Yearly Traffic Safety Analysis

1,454 CRASHES IN
MEDFORD, MA
2023

All metrics benchmarked against2022

In Medford, total vehicle crashes increased by 24.2% from 1,171 in 2022 to 1,454 in 2023. While the number of crashes and injuries rose, the number of fatalities decreased from three to one year-over-year. The most notable shift was a 39.7% increase in crashes occurring in 25 mph speed zones, which rose from 683 incidents in 2022 to 954 in 2023.

1,454

24.2%was 1,171

Total Crash Events

1

-66.7%was 3

Persons Killed

323

21.0%was 267

Persons Injured

261

26.1%was 207

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. 131 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

Crash data indicates a rising trend in Medford from 2022 to 2023. Total crashes increased from 1,171 to 1,454, a 24.2% rise. Similarly, total injuries grew by 21.0%, from 267 to 323, while total fatalities declined from three to one.

261

Hit-and-Run Crashes — 2023

26.1% vs prior (207)

Hit-and-run incidents increased from 2022 to 2023. The total count of hit-and-run crashes rose by 26.1%, from 207 to 261. The hit-and-run rate, as a percentage of all crashes, also saw a slight uptick from 17.7% in 2022 to 18.0% in 2023, indicating this crash type grew at a slightly faster pace than total crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 2-50.0%

0

Other Killed

Prior: 00.0%

27

Pedestrians Injured

Prior: 2128.6%

21

Cyclists Injured

Prior: 1275.0%

272

Motorists Injured

Prior: 23018.3%

3

Other Injured

Prior: 4-25.0%

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

The temporal patterns of crashes shifted between the two periods. In 2023, the peak day for crashes was Friday with 235 incidents, changing from Thursday (191 incidents) in the prior year. The peak time also shifted later into the afternoon, with 4 p.m. and 5 p.m. recording the highest frequency in 2023 (117 crashes each), compared to 2 p.m. in 2022 (89 crashes).

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 increased, the severity profile showed a decrease in fatal outcomes. The number of fatal crashes dropped from three in 2022 to one in 2023, and the fatal crash rate per 100 crashes fell from 0.26 to 0.07. The proportion of crashes resulting in minor injuries saw a slight increase from 11.3% to 11.5%, while the share of serious injury crashes remained stable at 1.0% for both years.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.1%
-66.7%prior 3
Serious Injury15serious injury crashes1%
25.0%prior 12
Minor Injury167minor injury crashes11.5%
26.5%prior 132
Possible Injury84possible injury crashes5.8%
18.3%prior 71
No Injury1,056no injury crashes72.6%
24.5%prior 848

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 top three contributing factors remained the same in both years: 'No improper driving', 'Followed too closely', and 'Failed to yield right of way'. The count of crashes attributed to 'No improper driving' increased by 62.5% from 253 to 411. Crashes involving 'Followed too closely' increased in count by 10.6% from 142 to 157, while those from 'Failed to yield right of way' saw a slight decrease in count from 139 to 137.

Officer-Reported Primary Contributing Cause

No improper driving411 (28.3%)62.5%prior 253
Followed too closely157 (10.8%)10.6%prior 142
Failed to yield right of way137 (9.4%)-1.4%prior 139
Inattention87 (6%)3.6%prior 84
Failure to keep in proper lane or running off road60 (4.1%)15.4%prior 52
Other improper action57 (3.9%)-14.9%prior 67
Disregarded traffic signs, signals, road markings41 (2.8%)36.7%prior 30
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner30 (2.1%)-23.1%prior 39
Over-correcting/over-steering24 (1.7%)20.0%prior 20
Distracted21 (1.4%)10.5%prior 19

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

In both years, the majority of crashes occurred during daylight on dry roads. However, the proportion of crashes on wet roads increased from 13.7% of all incidents in 2022 to 18.1% in 2023. Similarly, crashes during rainy weather accounted for a larger share in 2023 (12.9%) compared to 2022 (9.1%), while the share of crashes in clear weather conditions remained dominant but decreased.

Weather

Clear909 (65.1%)
15.9%prior 784
Cloudy138 (9.9%)
60.5%prior 86
Rain132 (9.5%)
69.2%prior 78
Clear/Clear85 (6.1%)
13.3%prior 75
Cloudy/Rain34 (2.4%)
112.5%prior 16
Snow14 (1.0%)
-6.7%prior 15
Unknown/Unknown13 (0.9%)
0.0%prior 13
Rain/Cloudy10 (0.7%)
42.9%prior 7
Rain/Rain9 (0.6%)
Clear/Cloudy8 (0.6%)
-27.3%prior 11

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

Lighting

Daylight968 (68.2%)
26.5%prior 765
Dark - lighted roadway373 (26.3%)
23.1%prior 303
Dusk34 (2.4%)
6.3%prior 32
Dawn21 (1.5%)
23.5%prior 17
Dark - roadway not lighted17 (1.2%)
112.5%prior 8
Dark - unknown roadway lighting4 (0.3%)
-55.6%prior 9
Other3 (0.2%)

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

Road Surface

Dry1,123 (79.5%)
22.5%prior 917
Wet263 (18.6%)
63.4%prior 161
Snow11 (0.8%)
-54.2%prior 24
Ice6 (0.4%)
-64.7%prior 17
Slush5 (0.4%)
Water (standing, moving)3 (0.2%)
Sand, mud, dirt, oil, gravel1 (0.1%)
Reported but invalid1 (0.1%)

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 were consistent across both years, with Toyota, Honda, and Ford ranking first, second, and third, respectively. The 26-34 age group represented the largest number of persons involved in crashes in both 2023 (556 persons) and 2022 (492 persons). The counts of individuals involved in collisions increased across all reported age groups year-over-year.

Top Vehicle Makes (2,795 vehicles)

1
TOYOTA489 (17.5%)
31.8%prior 371
2
HONDA461 (16.5%)
32.9%prior 347
3
FORD310 (11.1%)
25.0%prior 248
4
NISSAN181 (6.5%)
14.6%prior 158
5
CHEVROLET144 (5.2%)
20.0%prior 120
6
JEEP117 (4.2%)
34.5%prior 87
7
SUBARU112 (4%)
30.2%prior 86
8
KIA71 (2.5%)
57.8%prior 45
9
HYUNDAI70 (2.5%)
9.4%prior 64
10
VOLKSWAGEN59 (2.1%)
22.9%prior 48

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

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

Sex Distribution (2,718 persons with recorded sex)

Male1,584 (58.3%)
22.5%prior 1,293
Female1,133 (41.7%)
27.2%prior 891
R1 (0.0%)
0.0%prior 1

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

Crashes became more concentrated in lower speed zones in 2023 compared to the prior year. The number of crashes in 25 mph zones increased by 39.7%, from 683 to 954, while incidents in 55 mph zones decreased from 136 to 107. The single fatal crash in 2023 occurred in a 25 mph zone, whereas the three fatal crashes in 2022 were distributed across 25, 35, and 55 mph zones.

Fatal crashes by zone: 25 mph: 1 of 954 (0.105%)

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: MEDFORD, MA
  • Total crash records analyzed: 1,454
  • Total persons involved: 3,252
  • Total vehicles involved: 2,795

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). "MEDFORD, 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/medford/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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Medford, MA Crash Report — 2023 | ThatCarHitMe.com