Yearly Traffic Safety Analysis

575 CRASHES IN
NORTHAMPTON, MA
2023

All metrics benchmarked against2022

In 2023, Northampton recorded 575 total traffic crashes, a 7.5% increase from the 535 crashes documented in 2022. While fatalities remained stable with one death in each period, total injuries rose by 13.3% from 135 to 153. The most notable year-over-year shift was a 45.9% increase in the count of crashes attributed to 'Followed too closely', which grew from 37 incidents in 2022 to 54 in 2023.

575

7.5%was 535

Total Crash Events

1

Persons Killed

153

13.3%was 135

Persons Injured

13

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 5 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Northampton indicates a rising trend in traffic incidents year-over-year. Total crashes increased by 7.5%, from 535 in 2022 to 575 in 2023. Similarly, the number of people injured in these incidents grew by 13.3%, from 135 to 153, while the number of fatalities held steady at one for both years.

13

Hit-and-Run Crashes — 2023

0.0% vs prior (13)

The frequency of hit-and-run incidents remained stable year-over-year. There were 13 hit-and-run crashes recorded in 2023, the same number as in 2022. Due to the overall increase in total crashes, the hit-and-run rate experienced a slight decrease, from 2.4% of all crashes in 2022 to 2.3% in 2023.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

11

Pedestrians Injured

Prior: 757.1%

9

Cyclists Injured

Prior: 812.5%

132

Motorists Injured

Prior: 12010.0%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed a distinct shift between the two periods. In 2023, the peak day for crashes was Tuesday with 102 incidents, a change from Wednesday (104 incidents) in 2022. A more significant change occurred in the peak hour, which moved from the 5 p.m. hour in 2022 (53 crashes) to the 2 p.m. hour in 2023, with a higher concentration of 69 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the number of fatal crashes remained constant at one in both 2022 and 2023, the distribution of injury crashes changed. Crashes resulting in serious injuries decreased from 7 (1.3% of total) in 2022 to 5 (0.9% of total) in 2023. Conversely, minor injury crashes increased in both count and proportion, rising from 75 incidents (14.0% of total) to 89 incidents (15.5% of total).

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
0.0%prior 1
Serious Injury5serious injury crashes0.9%
-28.6%prior 7
Minor Injury89minor injury crashes15.5%
18.7%prior 75
Possible Injury31possible injury crashes5.4%
-11.4%prior 35
No Injury444no injury crashes77.2%
6.7%prior 416

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the leading contributing factor in both years, with its crash count increasing by 17.5% from 126 in 2022 to 148 in 2023. The top four factors kept their rankings, but there were significant year-over-year increases in the counts for other key factors. Crashes attributed to 'Failed to yield right of way' rose by 25.9% (from 58 to 73), and incidents involving 'Followed too closely' increased by 45.9% (from 37 to 54).

Officer-Reported Primary Contributing Cause

Inattention148 (25.7%)17.5%prior 126
No improper driving108 (18.8%)1.9%prior 106
Failed to yield right of way73 (12.7%)25.9%prior 58
Followed too closely54 (9.4%)45.9%prior 37
Failure to keep in proper lane or running off road25 (4.3%)-3.8%prior 26
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner24 (4.2%)41.2%prior 17
Other improper action19 (3.3%)5.6%prior 18
Distracted19 (3.3%)-9.5%prior 21
Disregarded traffic signs, signals, road markings16 (2.8%)-5.9%prior 17
Driving too fast for conditions15 (2.6%)-6.3%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Year-over-year data shows a notable increase in crashes occurring under adverse road conditions. The number of crashes on wet road surfaces grew by 43.9%, from 66 in 2022 to 95 in 2023, increasing their share of total crashes from 12.3% to 16.5%. Crashes in daylight conditions increased from 392 to 439, representing a slight proportional increase from 73.3% to 76.3% of all incidents.

Weather

Clear389 (68.6%)
-1.0%prior 393
Cloudy71 (12.5%)
73.2%prior 41
Rain36 (6.3%)
24.1%prior 29
Cloudy/Rain16 (2.8%)
60.0%prior 10
Snow11 (1.9%)
-8.3%prior 12
Rain/Cloudy9 (1.6%)
50.0%prior 6
Snow/Sleet, hail (freezing rain or drizzle)5 (0.9%)
Sleet, hail (freezing rain or drizzle)5 (0.9%)
-66.7%prior 15
Clear/Other4 (0.7%)
-42.9%prior 7
Clear/Unknown4 (0.7%)
-20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight439 (76.5%)
12.0%prior 392
Dark - lighted roadway78 (13.6%)
1.3%prior 77
Dark - roadway not lighted30 (5.2%)
-6.3%prior 32
Dusk19 (3.3%)
-26.9%prior 26
Dawn6 (1.0%)
Dark - unknown roadway lighting2 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry451 (78.6%)
6.6%prior 423
Wet95 (16.6%)
43.9%prior 66
Ice12 (2.1%)
-47.8%prior 23
Snow10 (1.7%)
-47.4%prior 19
Slush6 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—maintained their rankings from 2022 to 2023, with each showing an increase in total incidents. Analysis of persons involved in crashes reveals a shift in age demographics; the proportion of individuals in the 35-44 age group increased from 13.3% of all persons in 2022 to 15.1% in 2023.

Top Vehicle Makes (1,094 vehicles)

1
TOYOTA208 (19%)
13.0%prior 184
2
HONDA147 (13.4%)
22.5%prior 120
3
FORD106 (9.7%)
8.2%prior 98
4
CHEVROLET87 (8%)
31.8%prior 66
5
SUBARU80 (7.3%)
-17.5%prior 97
6
NISSAN61 (5.6%)
-1.6%prior 62
7
HYUNDAI56 (5.1%)
7.7%prior 52
8
JEEP39 (3.6%)
11.4%prior 35
9
VOLKSWAGEN35 (3.2%)
12.9%prior 31
10
MAZDA27 (2.5%)
50.0%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (1,255 persons with recorded sex)

Male678 (54.0%)
21.3%prior 559
Female577 (46.0%)
11.0%prior 520

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones shifted between 2022 and 2023. There was a notable increase in crashes within 25 mph zones, which rose from 181 incidents in 2022 to 210 in 2023. Crashes in 35 mph zones also increased from 106 to 133, while incidents in 30 mph zones decreased from 121 to 103. The single fatal crash in 2023 occurred in a 30 mph zone, whereas the fatal crash in 2022 was in a 25 mph zone.

Fatal crashes by zone: 30 mph: 1 of 103 (0.971%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: NORTHAMPTON, MA
  • Total crash records analyzed: 575
  • Total persons involved: 1,322
  • Total vehicles involved: 1,094

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/northampton/2023-annual-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 — 2023 | ThatCarHitMe.com