Monthly Traffic Safety Analysis

66 CRASHES IN
PITTSFIELD, MA
AUGUST 2024

All metrics benchmarked againstAugust 2023

Total crashes in PITTSFIELD, MA decreased from 81 in August 2023 to 66 in August 2024, representing an 18.5% reduction. The most notable shift was the increase in hit-and-run crashes, which rose from 0 in the prior period to 9 in the current period.

66

▼ -18.5%was 81

Total Crash Events

0

Persons Killed

10

▼ -54.5%was 22

Persons Injured

9

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. 9 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in PITTSFIELD, MA decreased year-over-year, with a reduction from 81 crashes in August 2023 to 66 crashes in August 2024. This represents an 18.5% decrease in total crash incidents.

9

Hit-and-Run Crashes — August 2024

13.6% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

0

Other Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 2↓-50.0%

8

Motorists Injured

Prior: 19↓-57.9%

1

Other Injured

Prior: 0→%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Wednesday, which had 22 crashes in August 2023, to Tuesday, with 14 crashes in August 2024. Similarly, the peak hour for crashes moved from 6 PM with 8 crashes in the prior period to 10 AM with 9 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total injuries decreased significantly from 22 in August 2023 to 10 in August 2024, a 54.5% reduction. While no fatalities were recorded in either period, minor injuries decreased from 10 to 4, and serious injuries decreased from 1 to 0.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes6.1%
↓-60.0%prior 10
Possible Injury6possible injury crashes9.1%
↑20.0%prior 5
No Injury47no injury crashes71.2%
↓-23.0%prior 61

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor shifted from 'Inattention' (17 crashes) in August 2023 to 'No improper driving' (20 crashes) in August 2024. Factors such as 'Inattention' decreased by 5 crashes, while 'Failure to keep in proper lane or running off road,' 'Visibility obstructed,' and 'Followed too closely' each decreased by 3 crashes.

Officer-Reported Primary Contributing Cause

No improper driving20 (30.3%)↑33.3%prior 15
Inattention12 (18.2%)↓-29.4%prior 17
Failed to yield right of way7 (10.6%)↓-12.5%prior 8
Disregarded traffic signs, signals, road markings4 (6.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (6.1%)
Failure to keep in proper lane or running off road3 (4.5%)↓-50.0%prior 6
Distracted2 (3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (3%)
Visibility obstructed2 (3%)↓-60.0%prior 5
Followed too closely1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring in clear weather conditions decreased from 62 to 48 year-over-year, while crashes in rainy conditions increased from 3 to 6. Crashes on dry road surfaces decreased from 70 to 55, but crashes on wet road surfaces remained stable at 11 in both periods. There was an increase in crashes occurring in 'Dark - lighted roadway' conditions, rising from 7 to 13.

Weather

Clear48 (75.0%)
↓-22.6%prior 62
Cloudy8 (12.5%)
↓-11.1%prior 9
Rain6 (9.4%)
Clear/Other1 (1.6%)
Clear/Unknown1 (1.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Weather condition at time of crash

Lighting

Daylight49 (75.4%)
↓-29.0%prior 69
Dark - lighted roadway13 (20.0%)
↑85.7%prior 7
Dark - roadway not lighted1 (1.5%)
Dawn1 (1.5%)
Dusk1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Lighting condition field

Road Surface

Dry55 (83.3%)
↓-21.4%prior 70
Wet11 (16.7%)
→0.0%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Road surface condition field

Vehicles & Demographics

There were significant decreases in person involvement for several age groups, notably a reduction of 24 persons in the 26-34 age group and 16 persons in the 65+ age group. Toyota remained the top vehicle make involved in crashes, increasing from 17 to 19, while Chevrolet and Hyundai involvement decreased by 8 crashes each.

Top Vehicle Makes (125 vehicles)

1
TOYOTA19 (15.2%)
↑11.8%prior 17
2
FORD16 (12.8%)
↑33.3%prior 12
3
NISSAN15 (12%)
↑7.1%prior 14
4
HONDA12 (9.6%)
↑20.0%prior 10
5
SUBARU9 (7.2%)
↓-35.7%prior 14
6
CHEVROLET8 (6.4%)
↓-50.0%prior 16
7
MAZDA7 (5.6%)
↑40.0%prior 5
8
JEEP5 (4%)
↓-37.5%prior 8
9
HYUNDAI5 (4%)
↓-61.5%prior 13
10
KIA4 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Vehicle unit records

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

Sex Distribution (119 persons with recorded sex)

Female60 (50.4%)
↓-26.8%prior 82
Male59 (49.6%)
↓-34.4%prior 90

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 38 to 24, a reduction of 14 crashes year-over-year. There was also a decrease of 4 crashes in 35 mph zones, going from 16 to 12. Conversely, crashes in 25 mph zones increased from 15 to 18.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · 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: 2024-08-01 through 2024-08-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-08-01 through 2024-08-31 (31 days)
  • Geographic scope: PITTSFIELD, MA
  • Total crash records analyzed: 66
  • Total persons involved: 149
  • Total vehicles involved: 125

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). "PITTSFIELD, MA Crash Intelligence Report: August 2024." Published June 21, 2026. Reporting period: 2024-08-01 to 2024-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/pittsfield/august-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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