ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BROOKLINE, MA · JULY 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/brookline/july-2025-report
Monthly Traffic Safety Analysis
28 CRASHES IN
BROOKLINE, MA
JULY 2025
In July 2025, BROOKLINE experienced 28 total crashes, a decrease of 17.65% compared to the 34 crashes recorded in July 2024. This period also saw a notable 35% reduction in total injuries, falling from 20 to 13. The most significant shift was the increase in crashes attributed to disregarding traffic signs, signals, or road markings, which rose from 1 to 5.
28
▼ -17.6%was 34
Total Crash Events
0
Persons Killed
13
▼ -35.0%was 20
Persons Injured
2
▲ 100.0%was 1
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for BROOKLINE indicates a downward trend year-over-year, with total crashes decreasing by 17.65% from 34 to 28. Similarly, the number of total injuries also decreased, falling by 35% from 20 to 13. Fatalities remained at zero in both periods.
2
Hit-and-Run Crashes — July 2025
▲ 100.0% vs prior (1)
Hit-and-run crashes increased by 100% year-over-year, rising from 1 crash in July 2024 to 2 crashes in July 2025. This resulted in an increase in the hit-and-run rate from 2.9% to 7.1%. The data indicates an upward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
2
Pedestrians Injured
1
Cyclists Injured
10
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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 Tuesday with 9 crashes in the prior period to Monday with 6 crashes in the current period. The peak hour remained 10a in both periods, though the number of crashes at this hour decreased from 7 to 5. While Monday had 6 crashes in both periods, the overall distribution of crashes across days of the week changed.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero for both periods, with no fatal crashes reported. The total number of injuries decreased from 20 to 13. The proportion of crashes resulting in Minor Injury increased from 17.6% to 25%, while crashes with Possible Injury decreased from 23.5% to 10.7%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Most severe injury per crash record
Top Contributing Factors
The count of crashes where 'No improper driving' was a factor increased from 9 to 10, and its share of total crashes rose from 26.5% to 35.7%. 'Disregarded traffic signs, signals, road markings' saw a significant increase in count from 1 to 5, raising its share from 2.9% to 17.9%. Conversely, 'Failed to yield right of way' crashes decreased by 50%, from 4 to 2, and 'Followed too closely' decreased from 4 to 3.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under clear weather conditions decreased from 28 to 24, consistent with the overall reduction in total crashes. Crashes on dry road surfaces also decreased from 31 to 27, and those on wet surfaces decreased from 3 to 1. Crashes during daylight hours decreased from 27 to 22, while crashes in 'Dark - lighted roadway' remained stable at 5.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Road surface condition field
Vehicles & Demographics
Toyota remained the most frequent vehicle make involved in crashes, with 10 vehicles in both periods. Ford vehicles involved in crashes increased from 6 to 8, while Chevrolet vehicles decreased significantly from 8 to 1. The age group 0-15 saw a substantial decrease in persons involved in crashes, from 10 to 2, while the 65+ age group increased from 6 to 12.
Top Vehicle Makes (57 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (63 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Person-level records linked to crash events
Speed Limit Zones
The majority of crashes in both periods occurred in the 25 mph speed zone, though the count decreased from 26 to 19. Crashes in the 35 mph zone increased from 2 to 3. No fatal crashes were recorded in any speed zone for either period, indicating no change in fatal rates by zone.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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: 2025-07-01 through 2025-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-07-01 through 2025-07-31 (31 days)
- Geographic scope: BROOKLINE, MA
- Total crash records analyzed: 28
- Total persons involved: 75
- Total vehicles involved: 57
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). "BROOKLINE, MA Crash Intelligence Report: July 2025." Published June 21, 2026. Reporting period: 2025-07-01 to 2025-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brookline/july-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-07-01 – 2025-07-31
Generated: June 21, 2026 · All rights reserved