Yearly Traffic Safety Analysis

51 CRASHES IN
WEST BROOKFIELD, MA
2024

All metrics benchmarked against2023

In West Brookfield, total crashes decreased from 54 in 2023 to 51 in 2024, a 5.6% reduction. During this period, there were no fatalities in either year. The most significant year-over-year change was a 61.1% decrease in the total number of people injured, which fell from 18 to 7.

51

-5.6%was 54

Total Crash Events

0

Persons Killed

7

-61.1%was 18

Persons Injured

2

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. 1 crash with unreported severity is not shown in the severity breakdown.

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

Crash data for West Brookfield indicates a downward trend from the prior year. Total crashes fell by 5.6%, from 54 in 2023 to 51 in 2024. This trend was accompanied by a substantial decrease in injuries, which dropped by 61.1% from 18 to 7, while fatalities remained at zero for both years.

2

Hit-and-Run Crashes — 2024

0.0% vs prior (2)

The number of hit-and-run incidents in West Brookfield remained unchanged, with 2 such crashes recorded in both 2024 and 2023. The hit-and-run rate, which represents the percentage of total crashes that were hit-and-runs, was stable, registering at 3.9% in 2024 compared to 3.7% in the prior year. This indicates no significant trend change in hit-and-run occurrences.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 18-61.1%

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 timing of crashes shifted between the two periods. In 2024, the peak day for crashes was Saturday with 13 incidents, a change from 2023 when Thursday was the peak day with 10 crashes. Similarly, the peak hour for crashes moved from the 4 p.m. hour in 2023 (9 crashes) to the 7 a.m. hour in 2024 (6 crashes).

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

While there were no fatal crashes in either year, the overall severity of crashes decreased. The proportion of crashes resulting in any injury fell from 24.1% in 2023 (13 out of 54 crashes) to 11.8% in 2024 (6 out of 51 crashes). However, the number of crashes involving a serious injury increased from one in 2023 to two in 2024.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes3.9%
100.0%prior 1
Minor Injury1minor injury crashes2%
-80.0%prior 5
Possible Injury3possible injury crashes5.9%
-57.1%prior 7
No Injury44no injury crashes86.3%
10.0%prior 40

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

In both years, 'No improper driving' was the most cited factor, with the count of such crashes increasing from 24 in 2023 to 33 in 2024. The count of crashes attributed to 'Followed too closely' decreased from 5 to 2, and crashes involving 'Distracted' driving fell from 4 to 2. Crashes linked to 'Inattention' also saw a notable drop from 4 incidents in 2023 to 1 in 2024.

Officer-Reported Primary Contributing Cause

No improper driving33 (64.7%)37.5%prior 24
Distracted2 (3.9%)
Followed too closely2 (3.9%)-60.0%prior 5
Made an improper turn2 (3.9%)
Other improper action2 (3.9%)
Illness1 (2%)
Inattention1 (2%)
Physical impairment1 (2%)
Emotional1 (2%)
Failed to yield right of way1 (2%)

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

The conditions under which crashes occurred showed some variation year-over-year. The proportion of crashes happening in daylight remained relatively stable, accounting for 66.7% in 2024 compared to 70.4% in 2023. Similarly, crashes on dry roads made up 66.7% of the total in 2024 versus 72.2% in 2023. A more noticeable change was in weather conditions, where the share of crashes during clear weather decreased from 74.1% of all incidents in 2023 to 54.9% in 2024.

Weather

Clear28 (56.0%)
-30.0%prior 40
Clear/Other6 (12.0%)
Snow/Sleet, hail (freezing rain or drizzle)3 (6.0%)
Cloudy3 (6.0%)
-40.0%prior 5
Rain3 (6.0%)
-40.0%prior 5
Rain/Other2 (4.0%)
Clear/Clear1 (2.0%)
Rain/Cloudy1 (2.0%)
Sleet, hail (freezing rain or drizzle)/Severe crosswinds1 (2.0%)
Snow/Blowing sand, snow1 (2.0%)

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

Lighting

Daylight34 (68.0%)
-10.5%prior 38
Dark - roadway not lighted8 (16.0%)
33.3%prior 6
Dark - lighted roadway5 (10.0%)
-28.6%prior 7
Dusk2 (4.0%)
Dark - unknown roadway lighting1 (2.0%)

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

Road Surface

Dry34 (68.0%)
-12.8%prior 39
Wet9 (18.0%)
-10.0%prior 10
Ice3 (6.0%)
Snow2 (4.0%)
Sand, mud, dirt, oil, gravel1 (2.0%)
Slush1 (2.0%)

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

Vehicles & Demographics

An analysis of the people and vehicles involved in crashes reveals shifts in demographics. The number of people aged 65 and older involved in crashes decreased from 24 in 2023 to 12 in 2024. Conversely, involvement for the 16-20 age group increased from 14 to 20 individuals. Regarding vehicle makes, Ford and Chevrolet remained among the top three most frequently involved makes in both years, with Honda replacing Toyota in the top three for 2024.

Top Vehicle Makes (75 vehicles)

1
FORD14 (18.7%)
7.7%prior 13
2
CHEVROLET13 (17.3%)
18.2%prior 11
3
HONDA9 (12%)
80.0%prior 5
4
SUBARU6 (8%)
20.0%prior 5
5
TOYOTA6 (8%)
-45.5%prior 11
6
JEEP4 (5.3%)
-33.3%prior 6
7
NISSAN3 (4%)
-66.7%prior 9
8
HYUNDAI3 (4%)
9
GMC2 (2.7%)
10
MITS2 (2.7%)

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

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

Sex Distribution (86 persons with recorded sex)

Male59 (68.6%)
18.0%prior 50
Female27 (31.4%)
-30.8%prior 39

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 remained broadly consistent year-over-year. In both 2024 and 2023, the 40 mph speed zone saw the highest number of crashes, with 18 and 17 incidents respectively. There was a decrease in crashes occurring in zones with speed limits of 30 mph or less, falling from 24 incidents in 2023 to 18 in 2024. No fatal crashes were recorded in any speed zone during either period.

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: WEST BROOKFIELD, MA
  • Total crash records analyzed: 51
  • Total persons involved: 89
  • Total vehicles involved: 75

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). "WEST 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/west-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

ThatCarHitMe.com · An Injuria.ai Company

West Brookfield, MA Crash Report — 2024 | ThatCarHitMe.com