Monthly Traffic Safety Analysis

44 CRASHES IN
NEEDHAM, MA
APRIL 2025

All metrics benchmarked againstApril 2024

In April 2025, Needham experienced 44 total crashes, a decrease of 6.4% compared to the 47 crashes recorded in April 2024. A significant year-over-year shift was the absence of fatalities in April 2025, down from one fatality in the prior year.

44

-6.4%was 47

Total Crash Events

0

-100.0%was 1

Persons Killed

9

-10.0%was 10

Persons Injured

2

-66.7%was 6

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for April 2025 shows a downward trend in Needham, with total crashes decreasing by 6.4% from 47 to 44. This period also saw a reduction in total fatalities from one to zero, and total injuries from 10 to 9.

2

Hit-and-Run Crashes — April 2025

-66.7% vs prior (6)

Hit-and-run crashes significantly decreased year-over-year, falling from 6 incidents in April 2024 to 2 incidents in April 2025. This reduction also led to a lower hit-and-run crash rate, dropping from 12.8% to 4.5% of all crashes.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

2

Cyclists Injured

Prior: 1100.0%

7

Motorists Injured

Prior: 70.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. In April 2025, Wednesday became the peak day for crashes with 13 incidents, compared to Thursday with 10 incidents in April 2024. The peak crash hour also moved from 11 AM with 6 crashes in the prior period to 3 PM with 7 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes showed a positive change, with no fatal crashes reported in April 2025, down from one fatal crash in April 2024. Minor injuries decreased from 7 to 5, while possible injuries increased from 1 to 2 year-over-year. The overall number of crashes resulting in any injury (minor or possible) slightly decreased from 8 to 7.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes11.4%
-28.6%prior 7
Possible Injury2possible injury crashes4.5%
100.0%prior 1
No Injury35no injury crashes79.5%
-5.4%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Failed to yield right of way' increased by 50% in count, rising from 6 crashes in April 2024 to 9 crashes in April 2025. 'Inattention' also saw an increase in count from 6 to 8 crashes, representing a 33.3% rise. Conversely, crashes attributed to 'No improper driving' decreased by 53.8% in count, from 13 to 6, while 'Followed too closely' remained constant at 8 crashes.

Officer-Reported Primary Contributing Cause

Failed to yield right of way9 (20.5%)50.0%prior 6
Followed too closely8 (18.2%)0.0%prior 8
Inattention8 (18.2%)33.3%prior 6
No improper driving6 (13.6%)-53.8%prior 13
Other improper action3 (6.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (4.5%)
Failure to keep in proper lane or running off road2 (4.5%)
Fatigued/asleep1 (2.3%)
Made an improper turn1 (2.3%)
Over-correcting/over-steering1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The conditions under which crashes occurred remained largely similar, with 'Clear' weather conditions accounting for 28 crashes in April 2025, a slight decrease from 29 in April 2024. Crashes on 'Wet' road surfaces decreased from 12 to 7, while those on 'Dry' surfaces remained constant at 34. The number of crashes occurring in 'Daylight' conditions also saw a minor decrease from 40 to 39.

Weather

Clear28 (65.1%)
-3.4%prior 29
Rain5 (11.6%)
-16.7%prior 6
Clear/Clear5 (11.6%)
Cloudy3 (7.0%)
-50.0%prior 6
Cloudy/Rain1 (2.3%)
Rain/Rain1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash

Lighting

Daylight39 (92.9%)
-2.5%prior 40
Dark - lighted roadway2 (4.8%)
Dusk1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field

Road Surface

Dry34 (81.0%)
0.0%prior 34
Wet7 (16.7%)
-41.7%prior 12
Ice1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field

Vehicles & Demographics

The distribution of persons involved in crashes showed a shift in age groups, with the '65+' group having the highest count of 21 persons in April 2025, compared to the '21-25', '45-54', and '26-34' groups each with 15 persons in April 2024. Among vehicle makes, Toyota crashes increased from 14 to 19, while Honda crashes decreased from 12 to 8. Chevrolet crashes also saw an increase from 4 to 10.

Top Vehicle Makes (86 vehicles)

1
TOYOTA19 (22.1%)
35.7%prior 14
2
CHEVROLET10 (11.6%)
3
FORD10 (11.6%)
25.0%prior 8
4
HONDA8 (9.3%)
-33.3%prior 12
5
SUBARU8 (9.3%)
6
BMW4 (4.7%)
7
FRHT3 (3.5%)
8
JEEP3 (3.5%)
9
NISSAN2 (2.3%)
10
RAM2 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records

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

Sex Distribution (96 persons with recorded sex)

Male58 (60.4%)
1.8%prior 57
Female38 (39.6%)
8.6%prior 35

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones increased from 26 in April 2024 to 30 in April 2025, while crashes in 55 mph speed zones decreased from 14 to 8. Notably, the 55 mph speed zone, which had one fatal crash in the prior period, reported zero fatalities in the current period. Overall, no fatalities were recorded in any speed zone in April 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-04-01 through 2025-04-30 (30 days)
  • Geographic scope: NEEDHAM, MA
  • Total crash records analyzed: 44
  • Total persons involved: 107
  • Total vehicles involved: 86

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). "NEEDHAM, MA Crash Intelligence Report: April 2025." Published June 21, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/needham/april-2025-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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Needham, MA Crash Report — April 2025 | ThatCarHitMe.com