Monthly Traffic Safety Analysis

93 CRASHES IN
ANDOVER, MA
SEPTEMBER 2023

All metrics benchmarked againstSeptember 2022

Andover experienced a 24% increase in total crashes, rising from 75 in September 2022 to 93 in September 2023. This period also saw a notable 50% increase in hit-and-run incidents, from 8 to 12 crashes.

93

24.0%was 75

Total Crash Events

0

Persons Killed

20

25.0%was 16

Persons Injured

12

50.0%was 8

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 · 2023-09-01 to 2023-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in crash activity year-over-year. Total crashes rose from 75 in September 2022 to 93 in September 2023, representing a 24% increase. Concurrently, total injuries increased by 25%, from 16 to 20.

12

Hit-and-Run Crashes — September 2023

50.0% vs prior (8)

Hit-and-run crashes increased by 50%, rising from 8 incidents in September 2022 to 12 in September 2023. The hit-and-run rate also rose from 10.7% of all crashes in the prior period to 12.9% in the current period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

19

Motorists Injured

Prior: 1526.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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 Thursday in September 2022 (17 crashes) to Tuesday in September 2023 (22 crashes). Monday and Tuesday saw significant increases in crash counts, with Monday rising from 4 to 15 crashes and Tuesday from 10 to 22 crashes. The peak hour for crashes shifted from 3 p.m. with 10 crashes in the prior period to 5 p.m. with 7 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either September 2022 or September 2023. Serious injury crashes decreased from 2 (2.7% of total crashes) in the prior period to 1 (1.1%) in the current period. Conversely, minor injury crashes increased from 8 (10.7%) to 13 (14%), contributing to an overall rise in total injuries from 16 to 20.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.1%
-50.0%prior 2
Minor Injury13minor injury crashes14%
62.5%prior 8
Possible Injury5possible injury crashes5.4%
0.0%prior 5
No Injury71no injury crashes76.3%
22.4%prior 58

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, "Followed too closely," increased by 8 crashes, from 17 in September 2022 to 25 in September 2023. "Failure to keep in proper lane or running off road" saw a substantial increase of 7 crashes, rising from 3 to 10. Conversely, crashes attributed to "No improper driving" decreased by 6, from 19 to 13.

Officer-Reported Primary Contributing Cause

Followed too closely25 (26.9%)47.1%prior 17
No improper driving13 (14%)-31.6%prior 19
Failed to yield right of way12 (12.9%)71.4%prior 7
Failure to keep in proper lane or running off road10 (10.8%)
Inattention10 (10.8%)11.1%prior 9
Other improper action5 (5.4%)
Made an improper turn2 (2.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (2.2%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (2.2%)
Exceeded authorized speed limit1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring on wet road surfaces significantly increased from 12 in September 2022 to 33 in September 2023. Crashes during rainy conditions also rose substantially, from 9 to 25 incidents. Daylight crashes saw a minor increase from 60 to 63, while crashes in dark-lighted conditions tripled from 3 to 9.

Weather

Clear36 (38.7%)
-23.4%prior 47
Clear/Clear18 (19.4%)
100.0%prior 9
Cloudy12 (12.9%)
100.0%prior 6
Rain11 (11.8%)
37.5%prior 8
Cloudy/Rain8 (8.6%)
Severe crosswinds/Rain3 (3.2%)
Rain/Cloudy2 (2.2%)
Cloudy/Cloudy1 (1.1%)
Rain/Rain1 (1.1%)
Unknown/Unknown1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Weather condition at time of crash

Lighting

Daylight63 (68.5%)
5.0%prior 60
Dark - lighted roadway9 (9.8%)
Dawn8 (8.7%)
Dark - roadway not lighted8 (8.7%)
-11.1%prior 9
Dusk2 (2.2%)
Dark - unknown roadway lighting1 (1.1%)
Other1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Lighting condition field

Road Surface

Dry57 (63.3%)
-9.5%prior 63
Wet33 (36.7%)
175.0%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 143 to 180 year-over-year. Honda and Toyota remained the top two vehicle makes involved, with Honda increasing from 22 to 28 and Toyota from 23 to 24. The 35-44 age group saw a significant increase in persons involved, from 26 to 56, while the 21-25 age group decreased from 24 to 15.

Top Vehicle Makes (180 vehicles)

1
HONDA28 (15.6%)
27.3%prior 22
2
TOYOTA24 (13.3%)
4.3%prior 23
3
FORD14 (7.8%)
16.7%prior 12
4
CHEVROLET13 (7.2%)
62.5%prior 8
5
NISSAN11 (6.1%)
6
SUBARU10 (5.6%)
42.9%prior 7
7
VOLKSWAGEN9 (5%)
80.0%prior 5
8
DODGE6 (3.3%)
9
KIA5 (2.8%)
0.0%prior 5
10
JEEP5 (2.8%)
-28.6%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Vehicle unit records

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

Sex Distribution (184 persons with recorded sex)

Male127 (69.0%)
53.0%prior 83
Female57 (31.0%)
-9.5%prior 63

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 65 mph speed zones increased by 11, rising from 24 in September 2022 to 35 in September 2023. Crashes in 25 mph zones more than doubled, increasing from 5 to 12. Conversely, crashes in 35 mph zones decreased by 7, from 13 to 6.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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: 2023-09-01 through 2023-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-09-01 through 2023-09-30 (30 days)
  • Geographic scope: ANDOVER, MA
  • Total crash records analyzed: 93
  • Total persons involved: 214
  • Total vehicles involved: 180

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: September 2023." Published June 21, 2026. Reporting period: 2023-09-01 to 2023-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/andover/september-2023-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 — September 2023 | ThatCarHitMe.com