ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEEDHAM, MA · 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/needham/2025-annual-report
Yearly Traffic Safety Analysis
497 CRASHES IN
NEEDHAM, MA
2025
In 2025, Needham recorded 497 total traffic crashes, a 7.1% decrease from the 535 crashes reported in 2024. During this period, total injuries fell from 124 to 111. Notably, there were zero fatalities in 2025, compared to one fatality in the prior year, marking a significant improvement in crash outcomes.
497
▼ -7.1%was 535
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
111
▼ -10.5%was 124
Persons Injured
37
▼ -31.5%was 54
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. 14 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, traffic crashes in Needham showed a downward trend year-over-year. The total number of crashes decreased by 7.1%, from 535 in 2024 to 497 in 2025. This trend extended to crash outcomes, with total injuries declining by 10.5% from 124 to 111, and fatalities dropping from one to zero.
37
Hit-and-Run Crashes — 2025
▼ -31.5% vs prior (54)
Hit-and-run incidents saw a significant year-over-year decrease. The total number of hit-and-run crashes fell by 31.5%, from 54 in 2024 to 37 in 2025. The hit-and-run rate, which measures the proportion of total crashes that were hit-and-runs, also trended downward, declining from 10.1% in the prior year to 7.4% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
4
Pedestrians Injured
3
Cyclists Injured
104
Motorists Injured
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 timing of crashes showed some shifts between the two periods. In 2025, the peak day for collisions was Thursday with 107 incidents, a change from 2024 when Wednesday was the peak day with 100 crashes. The busiest hour for crashes also shifted one hour earlier, moving from the 4 p.m. hour in 2024 (56 crashes) to the 3 p.m. hour in 2025 (49 crashes).
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
Crash severity improved in 2025 compared to the previous year, with zero fatal crashes reported, down from one in 2024. The overall proportion of crashes resulting in any level of injury decreased from 18.1% to 16.3%. This was driven by a drop in serious injury crashes (from 8 to 6) and possible injury crashes (from 31 to 13), while the share of no-injury crashes rose from 78.5% to 80.9%.
Outcome by Severity (Crash Events)
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 shifted in rank and count year-over-year. Crashes attributed to 'Inattention' increased by 17.1% from 70 to 82 incidents, moving it from the third to the second-ranked cause. In contrast, crashes involving 'Failed to yield right of way' decreased by 23.9% in count (from 88 to 67), dropping it from second to third place. The count of crashes due to 'Followed too closely' also increased from 48 to 54.
Officer-Reported Primary Contributing Cause
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 remained largely consistent between 2024 and 2025. In both years, the vast majority of crashes occurred in daylight (76.5% in 2025 vs. 76.1% in 2024) and on dry road surfaces (83.1% in 2025 vs. 81.5% in 2024). The proportion of crashes happening during clear weather was also stable, accounting for approximately 77% of all incidents in both periods, indicating no significant shifts in the prevalence of adverse conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained unchanged between 2024 and 2025, though the count for each decreased in line with the overall reduction in collisions. An analysis of persons involved in crashes shows a demographic shift, with the proportion of individuals aged 65 and older increasing from 12.5% of all persons in 2024 to 14.6% in 2025. Conversely, the share of persons in the 35-44 age group decreased from 14.8% to 13.2%.
Top Vehicle Makes (929 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
120 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (967 persons with recorded sex)
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 different speed zones shifted between the two years. In 2025, a larger proportion of crashes occurred in 30 mph zones, which accounted for 63.2% of incidents with a recorded speed limit, up from 58.0% in 2024. Conversely, the share of crashes in 55 mph zones decreased from 18.9% to 16.8%. The single fatal crash recorded in 2024 occurred in a 55 mph zone; no fatal crashes were reported in any speed zone in 2025.
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: NEEDHAM, MA
- Total crash records analyzed: 497
- Total persons involved: 1,097
- Total vehicles involved: 929
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: 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/needham/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved