Yearly Traffic Safety Analysis

988 CRASHES IN
PITTSFIELD, MA
2025

All metrics benchmarked against2024

In 2025, Pittsfield recorded 988 total traffic crashes, an increase of 6.9% from the 924 crashes reported in 2024. While the number of fatalities remained unchanged at 3 for both years, the total number of injuries decreased from 273 to 244. The most significant year-over-year change was a 75% increase in crashes involving speeding, which rose from 20 in 2024 to 35 in 2025.

988

6.9%was 924

Total Crash Events

3

Persons Killed

244

-10.6%was 273

Persons Injured

65

14.0%was 57

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 50 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes in Pittsfield increased by 6.9% from 924 in 2024 to 988 in 2025. Despite the rise in total incidents, the number of resulting injuries saw a decrease of 10.6%, falling from 273 to 244. The number of fatalities held steady at 3 in both periods.

65

Hit-and-Run Crashes — 2025

14.0% vs prior (57)

The number of hit-and-run incidents increased in 2025 compared to the prior year. There were 65 hit-and-run crashes recorded in 2025, a 14.0% rise from the 57 incidents in 2024. This represents an upward trend in the hit-and-run rate, which grew from 6.2% of all crashes in 2024 to 6.6% in 2025.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 1100.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 10.0%

0

Other Killed

Prior: 1-100.0%

12

Pedestrians Injured

Prior: 15-20.0%

20

Cyclists Injured

Prior: 1266.7%

211

Motorists Injured

Prior: 242-12.8%

1

Other Injured

Prior: 4-75.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained largely consistent year-over-year, with Tuesday being the peak day for collisions in both 2025 (172 crashes) and 2024 (165 crashes). However, the peak hour for crashes shifted slightly later, from the 3 p.m. hour in 2024 (75 crashes) to the 4 p.m. hour in 2025 (90 crashes). The afternoon commute period continues to see the highest concentration of traffic incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity shifted slightly towards less severe outcomes in 2025 compared to 2024. While the number of fatal crashes remained constant at 3, the proportion of crashes resulting in no injuries increased from 71.6% to 74.6% of all incidents. Correspondingly, the share of crashes involving possible injuries decreased from 6.6% to 5.0%, and serious injury crashes fell from 1.8% to 1.6% of the total.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.3%
0.0%prior 3
Serious Injury16serious injury crashes1.6%
-5.9%prior 17
Minor Injury133minor injury crashes13.5%
7.3%prior 124
Possible Injury49possible injury crashes5%
-19.7%prior 61
No Injury737no injury crashes74.6%
11.3%prior 662

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes in Pittsfield remained consistent, with 'Inattention' and 'Failed to yield right of way' being the top two cited driver actions after 'No improper driving' in both 2025 and 2024. The number of crashes attributed to 'Inattention' increased by 19.7%, from 147 to 176 incidents. Notably, crashes where 'Driving too fast for conditions' was a factor more than doubled, rising from 10 in 2024 to 23 in 2025, a 130% increase in count.

Officer-Reported Primary Contributing Cause

No improper driving275 (27.8%)15.1%prior 239
Inattention176 (17.8%)19.7%prior 147
Failed to yield right of way109 (11%)0.9%prior 108
Disregarded traffic signs, signals, road markings48 (4.9%)-5.9%prior 51
Followed too closely47 (4.8%)-20.3%prior 59
Other improper action38 (3.8%)46.2%prior 26
Failure to keep in proper lane or running off road34 (3.4%)-26.1%prior 46
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner32 (3.2%)18.5%prior 27
Driving too fast for conditions23 (2.3%)130.0%prior 10
Distracted20 (2%)-20.0%prior 25

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions in 2025 were very similar to those in 2024, with the majority of incidents occurring in favorable environments. In 2025, 70.8% of crashes happened during daylight, compared to 71.2% in the prior year. Crashes on dry roads accounted for 78.5% of the total in 2025, a slight decrease from a 79.6% share in 2024, while incidents in clear weather made up 71.4% of crashes, down from 73.4%.

Weather

Clear705 (71.9%)
4.0%prior 678
Cloudy126 (12.9%)
31.3%prior 96
Rain37 (3.8%)
-11.9%prior 42
Snow36 (3.7%)
44.0%prior 25
Cloudy/Rain14 (1.4%)
-12.5%prior 16
Cloudy/Snow12 (1.2%)
140.0%prior 5
Rain/Cloudy10 (1.0%)
100.0%prior 5
Snow/Sleet, hail (freezing rain or drizzle)9 (0.9%)
80.0%prior 5
Snow/Blowing sand, snow7 (0.7%)
40.0%prior 5
Snow/Cloudy4 (0.4%)
-42.9%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight700 (71.3%)
6.4%prior 658
Dark - lighted roadway201 (20.5%)
3.6%prior 194
Dark - roadway not lighted32 (3.3%)
39.1%prior 23
Dusk23 (2.3%)
4.5%prior 22
Dawn16 (1.6%)
33.3%prior 12
Dark - unknown roadway lighting8 (0.8%)
14.3%prior 7
Other2 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry776 (79.2%)
5.4%prior 736
Wet112 (11.4%)
-6.7%prior 120
Snow49 (5.0%)
22.5%prior 40
Ice39 (4.0%)
85.7%prior 21
Slush3 (0.3%)
Water (standing, moving)1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes showed high consistency, with Toyota, Ford, and Honda remaining among the top three most common makes in both 2025 and 2024. Regarding the demographics of persons involved, there was a notable shift in the age distribution. The 65+ age group saw its count increase from 275 to 321, becoming the largest represented age cohort in 2025, while involvement of the 16-20 age group also grew from 159 to 206 persons.

Top Vehicle Makes (1,835 vehicles)

1
TOYOTA283 (15.4%)
5.2%prior 269
2
HONDA190 (10.4%)
8.0%prior 176
3
FORD185 (10.1%)
0.0%prior 185
4
CHEVROLET160 (8.7%)
8.1%prior 148
5
SUBARU156 (8.5%)
25.8%prior 124
6
NISSAN130 (7.1%)
-7.1%prior 140
7
HYUNDAI107 (5.8%)
44.6%prior 74
8
JEEP91 (5%)
37.9%prior 66
9
MAZDA51 (2.8%)
4.1%prior 49
10
VOLKSWAGEN41 (2.2%)
32.3%prior 31

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (1,835 persons with recorded sex)

Male1,037 (56.5%)
5.4%prior 984
Female798 (43.5%)
-0.7%prior 804

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones remained concentrated in the 25 to 35 mph range for both periods. In 2025, the number of crashes in 30 mph zones decreased to 325 from 342 the previous year, while crashes in 25 mph zones increased from 187 to 204. There was a notable concentration of fatal crashes in 2025, with two occurring in the 35 mph zone, whereas in 2024, the three fatal crashes with recorded speed limits were spread across the 25, 30, and 40 mph zones.

Fatal crashes by zone: 35 mph: 2 of 214 (0.935%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: PITTSFIELD, MA
  • Total crash records analyzed: 988
  • Total persons involved: 2,080
  • Total vehicles involved: 1,835

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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/pittsfield/2025-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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Pittsfield, MA Crash Report — 2025 | ThatCarHitMe.com