Monthly Traffic Safety Analysis

25 CRASHES IN
NORTHAMPTON, MA
APRIL 2025

All metrics benchmarked againstApril 2024

In April 2025, NORTHAMPTON experienced 25 total crashes, a decrease of 45.65% compared to the 46 crashes recorded in April 2024. Total injuries also saw a significant reduction, falling from 18 to 8. The most notable year-over-year shift was an 83.33% decrease in speeding-related crashes, which fell from 6 to 1.

25

-45.7%was 46

Total Crash Events

0

Persons Killed

8

-55.6%was 18

Persons Injured

1

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash data for April 2025 indicates a significant downward trend in NORTHAMPTON, with total crashes decreasing by 45.65% compared to April 2024. This reduction is also reflected in a 55.56% drop in total injuries, from 18 to 8.

1

Hit-and-Run Crashes — April 2025

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both April 2024 and April 2025. However, the hit-and-run crash rate increased from 2.2% in the prior period to 4% in the current period, reflecting the overall decrease in total crashes.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

7

Motorists Injured

Prior: 16-56.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak day moving from Thursday (11 crashes) in April 2024 to Friday (5 crashes) in April 2025. Similarly, the peak crash hour changed from 6 PM (7 crashes) in April 2024 to 2 PM (4 crashes) in April 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both April 2024 and April 2025 recorded 0 total fatalities and 0 fatal crashes. However, the number of total injuries decreased from 18 in April 2024 to 8 in April 2025. The prior period included 1 serious injury crash, which was not present in the current period, while minor injury crashes increased from 4 to 7.

Outcome by Severity (Crash Events)

Minor Injury7minor injury crashes28%
75.0%prior 4
Possible Injury1possible injury crashes4%
-66.7%prior 3
No Injury16no injury crashes64%
-57.9%prior 38

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' crashes decreased from 13 to 5, a 61.5% reduction in count, and 'No improper driving' crashes decreased from 8 to 4, a 50% reduction in count. 'Failed to yield right of way' remained constant at 6 crashes, but became the top factor in April 2025. 'Driving too fast for conditions' crashes decreased by 75%, from 4 to 1, while 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' crashes increased by 100%, from 1 to 2.

Officer-Reported Primary Contributing Cause

Failed to yield right of way6 (24%)0.0%prior 6
Inattention5 (20%)-61.5%prior 13
No improper driving4 (16%)-50.0%prior 8
Followed too closely2 (8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (8%)
Operating defective equipment1 (4%)
Driving too fast for conditions1 (4%)
Other improper action1 (4%)
Failure to keep in proper lane or running off road1 (4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Daylight' conditions decreased from 35 to 19, and 'Dry' road surface crashes decreased from 27 to 19. Crashes during 'Rain' decreased from 5 to 4, and those on 'Wet' road surfaces decreased from 10 to 5. The prior period recorded 5 crashes on 'Ice' and 2 during 'Sleet, hail', conditions not observed in the current period's data.

Weather

Clear16 (64.0%)
-11.1%prior 18
Rain4 (16.0%)
-20.0%prior 5
Clear/Clear2 (8.0%)
Cloudy/Rain1 (4.0%)
Cloudy/Unknown1 (4.0%)
Snow1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash

Lighting

Daylight19 (76.0%)
-45.7%prior 35
Dark - lighted roadway3 (12.0%)
-40.0%prior 5
Dark - roadway not lighted2 (8.0%)
Dawn1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field

Road Surface

Dry19 (76.0%)
-29.6%prior 27
Wet5 (20.0%)
-50.0%prior 10
Slush1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (42 vehicles)

1
TOYOTA8 (19%)
-50.0%prior 16
2
HYUNDAI7 (16.7%)
0.0%prior 7
3
JEEP4 (9.5%)
-33.3%prior 6
4
FORD3 (7.1%)
-66.7%prior 9
5
NISSAN3 (7.1%)
6
KIA3 (7.1%)
7
SUBARU2 (4.8%)
-77.8%prior 9
8
CHEVROLET2 (4.8%)
-60.0%prior 5
9
CADI1 (2.4%)
10
VOLKSWAGEN1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records

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

Sex Distribution (48 persons with recorded sex)

Female24 (50.0%)
-68.8%prior 77
Male24 (50.0%)
-61.9%prior 63

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crash counts decreased across several speed zones year-over-year, with 25 mph zones falling from 12 to 8 crashes, and 35 mph zones decreasing from 10 to 4 crashes. Crashes in 65 mph zones also saw a reduction from 11 to 6. No fatalities were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-04-01 through 2025-04-30 (30 days)
  • Geographic scope: NORTHAMPTON, MA
  • Total crash records analyzed: 25
  • Total persons involved: 51
  • Total vehicles involved: 42

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). "NORTHAMPTON, MA Crash Intelligence Report: April 2025." Published June 21, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/northampton/april-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

ThatCarHitMe.com · An Injuria.ai Company

Northampton, MA Crash Report — April 2025 | ThatCarHitMe.com