Monthly Traffic Safety Analysis

421 CRASHES IN
SPRINGFIELD, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

In October 2023, there were 421 crashes, marking a 19.6% increase from the 352 crashes reported in October 2022. The most significant year-over-year shift was a substantial rise in total fatalities, from 1 to 3.

421

19.6%was 352

Total Crash Events

3

200.0%was 1

Persons Killed

216

9.6%was 197

Persons Injured

41

2.5%was 40

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 22 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in October 2023 showed an upward trend compared to the prior year, increasing by 19.6% from 352 to 421 crashes. This period also saw a notable rise in fatalities, with 3 reported compared to 1 in October 2022.

41

Hit-and-Run Crashes — October 2023

2.5% vs prior (40)

Hit-and-run crashes saw a minor increase in count from 40 in October 2022 to 41 in October 2023. However, the overall hit-and-run rate decreased from 11.4% of total crashes in the prior period to 9.7% in the current period.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 1100.0%

12

Pedestrians Injured

Prior: 6100.0%

3

Cyclists Injured

Prior: 1200.0%

201

Motorists Injured

Prior: 1905.8%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year; the peak day for crashes moved from Saturday in October 2022 (65 crashes) to Monday in October 2023 (90 crashes). Additionally, the peak crash hour shifted from 3 p.m. in the prior period (31 crashes) to 4 p.m. in the current period (43 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes increased from 1 in October 2022 (0.3% of total crashes) to 3 in October 2023 (0.7% of total crashes). While total injuries rose from 197 to 216, the share of serious injury crashes slightly decreased from 2.3% to 2.1% year-over-year.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.7%
200.0%prior 1
Serious Injury9serious injury crashes2.1%
12.5%prior 8
Minor Injury86minor injury crashes20.4%
8.9%prior 79
Possible Injury46possible injury crashes10.9%
15.0%prior 40
No Injury255no injury crashes60.6%
26.2%prior 202

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the top contributing factor, increasing from 74 crashes in October 2022 to 95 crashes in October 2023, a 28.4% rise in count. 'No improper driving' saw a substantial 87.2% increase in count, rising from 39 to 73 crashes, moving it from third to second most frequent factor.

Officer-Reported Primary Contributing Cause

Inattention95 (22.6%)28.4%prior 74
No improper driving73 (17.3%)87.2%prior 39
Failed to yield right of way67 (15.9%)26.4%prior 53
Failure to keep in proper lane or running off road28 (6.7%)-6.7%prior 30
Followed too closely23 (5.5%)21.1%prior 19
Disregarded traffic signs, signals, road markings18 (4.3%)-5.3%prior 19
Other improper action15 (3.6%)15.4%prior 13
Driving too fast for conditions15 (3.6%)66.7%prior 9
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner9 (2.1%)-40.0%prior 15
Exceeded authorized speed limit9 (2.1%)28.6%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 241 to 306 year-over-year, while crashes in rainy conditions nearly doubled from 33 to 62. The proportion of crashes occurring in daylight conditions remained the majority, increasing from 204 to 262, though crashes in 'Dark - lighted roadway' decreased slightly from 126 to 121.

Weather

Clear306 (72.9%)
27.0%prior 241
Rain62 (14.8%)
87.9%prior 33
Cloudy/Rain19 (4.5%)
-9.5%prior 21
Cloudy17 (4.0%)
-43.3%prior 30
Clear/Other4 (1.0%)
Clear/Rain3 (0.7%)
Clear/Unknown3 (0.7%)
Rain/Cloudy2 (0.5%)
-66.7%prior 6
Cloudy/Unknown1 (0.2%)
Fog, smog, smoke1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight262 (62.5%)
28.4%prior 204
Dark - lighted roadway121 (28.9%)
-4.0%prior 126
Dusk20 (4.8%)
81.8%prior 11
Dark - roadway not lighted10 (2.4%)
Dawn5 (1.2%)
0.0%prior 5
Other1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry327 (77.7%)
21.1%prior 270
Wet94 (22.3%)
17.5%prior 80

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 684 to 805 year-over-year. Honda became the most frequently involved vehicle make in October 2023 with 116 vehicles, surpassing Toyota which was highest in October 2022 with 104. The age group 35-44 saw a notable increase in persons involved, rising from 122 to 180.

Top Vehicle Makes (805 vehicles)

1
HONDA116 (14.4%)
20.8%prior 96
2
TOYOTA99 (12.3%)
-4.8%prior 104
3
NISSAN77 (9.6%)
32.8%prior 58
4
FORD68 (8.4%)
28.3%prior 53
5
HYUNDAI62 (7.7%)
51.2%prior 41
6
CHEVROLET46 (5.7%)
-11.5%prior 52
7
JEEP40 (5%)
81.8%prior 22
8
ACURA36 (4.5%)
56.5%prior 23
9
SUBARU24 (3%)
33.3%prior 18
10
DODGE20 (2.5%)
17.6%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

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

Sex Distribution (949 persons with recorded sex)

Male485 (51.1%)
22.5%prior 396
Female464 (48.9%)
20.5%prior 385

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone increased from 127 to 134, with the number of fatal crashes remaining at 1. The 35 mph speed zone experienced a rise in crashes from 90 to 114, and also saw an increase in fatal crashes from 0 to 2 year-over-year.

Fatal crashes by zone: 30 mph: 1 of 134 (0.746%) · 35 mph: 2 of 114 (1.754%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: SPRINGFIELD, MA
  • Total crash records analyzed: 421
  • Total persons involved: 1,097
  • Total vehicles involved: 805

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: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/october-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 — October 2023 | ThatCarHitMe.com