Monthly Traffic Safety Analysis

65 CRASHES IN
ANDOVER, MA
JULY 2024

All metrics benchmarked againstJuly 2023

Total crashes in Andover decreased significantly from 109 in July 2023 to 65 in July 2024, representing a 40.4% reduction. Despite this substantial decrease in crash volume, the total number of injuries remained stable at 21 in both periods. The most notable shift was the overall decline in crash incidents year-over-year.

65

-40.4%was 109

Total Crash Events

0

Persons Killed

21

Persons Injured

6

-62.5%was 16

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. 3 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 a significant decrease in crash incidents in Andover, with total crashes falling by 40.4% year-over-year. The number of crashes dropped from 109 in July 2023 to 65 in July 2024, reflecting a positive trend in crash reduction.

6

Hit-and-Run Crashes — July 2024

-62.5% vs prior (16)

The number of hit-and-run crashes decreased from 16 in July 2023 to 6 in July 2024, representing a 62.5% reduction in count. The hit-and-run crash rate also declined year-over-year, falling from 14.7% of all crashes in July 2023 to 9.2% in July 2024. This indicates a positive trend with fewer hit-and-run incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

21

Motorists Injured

Prior: 210.0%

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 Tuesday in July 2023, which saw 24 incidents, to Monday in July 2024, with 14 incidents. Similarly, the peak crash hour moved from 4 PM in July 2023 (17 crashes) to 3 PM in July 2024 (10 crashes). This indicates a change in the temporal distribution of crash occurrences.

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

There were no fatal crashes or fatalities reported in either July 2023 or July 2024. The total number of injuries remained consistent at 21 in both periods, despite a 40.4% reduction in overall crashes. Serious injuries (Severity A) increased by 100% in count, from 1 crash (0.9% of crashes) in July 2023 to 2 crashes (3.1% of crashes) in July 2024.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes3.1%
100.0%prior 1
Minor Injury12minor injury crashes18.5%
-7.7%prior 13
Possible Injury3possible injury crashes4.6%
0.0%prior 3
No Injury45no injury crashes69.2%
-50.0%prior 90

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

The contributing factor 'Followed too closely' saw a significant decrease of 15 crashes (a 57.7% reduction in count), from 26 in July 2023 to 11 in July 2024. 'Failed to yield right of way' also declined by 8 crashes (a 61.5% reduction in count), from 13 to 5. Conversely, 'Inattention' increased by 2 crashes (a 22.2% increase in count), from 9 to 11, and 'Made an improper turn' doubled in count from 2 to 4 crashes.

Officer-Reported Primary Contributing Cause

Inattention11 (16.9%)22.2%prior 9
Followed too closely11 (16.9%)-57.7%prior 26
No improper driving6 (9.2%)-45.5%prior 11
Disregarded traffic signs, signals, road markings5 (7.7%)0.0%prior 5
Failed to yield right of way5 (7.7%)-61.5%prior 13
Made an improper turn4 (6.2%)
Exceeded authorized speed limit4 (6.2%)
Failure to keep in proper lane or running off road3 (4.6%)-78.6%prior 14
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (4.6%)
Driving too fast for conditions2 (3.1%)

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 accounted for a larger proportion of total crashes in July 2024 (90.8%) compared to July 2023 (72.5%). Concurrently, the proportion of crashes on wet road surfaces decreased significantly from 23.9% in July 2023 to 4.6% in July 2024. The percentage of crashes occurring during daylight hours remained stable at approximately 80% in both periods.

Weather

Clear49 (75.4%)
-21.0%prior 62
Clear/Clear10 (15.4%)
-41.2%prior 17
Cloudy2 (3.1%)
-75.0%prior 8
Cloudy/Rain2 (3.1%)
-66.7%prior 6
Rain2 (3.1%)
-80.0%prior 10

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

Lighting

Daylight52 (80.0%)
-40.9%prior 88
Dark - lighted roadway5 (7.7%)
-54.5%prior 11
Dark - roadway not lighted3 (4.6%)
-57.1%prior 7
Dusk3 (4.6%)
Dawn2 (3.1%)

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

Road Surface

Dry60 (92.3%)
-26.8%prior 82
Wet3 (4.6%)
-88.5%prior 26
Sand, mud, dirt, oil, gravel1 (1.5%)
Water (standing, moving)1 (1.5%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 209 in July 2023 to 122 in July 2024. The 16-20 age group saw a notable decrease in involved persons, dropping from 27 to 11, while the 26-34 age group also decreased from 52 to 30. However, the 65+ age group experienced a slight increase in involved persons, from 12 to 15.

Top Vehicle Makes (122 vehicles)

1
HONDA24 (19.7%)
-40.0%prior 40
2
TOYOTA20 (16.4%)
-35.5%prior 31
3
FORD13 (10.7%)
-50.0%prior 26
4
CHEVROLET6 (4.9%)
-64.7%prior 17
5
LEXUS5 (4.1%)
6
KIA5 (4.1%)
7
BMW5 (4.1%)
8
ACURA4 (3.3%)
-33.3%prior 6
9
JEEP4 (3.3%)
-60.0%prior 10
10
SUBARU4 (3.3%)
-42.9%prior 7

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

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

Sex Distribution (125 persons with recorded sex)

Male73 (58.4%)
-41.1%prior 124
Female52 (41.6%)
-45.3%prior 95

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 65 mph speed zones decreased by 16 crashes (a 34.8% reduction in count), from 46 in July 2023 to 30 in July 2024. Crashes in 30 mph zones also saw a reduction of 10 crashes (a 52.6% decrease in count), from 19 to 9. Conversely, crashes in 25 mph zones increased by 1 crash (a 9.1% increase in count), from 11 to 12. No fatal crashes were reported in any speed zone during either period.

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: ANDOVER, MA
  • Total crash records analyzed: 65
  • Total persons involved: 152
  • Total vehicles involved: 122

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). "ANDOVER, 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/andover/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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Andover, MA Crash Report — July 2024 | ThatCarHitMe.com