while those in "Dark - lighted roadway" decreased from 190 to 178. Crashes on "Dry" road surfaces increased from 252 to 263, whereas crashes on "Wet" surfaces decreased from 97 to 82.

Weather

Clear240 (62.2%)
-2.4%prior 246
Rain41 (10.6%)
-2.4%prior 42
Cloudy39 (10.1%)
0.0%prior 39
Snow21 (5.4%)
-4.5%prior 22
Cloudy/Rain10 (2.6%)
-41.2%prior 17
Cloudy/Snow6 (1.6%)
Clear/Cloudy5 (1.3%)
0.0%prior 5
Snow/Sleet, hail (freezing rain or drizzle)4 (1.0%)
Snow/Blowing sand, snow4 (1.0%)
Clear/Other3 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight185 (47.7%)
9.5%prior 169
Dark - lighted roadway178 (45.9%)
-6.3%prior 190
Dusk15 (3.9%)
-21.1%prior 19
Dawn8 (2.1%)
-20.0%prior 10
Dark - roadway not lighted2 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry263 (67.6%)
4.4%prior 252
Wet82 (21.1%)
-15.5%prior 97
Snow36 (9.3%)
12.5%prior 32
Ice7 (1.8%)
-22.2%prior 9
Other1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased slightly from 743 to 748. Crashes involving Honda vehicles decreased from 121 to 109, and Toyota vehicles from 114 to 90. The 21-25 age group saw the largest increase in persons involved, rising from 108 to 132.

Top Vehicle Makes (748 vehicles)

1
HONDA109 (14.6%)
-9.9%prior 121
2
TOYOTA90 (12%)
-21.1%prior 114
3
NISSAN68 (9.1%)
6.3%prior 64
4
FORD61 (8.2%)
-7.6%prior 66
5
CHEVROLET51 (6.8%)
-7.3%prior 55
6
HYUNDAI40 (5.3%)
-28.6%prior 56
7
JEEP35 (4.7%)
66.7%prior 21
8
DODGE24 (3.2%)
50.0%prior 16
9
ACURA22 (2.9%)
69.2%prior 13
10
GMC17 (2.3%)
41.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (895 persons with recorded sex)

Male495 (55.3%)
5.5%prior 469
Female400 (44.7%)
-2.9%prior 412

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones increased from 104 to 132, and this zone recorded 2 fatal crashes in the current period compared to 0 in the prior period. Conversely, crashes in 35 mph zones decreased from 94 to 72. The 30 mph zone saw a slight increase in crashes from 130 to 132, but its fatal crash count decreased from 1 to 0.

Fatal crashes by zone: 25 mph: 2 of 132 (1.515%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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: 2022-12-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-12-01 through 2022-12-31 (31 days)
  • Geographic scope: SPRINGFIELD, MA
  • Total crash records analyzed: 389
  • Total persons involved: 1,021
  • Total vehicles involved: 748

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: December 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/december-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

ThatCarHitMe.com · An Injuria.ai Company

Springfield, MA Crash Report — December 2022 | ThatCarHitMe.com