Yearly Traffic Safety Analysis

30 CRASHES IN
BROOKFIELD, MA
2024

All metrics benchmarked against2023

In 2024, Brookfield recorded 30 total crashes, a decrease from 37 crashes in 2023, representing an 18.9% reduction. Despite the overall decline in collisions, the most significant year-over-year change was the occurrence of one fatal crash in 2024, whereas none were recorded in the prior year.

30

-18.9%was 37

Total Crash Events

1

Persons Killed

6

-71.4%was 21

Persons Injured

1

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Brookfield show a year-over-year decrease. Total crashes fell by 18.9% from 37 in 2023 to 30 in 2024, and the number of people injured in crashes dropped from 21 to 6. However, this period also saw the number of fatalities rise from zero in 2023 to one in 2024.

1

Hit-and-Run Crashes — 2024

3.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

6

Motorists Injured

Prior: 21-71.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Saturday (6 crashes) in 2023 to Friday (7 crashes) in 2024. The peak hour also changed significantly, moving from the morning at 8 a.m. (5 crashes) in the prior year to the evening at 8 p.m. (4 crashes) in the current year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity changed notably year-over-year, with one fatal crash recorded in 2024, resulting in a 3.3% fatal crash rate, up from zero in 2023. Despite the new fatality, the proportion of crashes resulting in any injury decreased, with minor and possible injury crashes accounting for 16.7% of all incidents in 2024, down from a combined 35.1% in 2023. Consequently, the share of no-injury crashes increased from 62.2% to 80% of all collisions.

Outcome by Severity (Crash Events)

Fatal1fatal crashes3.3%
Minor Injury3minor injury crashes10%
-72.7%prior 11
Possible Injury2possible injury crashes6.7%
0.0%prior 2
No Injury24no injury crashes80%
4.3%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes shifted between periods. 'Inattention' was the top factor in 2023 with 13 crashes but saw its count drop by 53.8% to 6 crashes in 2024, falling to the second position. Conversely, crashes with 'No improper driving' cited increased in count from 7 to 9, becoming the most common factor in 2024. 'Physical impairment' was attributed to 3 crashes in 2024, a factor not listed among the top contributors in the prior year.

Officer-Reported Primary Contributing Cause

No improper driving9 (30%)28.6%prior 7
Inattention6 (20%)-53.8%prior 13
Physical impairment3 (10%)
Failed to yield right of way2 (6.7%)
Made an improper turn1 (3.3%)
Emotional1 (3.3%)
Operating defective equipment1 (3.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.3%)
Other improper action1 (3.3%)
Disregarded traffic signs, signals, road markings1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While total crashes decreased, the proportion of collisions occurring in adverse conditions increased year-over-year. In 2024, 43.3% of crashes happened on wet, icy, or snowy roads, compared to 27% in 2023. Similarly, crashes in low-light conditions (dark, dawn, or dusk) rose from a 35.1% share of the total in 2023 to 43.3% in 2024, while the share of crashes in clear weather and on dry roads decreased.

Weather

Clear18 (60.0%)
-37.9%prior 29
Cloudy/Rain3 (10.0%)
Rain2 (6.7%)
Snow2 (6.7%)
Clear/Cloudy2 (6.7%)
Snow/Sleet, hail (freezing rain or drizzle)1 (3.3%)
Clear/Clear1 (3.3%)
Fog, smog, smoke1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight17 (56.7%)
-29.2%prior 24
Dark - roadway not lighted9 (30.0%)
80.0%prior 5
Dawn2 (6.7%)
Dark - lighted roadway1 (3.3%)
-85.7%prior 7
Dusk1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry17 (56.7%)
-37.0%prior 27
Wet8 (26.7%)
33.3%prior 6
Ice2 (6.7%)
Snow2 (6.7%)
Slush1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (45 vehicles)

1
TOYOTA8 (17.8%)
14.3%prior 7
2
HONDA6 (13.3%)
-14.3%prior 7
3
NISSAN5 (11.1%)
4
SUBARU4 (8.9%)
5
CHEVROLET3 (6.7%)
-70.0%prior 10
6
HYUNDAI3 (6.7%)
7
VOLKSWAGEN2 (4.4%)
8
DODGE2 (4.4%)
9
FORD2 (4.4%)
-81.8%prior 11
10
JEEP2 (4.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (62 persons with recorded sex)

Female34 (54.8%)
21.4%prior 28
Male28 (45.2%)
-33.3%prior 42

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones shifted towards higher speeds in 2024. The 40 mph zone saw the highest number of crashes (11) in 2024, up from 5 in the prior year, while crashes in the 30 mph zone decreased from 11 to 4. The single fatal crash recorded in 2024 occurred in a 45 mph zone; no fatal crashes were recorded in any speed zone during 2023.

Fatal crashes by zone: 45 mph: 1 of 7 (14.286%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: BROOKFIELD, MA
  • Total crash records analyzed: 30
  • Total persons involved: 65
  • Total vehicles involved: 45

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). "BROOKFIELD, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/brookfield/2024-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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Brookfield, MA Crash Report — 2024 | ThatCarHitMe.com