Yearly Traffic Safety Analysis

187 CRASHES IN
MIDDLETON, MA
2023

All metrics benchmarked against2022

In 2023, Middleton recorded 187 total vehicle crashes, a 19.1% decrease from the 231 crashes reported in 2022. While overall collisions and injuries (57 in 2023 vs. 60 in 2022) saw a decline, the most significant year-over-year change was the occurrence of two fatal crashes in 2023, whereas none were recorded in the prior year.

187

-19.0%was 231

Total Crash Events

2

Persons Killed

57

-5.0%was 60

Persons Injured

4

-42.9%was 7

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in Middleton shows a notable decrease in the total number of crashes, which fell from 231 in 2022 to 187 in 2023. Despite this 19.1% reduction in crash volume, the number of total injuries remained stable, decreasing slightly from 60 to 57. However, the city experienced two fatalities in 2023 after having zero in the previous year.

4

Hit-and-Run Crashes — 2023

-42.9% vs prior (7)

Hit-and-run incidents decreased in both count and rate from 2022 to 2023. The number of hit-and-run crashes fell from 7 to 4. Consequently, the hit-and-run rate, as a percentage of total crashes, also declined from 3.0% in 2022 to 2.1% in 2023.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 0%

57

Motorists Injured

Prior: 60-5.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal crash patterns shifted between the two periods. In 2023, the peak day for crashes was Wednesday with 35 incidents, and the peak hour was 3 PM with 26 incidents. This contrasts with 2022, when Friday was the peak day (52 crashes) and the 5 PM hour saw the most collisions (21 crashes), indicating a shift in peak crash times from the end of the work week to mid-week.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the severity of outcomes worsened in 2023. The city recorded two fatal crashes, accounting for 1.1% of all incidents, a category that was at zero in 2022. The number of serious injury crashes decreased from four to three, but the proportion of crashes involving any level of injury (from possible to fatal) increased from 18.2% in 2022 to 23.0% in 2023.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.1%
Serious Injury3serious injury crashes1.6%
-25.0%prior 4
Minor Injury23minor injury crashes12.3%
21.1%prior 19
Possible Injury15possible injury crashes8%
-21.1%prior 19
No Injury141no injury crashes75.4%
-20.8%prior 178

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors showed some changes in frequency between periods. The count of crashes attributed to "Inattention" decreased significantly, from 39 incidents in 2022 to 21 in 2023. Similarly, crashes involving "Failure to keep in proper lane or running off road" dropped from 12 to 3. Despite these decreases, "No improper driving" remained the most common factor in both years, though its count also fell from 97 to 75.

Officer-Reported Primary Contributing Cause

No improper driving75 (40.1%)-22.7%prior 97
Inattention21 (11.2%)-46.2%prior 39
Failed to yield right of way14 (7.5%)7.7%prior 13
Other improper action10 (5.3%)66.7%prior 6
Followed too closely7 (3.7%)16.7%prior 6
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway5 (2.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (2.1%)-55.6%prior 9
Visibility obstructed3 (1.6%)
Distracted3 (1.6%)-40.0%prior 5
Disregarded traffic signs, signals, road markings3 (1.6%)-40.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in both years predominantly occurred in clear weather and on dry roads, with the proportions remaining stable. However, there was a notable shift in lighting conditions. In 2023, 77.5% of crashes happened during daylight hours, a marked increase from the 66.7% reported in 2022. Correspondingly, crashes in dark but lighted conditions decreased from 60 incidents in 2022 to 31 in 2023.

Weather

Clear129 (69.0%)
-20.9%prior 163
Cloudy14 (7.5%)
-36.4%prior 22
Rain9 (4.8%)
-52.6%prior 19
Rain/Cloudy8 (4.3%)
Cloudy/Rain7 (3.7%)
Snow6 (3.2%)
20.0%prior 5
Clear/Cloudy5 (2.7%)
Clear/Unknown2 (1.1%)
Snow/Cloudy1 (0.5%)
Clear/Other1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight145 (77.5%)
-5.8%prior 154
Dark - lighted roadway31 (16.6%)
-48.3%prior 60
Dark - roadway not lighted6 (3.2%)
Dawn3 (1.6%)
-50.0%prior 6
Dusk2 (1.1%)
-75.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry144 (77.0%)
-14.3%prior 168
Wet34 (18.2%)
-24.4%prior 45
Snow5 (2.7%)
-16.7%prior 6
Ice2 (1.1%)
-75.0%prior 8
Sand, mud, dirt, oil, gravel2 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent, with Honda, Toyota, and Ford leading in both years, though Honda (54) overtook Toyota (50) for the top spot in 2023. The age distribution of persons involved in crashes also showed general stability, with no single age group experiencing a disproportionate change in representation year-over-year relative to the overall decrease in total persons involved.

Top Vehicle Makes (350 vehicles)

1
HONDA54 (15.4%)
10.2%prior 49
2
TOYOTA49 (14%)
-2.0%prior 50
3
FORD41 (11.7%)
-8.9%prior 45
4
CHEVROLET27 (7.7%)
-20.6%prior 34
5
NISSAN20 (5.7%)
-33.3%prior 30
6
JEEP18 (5.1%)
-30.8%prior 26
7
SUBARU13 (3.7%)
0.0%prior 13
8
GMC12 (3.4%)
71.4%prior 7
9
MERCEDES-BENZ12 (3.4%)
0.0%prior 12
10
BMW10 (2.9%)
0.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (415 persons with recorded sex)

Male226 (54.5%)
-16.6%prior 271
Female189 (45.5%)
-8.7%prior 207

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crash distributions across speed zones saw a general decrease, consistent with the overall trend. The largest absolute reductions occurred in 35 mph zones (down from 59 to 44 crashes) and 40 mph zones (down from 64 to 50 crashes). Critically, 2023 saw two fatal crashes in zones where none occurred in the prior year: one in a 25 mph zone and another in a 45 mph zone.

Fatal crashes by zone: 25 mph: 1 of 17 (5.882%) · 45 mph: 1 of 24 (4.167%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: MIDDLETON, MA
  • Total crash records analyzed: 187
  • Total persons involved: 426
  • Total vehicles involved: 350

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). "MIDDLETON, MA Crash Intelligence Report: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/middleton/2023-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

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Middleton, MA Crash Report — 2023 | ThatCarHitMe.com