Yearly Traffic Safety Analysis

456 CRASHES IN
BROOKLINE, MA
2025

All metrics benchmarked against2024

In 2025, Brookline recorded 456 total crashes, an 8.8% increase from the 419 crashes reported in 2024. Total injuries saw a slight rise from 178 to 181, while fatalities remained stable at one death in each period. The most significant year-over-year change was a 65% increase in crashes involving bicycles, which rose from 20 in 2024 to 33 in 2025.

456

8.8%was 419

Total Crash Events

1

Persons Killed

181

1.7%was 178

Persons Injured

30

15.4%was 26

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 7 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 Brookline trended upward, increasing by 8.8% from 419 in 2024 to 456 in 2025. While total fatalities were unchanged year-over-year, the number of persons injured rose slightly from 178 to 181. This indicates a rise in crash frequency, though not a corresponding rise in fatal outcomes.

30

Hit-and-Run Crashes — 2025

15.4% vs prior (26)

Hit-and-run incidents increased from 2024 to 2025. The total count of hit-and-run crashes rose by 15.4%, from 26 to 30. The hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also trended upward, increasing from 6.2% in 2024 to 6.6% in 2025.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 10.0%

0

Other Killed

Prior: 00.0%

22

Pedestrians Injured

Prior: 214.8%

28

Cyclists Injured

Prior: 2133.3%

127

Motorists Injured

Prior: 134-5.2%

4

Other Injured

Prior: 2100.0%

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 showed some shifts between the two periods. The peak day for crashes moved from Thursday (74 crashes) in 2024 to Friday (87 crashes) in 2025. However, the peak hour for collisions remained consistent, with the 8 AM hour having the highest frequency in both years, recording 41 crashes in 2024 and 42 in 2025.

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 severity of crashes shifted slightly year-over-year. While the number of fatal crashes remained stable at one, the fatal crash rate decreased from 0.24 to 0.22. The count of serious injury crashes increased from 4 to 7, and minor injury crashes rose from 70 to 89. Consequently, the proportion of crashes resulting in any injury (fatal, serious, minor, or possible) increased from 33.6% in 2024 to 33.7% in 2025.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
0.0%prior 1
Serious Injury7serious injury crashes1.5%
75.0%prior 4
Minor Injury89minor injury crashes19.5%
27.1%prior 70
Possible Injury57possible injury crashes12.5%
-10.9%prior 64
No Injury295no injury crashes64.7%
20.9%prior 244

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 top two contributing factors remained 'No improper driving' and 'Failed to yield right of way' in both years, with counts for both increasing. The count of crashes where 'No improper driving' was cited rose by 15% from 113 to 130. A notable change was the 87.5% increase in the count of crashes attributed to 'Disregarded traffic signs, signals, road markings,' which grew from 16 in 2024 to 30 in 2025, moving it from the fifth-ranked factor to the fourth.

Officer-Reported Primary Contributing Cause

No improper driving130 (28.5%)15.0%prior 113
Failed to yield right of way70 (15.4%)7.7%prior 65
Followed too closely31 (6.8%)-8.8%prior 34
Disregarded traffic signs, signals, road markings30 (6.6%)87.5%prior 16
Failure to keep in proper lane or running off road26 (5.7%)30.0%prior 20
Inattention12 (2.6%)-14.3%prior 14
Other improper action12 (2.6%)20.0%prior 10
Made an improper turn12 (2.6%)33.3%prior 9
Distracted9 (2%)-25.0%prior 12
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner9 (2%)

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

Crashes were more concentrated in clear conditions in 2025 compared to the prior year. Collisions during daylight hours made up 78.3% of all crashes in 2025, up from a 72.3% share in 2024. Correspondingly, crashes on wet roads decreased in both count, from 70 to 57, and as a percentage of total crashes, from 16.7% to 12.5%.

Weather

Clear327 (71.9%)
14.3%prior 286
Cloudy40 (8.8%)
0.0%prior 40
Rain33 (7.3%)
-29.8%prior 47
Clear/Clear20 (4.4%)
11.1%prior 18
Snow14 (3.1%)
27.3%prior 11
Cloudy/Rain4 (0.9%)
-20.0%prior 5
Rain/Cloudy2 (0.4%)
Cloudy/Clear2 (0.4%)
Rain/Fog, smog, smoke2 (0.4%)
Rain/Rain2 (0.4%)

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

Lighting

Daylight357 (78.3%)
17.8%prior 303
Dark - lighted roadway87 (19.1%)
-7.4%prior 94
Dusk5 (1.1%)
-68.8%prior 16
Dark - roadway not lighted3 (0.7%)
Dark - unknown roadway lighting2 (0.4%)
Dawn2 (0.4%)

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

Road Surface

Dry370 (81.5%)
12.5%prior 329
Wet57 (12.6%)
-18.6%prior 70
Snow17 (3.7%)
13.3%prior 15
Ice5 (1.1%)
Other4 (0.9%)
Slush1 (0.2%)

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 were Toyota, Honda, and Ford in both years, though their order shifted. Honda involvement saw a significant 37.8% increase from 82 to 113 vehicles. Analysis of person age distribution shows a notable 45.1% increase in the number of individuals aged 55-64 involved in crashes, rising from 82 in 2024 to 119 in 2025.

Top Vehicle Makes (815 vehicles)

1
TOYOTA145 (17.8%)
0.7%prior 144
2
HONDA113 (13.9%)
37.8%prior 82
3
FORD71 (8.7%)
-11.3%prior 80
4
SUBARU48 (5.9%)
26.3%prior 38
5
NISSAN40 (4.9%)
42.9%prior 28
6
CHEVROLET30 (3.7%)
-43.4%prior 53
7
AUDI26 (3.2%)
23.8%prior 21
8
HYUNDAI26 (3.2%)
-7.1%prior 28
9
MERCEDES-BENZ25 (3.1%)
47.1%prior 17
10
KIA22 (2.7%)
57.1%prior 14

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

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

Sex Distribution (951 persons with recorded sex)

Male537 (56.5%)
10.0%prior 488
Female413 (43.4%)
20.8%prior 342
X / Unspecified1 (0.1%)

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 by speed zone remained largely consistent, with the 25 mph zone accounting for the vast majority of incidents in both periods. The number of crashes in 25 mph zones increased by 14% from 314 in 2024 to 358 in 2025. The single fatal crash in both years occurred within a 25 mph zone.

Fatal crashes by zone: 25 mph: 1 of 358 (0.279%)

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: BROOKLINE, MA
  • Total crash records analyzed: 456
  • Total persons involved: 1,069
  • Total vehicles involved: 815

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: 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/brookline/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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Brookline, MA Crash Report — 2025 | ThatCarHitMe.com