Monthly Traffic Safety Analysis

36 CRASHES IN
HADLEY, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

Total crashes in December 2024 remained stable at 36, matching the 36 crashes reported in December 2023. Despite the consistent number of incidents, total injuries decreased by 66.7%, falling from 12 in the prior year to 4 in the current period. This significant reduction in injuries represents the most notable year-over-year shift in safety outcomes.

36

Total Crash Events

0

Persons Killed

4

-66.7%was 12

Persons Injured

4

300.0%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. 2 crashes with unreported severity are not shown in the severity breakdown.

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

Trend Summary

Overall, the number of crashes remained stable year-over-year, with 36 incidents reported in both December 2024 and December 2023. However, there was a substantial positive trend in injury outcomes, with total injuries decreasing by 66.7% from 12 to 4. Fatalities remained at zero in both periods.

4

Hit-and-Run Crashes — December 2024

300.0% vs prior (1)

Hit-and-run crashes significantly increased year-over-year, rising from 1 incident in December 2023 to 4 incidents in December 2024. This change represents a substantial increase in the hit-and-run rate, which climbed from 2.8% to 11.1% of all crashes. The trend for hit-and-run incidents is notably upward.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 12-66.7%

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

When Crashes Happen

The peak day for crashes shifted from Friday in December 2023, with 11 crashes, to Monday in December 2024, also with 11 crashes. The peak hour remained consistent at 2 PM in both periods, although the number of crashes at this hour decreased from 7 in the prior year to 4 in the current year. Crashes on Mondays increased significantly from 4 to 11, while crashes on Fridays decreased from 11 to 7.

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

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

Crash Severity Breakdown

Fatalities remained at zero in both December 2024 and December 2023, indicating no change in the fatal crash rate. The overall number of injuries significantly decreased from 12 in the prior period to 4 in the current period. Specifically, minor injuries (Severity B) saw a substantial reduction from 6 to 1, while serious injuries (Severity A) appeared in the current period with 1 crash, compared to none in the prior year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.8%
Minor Injury1minor injury crashes2.8%
-83.3%prior 6
Possible Injury2possible injury crashes5.6%
100.0%prior 1
No Injury30no injury crashes83.3%
3.4%prior 29

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

Inattention remained the most frequent contributing factor, increasing slightly from 11 crashes in December 2023 to 12 crashes in December 2024. "Followed too closely" crashes saw a significant decrease, dropping from 4 incidents in the prior year to 1 in the current period. Conversely, "Failed to yield right of way" crashes increased from 5 to 6, and "No improper driving" increased from 7 to 8.

Officer-Reported Primary Contributing Cause

Inattention12 (33.3%)9.1%prior 11
No improper driving8 (22.2%)14.3%prior 7
Failed to yield right of way6 (16.7%)20.0%prior 5
Physical impairment1 (2.8%)
Visibility obstructed1 (2.8%)
Other improper action1 (2.8%)
Followed too closely1 (2.8%)
Driving too fast for conditions1 (2.8%)
Over-correcting/over-steering1 (2.8%)

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

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 23 in December 2023 to 17 in December 2024, while cloudy conditions saw an increase from 6 to 11 crashes. Crashes on dry road surfaces increased from 24 to 27, whereas crashes on wet road surfaces decreased from 12 to 7. There was a notable increase in crashes during daylight hours, rising from 20 to 26, while crashes in dark conditions (lighted and unlighted combined) decreased from 15 to 10.

Weather

Clear17 (47.2%)
-26.1%prior 23
Cloudy11 (30.6%)
83.3%prior 6
Rain2 (5.6%)
Clear/Cloudy2 (5.6%)
Snow1 (2.8%)
Cloudy/Rain1 (2.8%)
Cloudy/Snow1 (2.8%)
Rain/Cloudy1 (2.8%)

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

Lighting

Daylight26 (72.2%)
30.0%prior 20
Dark - lighted roadway6 (16.7%)
-33.3%prior 9
Dark - roadway not lighted4 (11.1%)
-33.3%prior 6

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

Road Surface

Dry27 (75.0%)
12.5%prior 24
Wet7 (19.4%)
-41.7%prior 12
Sand, mud, dirt, oil, gravel1 (2.8%)
Snow1 (2.8%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes decreased slightly from 71 in December 2023 to 67 in December 2024. Honda, which was the top make with 16 vehicles in the prior period, decreased to 12 and is now tied with Toyota for the most frequently involved make. Subaru and Ford saw an increase in their involvement, with Subaru rising from 3 to 8 vehicles and Ford from 3 to 6 vehicles.

Top Vehicle Makes (67 vehicles)

1
TOYOTA12 (17.9%)
-7.7%prior 13
2
HONDA12 (17.9%)
-25.0%prior 16
3
SUBARU8 (11.9%)
4
FORD6 (9%)
5
CHEVROLET3 (4.5%)
-57.1%prior 7
6
LEXUS2 (3%)
7
HYUNDAI2 (3%)
-66.7%prior 6
8
NISSAN2 (3%)
-60.0%prior 5
9
VOLKSWAGEN2 (3%)
10
JEEP2 (3%)

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

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

Sex Distribution (69 persons with recorded sex)

Female40 (58.0%)
11.1%prior 36
Male29 (42.0%)
-19.4%prior 36

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

Speed Limit Zones

The highest frequency of crashes remained in the 35 mph speed zone, with 15 crashes in both periods. There was a shift in crashes from higher speed zones to lower ones; crashes in the 40 mph zone decreased from 8 to 5, and in the 45 mph zone from 5 to 2. Conversely, crashes in the 10 mph zone increased from 2 to 5, and crashes in the 30 mph zone increased from 2 to 4.

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

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: HADLEY, MA
  • Total crash records analyzed: 36
  • Total persons involved: 78
  • Total vehicles involved: 67

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