Monthly Traffic Safety Analysis

42 CRASHES IN
NORTHAMPTON, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

In September 2024, Northampton experienced 42 crashes, a 25% decrease from the 56 crashes reported in September 2023. While overall crashes declined, total injuries saw a 12.5% increase, rising from 16 to 18, and hit-and-run crashes increased by 50% from 2 to 3.

42

-25.0%was 56

Total Crash Events

0

Persons Killed

18

12.5%was 16

Persons Injured

3

50.0%was 2

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in Northampton decreased by 25% year-over-year, from 56 in September 2023 to 42 in September 2024. Despite this reduction in crash events, the number of total injuries increased by 12.5%, from 16 to 18.

3

Hit-and-Run Crashes — September 2024

50.0% vs prior (2)

Hit-and-run crashes increased by 50% year-over-year, rising from 2 crashes in September 2023 to 3 crashes in September 2024. This resulted in the hit-and-run rate increasing from 3.6% to 7.1% of all crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

3

Cyclists Injured

Prior: 250.0%

13

Motorists Injured

Prior: 130.0%

1

Other Injured

Prior: 10.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, though the count decreased from 13 in September 2023 to 9 in September 2024. The peak hour shifted from 3 PM with 8 crashes in the prior year to 2 PM with 6 crashes in the current year, indicating a slight change in the busiest time for incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both September 2023 and September 2024. However, the current period saw one crash resulting in a serious injury (2.4% of crashes), which was not present in the prior period. Minor injury crashes increased from 8 (14.3% share) to 10 (23.8% share), while crashes with no injuries decreased from 44 (78.6% share) to 27 (64.3% share).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.4%
Minor Injury10minor injury crashes23.8%
25.0%prior 8
Possible Injury4possible injury crashes9.5%
0.0%prior 4
No Injury27no injury crashes64.3%
-38.6%prior 44

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factors, 'No improper driving' and 'Inattention,' each remained constant at 12 crashes in both periods. 'Failed to yield right of way' crashes decreased from 11 in September 2023 to 6 in September 2024, representing a 45.5% reduction in count. Conversely, 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway' crashes increased from 1 to 2, a 100% increase in count.

Officer-Reported Primary Contributing Cause

No improper driving12 (28.6%)0.0%prior 12
Inattention12 (28.6%)0.0%prior 12
Failed to yield right of way6 (14.3%)-45.5%prior 11
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (4.8%)
Other improper action1 (2.4%)
Over-correcting/over-steering1 (2.4%)
Visibility obstructed1 (2.4%)
Operating defective equipment1 (2.4%)
Driving too fast for conditions1 (2.4%)
Made an improper turn1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 39 to 33 year-over-year. Incidents on wet road surfaces saw a substantial decrease, falling from 12 crashes in September 2023 to 4 crashes in September 2024. Crashes during daylight hours also decreased from 46 to 33, while crashes during dusk increased from 2 to 3.

Weather

Clear33 (78.6%)
-15.4%prior 39
Clear/Other2 (4.8%)
Clear/Unknown2 (4.8%)
Cloudy2 (4.8%)
-71.4%prior 7
Rain/Cloudy1 (2.4%)
Rain1 (2.4%)
Clear/Clear1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight33 (78.6%)
-28.3%prior 46
Dark - lighted roadway5 (11.9%)
0.0%prior 5
Dusk3 (7.1%)
Dark - roadway not lighted1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry38 (90.5%)
-13.6%prior 44
Wet4 (9.5%)
-66.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

The distribution of persons involved in crashes by age group shifted, with the '35-44' age group seeing a decrease from 23 to 11 persons, and the '65+' age group decreasing from 28 to 19 persons. Among vehicle makes, Toyota, which was the top make with 21 vehicles in the prior period, decreased to 9, while Honda became the most involved make with 15 vehicles, down from 20.

Top Vehicle Makes (88 vehicles)

1
HONDA15 (17%)
-25.0%prior 20
2
TOYOTA9 (10.2%)
-57.1%prior 21
3
FORD9 (10.2%)
-10.0%prior 10
4
JEEP6 (6.8%)
5
NISSAN5 (5.7%)
6
KIA4 (4.5%)
7
HYUNDAI4 (4.5%)
-42.9%prior 7
8
SUBARU4 (4.5%)
-55.6%prior 9
9
GMC3 (3.4%)
10
VOLKSWAGEN3 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

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

Sex Distribution (98 persons with recorded sex)

Male54 (55.1%)
-23.9%prior 71
Female44 (44.9%)
-20.0%prior 55

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 35 mph speed zones decreased significantly from 20 in September 2023 to 6 in September 2024. Additionally, 65 mph zones, which accounted for 5 crashes in the prior period, reported no crashes in the current period. Crashes in 25 mph zones remained stable, decreasing slightly from 18 to 17.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: NORTHAMPTON, MA
  • Total crash records analyzed: 42
  • Total persons involved: 110
  • Total vehicles involved: 88

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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/northampton/september-2024-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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Northampton, MA Crash Report — September 2024 | ThatCarHitMe.com