Monthly Traffic Safety Analysis

45 CRASHES IN
GARDNER, MA
JULY 2024

All metrics benchmarked againstJuly 2023

Total crashes in Gardner increased by 28.57% year-over-year, rising from 35 in July 2023 to 45 in July 2024. Despite this increase, total fatalities remained stable at 1 for both periods. The most notable year-over-year shift was a 100% increase in total injuries, from 5 in July 2023 to 10 in July 2024.

45

28.6%was 35

Total Crash Events

1

Persons Killed

10

100.0%was 5

Persons Injured

4

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in crash activity, with total crashes rising from 35 to 45, representing a 28.57% increase. Total injuries also saw a significant upward trend, doubling from 5 to 10 year-over-year. Fatalities remained stable at 1 in both periods.

4

Hit-and-Run Crashes — July 2024

0.0% vs prior (4)

The number of hit-and-run crashes remained consistent at 4 in both July 2023 and July 2024. However, the overall hit-and-run rate decreased from 11.4% in the prior period to 8.9% in the current period. This reduction in rate is due to the increase in total crashes while the number of hit-and-run incidents stayed the same.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 1-100.0%

1

Motorists Killed

Prior: 0%

2

Cyclists Injured

Prior: 0%

8

Motorists Injured

Prior: 560.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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 Friday in July 2023, with 8 crashes, to Wednesday in July 2024, with 14 crashes. The peak hour also changed significantly, moving from 10 PM with 3 crashes in the prior period to 11 AM with 10 crashes in the current period. These changes suggest a shift in the times of day and week when crashes are most frequent.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes remained constant at 1 in both July 2023 and July 2024, though the fatal rate decreased from 2.9% to 2.2% due to an increase in overall crashes. Total injuries, however, doubled from 5 to 10 year-over-year, driven by a 250% increase in minor injuries (from 2 to 7) and a 50% decrease in possible injuries (from 2 to 1). Serious injuries remained at 1 in both periods.

Outcome by Severity (Crash Events)

Fatal1fatal crashes2.2%
0.0%prior 1
Serious Injury1serious injury crashes2.2%
0.0%prior 1
Minor Injury7minor injury crashes15.6%
250.0%prior 2
Possible Injury1possible injury crashes2.2%
-50.0%prior 2
No Injury33no injury crashes73.3%
26.9%prior 26

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' decreased slightly in count from 13 to 12, a 7.7% reduction. Conversely, 'No improper driving' crashes increased by 80% in count, rising from 5 to 9, and 'Failed to yield right of way' crashes doubled from 4 to 8. These shifts indicate changes in the primary causes associated with crashes.

Officer-Reported Primary Contributing Cause

Inattention12 (26.7%)-7.7%prior 13
No improper driving9 (20%)80.0%prior 5
Failed to yield right of way8 (17.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (6.7%)
Disregarded traffic signs, signals, road markings2 (4.4%)
Made an improper turn2 (4.4%)
Failure to keep in proper lane or running off road2 (4.4%)
Followed too closely1 (2.2%)
Exceeded authorized speed limit1 (2.2%)
Illness1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 24 in July 2023 to 36 in July 2024. Crashes on 'Dry' road surfaces also increased from 31 to 43 year-over-year. The number of crashes occurring in 'Daylight' conditions rose from 26 to 40, while crashes in 'Dark - lighted roadway' conditions remained stable at 4 for both periods.

Weather

Clear36 (80.0%)
50.0%prior 24
Clear/Cloudy4 (8.9%)
Cloudy3 (6.7%)
Cloudy/Rain1 (2.2%)
Rain1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Weather condition at time of crash

Lighting

Daylight40 (88.9%)
53.8%prior 26
Dark - lighted roadway4 (8.9%)
Dawn1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Lighting condition field

Road Surface

Dry43 (95.6%)
38.7%prior 31
Wet2 (4.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Road surface condition field

Vehicles & Demographics

The distribution of top vehicle makes saw some shifts; Toyota, which was the top make in July 2023 with 12 crashes, tied with Chevrolet in July 2024 with 11 crashes each. Subaru remained a prominent make, with 9 crashes in the prior period and 8 in the current period. The age distribution of persons involved in crashes showed a significant increase in the '0-15' age group (from 1 to 6) and the '65+' age group (from 11 to 27) year-over-year.

Top Vehicle Makes (78 vehicles)

1
CHEVROLET11 (14.1%)
83.3%prior 6
2
TOYOTA11 (14.1%)
-8.3%prior 12
3
SUBARU8 (10.3%)
-11.1%prior 9
4
FORD7 (9%)
5
HONDA4 (5.1%)
-50.0%prior 8
6
NISSAN4 (5.1%)
-20.0%prior 5
7
KIA4 (5.1%)
8
MAZDA3 (3.8%)
9
RAM3 (3.8%)
10
HD3 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Vehicle unit records

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

Sex Distribution (75 persons with recorded sex)

Male42 (56.0%)
13.5%prior 37
Female33 (44.0%)
13.8%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones doubled from 12 in July 2023 to 24 in July 2024, with no fatalities in either period for this zone. Crashes in 40 mph speed zones increased from 2 to 3, with 1 fatal crash recorded in both periods. The fatal crash rate in 40 mph zones decreased from 50% to 33.333% due to the increased number of crashes in that zone.

Fatal crashes by zone: 40 mph: 1 of 3 (33.333%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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: 2024-07-01 through 2024-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-07-01 through 2024-07-31 (31 days)
  • Geographic scope: GARDNER, MA
  • Total crash records analyzed: 45
  • Total persons involved: 92
  • Total vehicles involved: 78

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). "GARDNER, MA Crash Intelligence Report: July 2024." Published June 21, 2026. Reporting period: 2024-07-01 to 2024-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gardner/july-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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Gardner, MA Crash Report — July 2024 | ThatCarHitMe.com