Monthly Traffic Safety Analysis

54 CRASHES IN
NORTHAMPTON, MA
SEPTEMBER 2022

All metrics benchmarked againstSeptember 2021

Total crashes in Northampton increased from 41 in September 2021 to 54 in September 2022, marking a 31.7% rise year-over-year. A notable shift is the increase in DUI-related crashes, which rose from 0 in September 2021 to 3 in September 2022.

54

31.7%was 41

Total Crash Events

0

Persons Killed

16

60.0%was 10

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Northampton increased year-over-year, with total crashes rising by 13 incidents, from 41 in September 2021 to 54 in September 2022. This represents a 31.7% increase in crash volume for the month.

1

Hit-and-Run Crashes — September 2022

1.9% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 0%

2

Cyclists Injured

Prior: 1100.0%

12

Motorists Injured

Prior: 933.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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, with 9 crashes in September 2021 and 14 crashes in September 2022. The peak hour for crashes shifted from 2 PM with 6 crashes in September 2021 to 5 PM with 8 crashes in September 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total injuries increased by 60%, from 10 in September 2021 to 16 in September 2022. Minor injuries rose from 5 (12.2% of crashes) to 9 (16.7% of crashes), while possible injuries decreased from 4 (9.8% of crashes) to 3 (5.6% of crashes). No fatalities were reported in either September 2021 or September 2022.

Outcome by Severity (Crash Events)

Minor Injury9minor injury crashes16.7%
80.0%prior 5
Possible Injury3possible injury crashes5.6%
-25.0%prior 4
No Injury42no injury crashes77.8%
31.3%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' increased from 12 crashes in September 2021 to 14 crashes in September 2022, a 16.7% rise. 'Failed to yield right of way' saw a significant increase, from 3 crashes to 7 crashes, representing a 133.3% increase. 'Followed too closely' also doubled, rising from 3 crashes to 6 crashes.

Officer-Reported Primary Contributing Cause

Inattention14 (25.9%)16.7%prior 12
Failed to yield right of way7 (13%)
Followed too closely6 (11.1%)
Glare3 (5.6%)
No improper driving3 (5.6%)-40.0%prior 5
Failure to keep in proper lane or running off road3 (5.6%)
Other improper action3 (5.6%)
Disregarded traffic signs, signals, road markings2 (3.7%)
Fatigued/asleep2 (3.7%)
Over-correcting/over-steering2 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 31 in September 2021 to 39 in September 2022. Crashes under 'Daylight' conditions increased from 35 to 38, while those in 'Dark - lighted roadway' conditions quadrupled from 2 to 8. Crashes on 'Dry' road surfaces rose from 37 to 46, and on 'Wet' surfaces from 4 to 7.

Weather

Clear39 (72.2%)
25.8%prior 31
Cloudy4 (7.4%)
Clear/Unknown3 (5.6%)
Rain/Cloudy2 (3.7%)
Clear/Other2 (3.7%)
Rain2 (3.7%)
Cloudy/Clear1 (1.9%)
Cloudy/Rain1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash

Lighting

Daylight38 (70.4%)
8.6%prior 35
Dark - lighted roadway8 (14.8%)
Dark - roadway not lighted4 (7.4%)
Dusk4 (7.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field

Road Surface

Dry46 (85.2%)
24.3%prior 37
Wet7 (13.0%)
Sand, mud, dirt, oil, gravel1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 74 in September 2021 to 103 in September 2022. Honda saw the largest increase in involvement among top makes, rising from 9 vehicles to 19, while Toyota involvement increased from 16 to 18. The 16-20 age group saw a decrease in persons involved, from 24 to 12, while the 65+ age group increased from 13 to 23 persons.

Top Vehicle Makes (103 vehicles)

1
HONDA19 (18.4%)
111.1%prior 9
2
TOYOTA18 (17.5%)
12.5%prior 16
3
FORD12 (11.7%)
71.4%prior 7
4
SUBARU9 (8.7%)
5
NISSAN9 (8.7%)
6
HYUNDAI7 (6.8%)
40.0%prior 5
7
BUIC4 (3.9%)
8
CHEVROLET4 (3.9%)
9
VOLKSWAGEN4 (3.9%)
10
KIA3 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records

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

Sex Distribution (121 persons with recorded sex)

Male62 (51.2%)
-10.1%prior 69
Female59 (48.8%)
43.9%prior 41

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones increased by 62.5%, from 16 in September 2021 to 26 in September 2022. Crashes in 30 mph zones doubled from 5 to 10, and in 65 mph zones increased from 3 to 4. There were no fatal crashes reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-09-01 through 2022-09-30 (30 days)
  • Geographic scope: NORTHAMPTON, MA
  • Total crash records analyzed: 54
  • Total persons involved: 132
  • Total vehicles involved: 103

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 2022." Published June 21, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/northampton/september-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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Northampton, MA Crash Report — September 2022 | ThatCarHitMe.com