Yearly Traffic Safety Analysis

672 CRASHES IN
SAUGUS, MA
2024

All metrics benchmarked against2023

In 2024, Saugus recorded 672 total crashes, a 1.2% decrease from the 680 crashes documented in 2023. While overall crashes slightly declined, the city experienced one fatal crash in 2024 compared to zero in the prior year. Notably, crashes involving speeding more than doubled, increasing from 13 in 2023 to 35 in 2024.

672

-1.2%was 680

Total Crash Events

1

Persons Killed

257

-10.1%was 286

Persons Injured

72

33.3%was 54

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Saugus show a slight year-over-year decline, with total crashes decreasing by 1.2% from 680 in 2023 to 672 in 2024. The number of people injured also fell by 10.1%, from 286 to 257. However, the city recorded one fatality in 2024, whereas there were none in the previous year.

72

Hit-and-Run Crashes — 2024

33.3% vs prior (54)

Hit-and-run incidents increased significantly in 2024 compared to the previous year. The number of hit-and-run crashes rose from 54 in 2023 to 72 in 2024, a 33.3% increase in count. Consequently, the hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, trended upward from 7.9% in 2023 to 10.7% in 2024.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

7

Pedestrians Injured

Prior: 12-41.7%

11

Cyclists Injured

Prior: 11000.0%

236

Motorists Injured

Prior: 273-13.6%

3

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Saugus shifted between 2023 and 2024. The peak day for collisions moved from Friday (105 crashes) in 2023 to Monday (111 crashes) in 2024. Similarly, the peak hour for crashes shifted one hour later, from the 5 p.m. hour in 2023 (63 crashes) to the 6 p.m. hour in 2024 (66 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity saw a notable change with the occurrence of one fatal crash in 2024, compared to zero in 2023. The number of serious injury crashes remained stable at 15 for both years. The proportion of crashes resulting in no injury increased from 63.2% of all incidents in 2023 to 66.7% in 2024, while the share of possible injury crashes decreased from 10.4% to 7.6%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.1%
Serious Injury15serious injury crashes2.2%
0.0%prior 15
Minor Injury140minor injury crashes20.8%
0.0%prior 140
Possible Injury51possible injury crashes7.6%
-28.2%prior 71
No Injury448no injury crashes66.7%
4.2%prior 430

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor in both years was 'No improper driving,' with its count increasing from 232 in 2023 to 254 in 2024. 'Followed too closely' became the second most common factor in 2024, rising in count from 70 to 80 incidents, while 'Inattention' dropped from 74 to 47 incidents. Notably, speed-related factors saw a significant increase in count; crashes attributed to 'Driving too fast for conditions' rose from 7 to 17, and those for 'Exceeded authorized speed limit' increased from 4 to 12.

Officer-Reported Primary Contributing Cause

No improper driving254 (37.8%)9.5%prior 232
Followed too closely80 (11.9%)14.3%prior 70
Inattention47 (7%)-36.5%prior 74
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner26 (3.9%)30.0%prior 20
Failed to yield right of way23 (3.4%)-8.0%prior 25
Failure to keep in proper lane or running off road23 (3.4%)-11.5%prior 26
Driving too fast for conditions17 (2.5%)142.9%prior 7
Other improper action13 (1.9%)-18.8%prior 16
Exceeded authorized speed limit12 (1.8%)
Distracted11 (1.6%)-35.3%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather on dry roads. In 2024, the proportion of crashes in clear weather increased to 74.3% from 71.2% in 2023. Crashes during dark but lighted roadway conditions increased from 168 in 2023 to 195 in 2024, representing a rise in share from 24.7% to 29.0%. Incidents on snowy road surfaces also saw a notable increase, from 5 crashes in 2023 to 20 in 2024.

Weather

Clear499 (74.3%)
3.1%prior 484
Cloudy54 (8.0%)
-37.2%prior 86
Rain50 (7.4%)
-21.9%prior 64
Snow16 (2.4%)
Clear/Clear10 (1.5%)
Clear/Cloudy9 (1.3%)
Cloudy/Rain8 (1.2%)
-46.7%prior 15
Clear/Unknown6 (0.9%)
Sleet, hail (freezing rain or drizzle)3 (0.4%)
Rain/Cloudy3 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight422 (63.0%)
-3.4%prior 437
Dark - lighted roadway195 (29.1%)
16.1%prior 168
Dusk21 (3.1%)
-30.0%prior 30
Dark - roadway not lighted16 (2.4%)
-36.0%prior 25
Dawn14 (2.1%)
7.7%prior 13
Dark - unknown roadway lighting2 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry552 (82.1%)
0.5%prior 549
Wet94 (14.0%)
-17.5%prior 114
Snow20 (3.0%)
300.0%prior 5
Slush5 (0.7%)
Ice1 (0.1%)
-83.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in crashes remained stable year-over-year, with Toyota, Honda, and Ford holding the top three spots in both 2023 and 2024. Regarding the age of persons involved in crashes, there was a noticeable increase in younger age groups. The number of individuals aged 16-20 rose from 131 to 143, and the 0-15 age group increased from 62 to 78. Conversely, the number of persons in the 26-34 and 35-44 age brackets saw a decrease.

Top Vehicle Makes (1,301 vehicles)

1
TOYOTA212 (16.3%)
-2.8%prior 218
2
HONDA188 (14.5%)
-2.6%prior 193
3
FORD130 (10%)
4.0%prior 125
4
NISSAN81 (6.2%)
-21.4%prior 103
5
JEEP75 (5.8%)
10.3%prior 68
6
CHEVROLET72 (5.5%)
-20.0%prior 90
7
SUBARU44 (3.4%)
-4.3%prior 46
8
MERCEDES-BENZ36 (2.8%)
9.1%prior 33
9
HYUNDAI35 (2.7%)
-41.7%prior 60
10
KIA32 (2.5%)
-8.6%prior 35

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (1,339 persons with recorded sex)

Male799 (59.7%)
-1.5%prior 811
Female540 (40.3%)
-5.1%prior 569

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones showed some shifts between 2023 and 2024. Crashes in 50 mph zones increased from 209 to 219, while incidents in 30 mph zones decreased from 216 to 196. The single fatal crash recorded in 2024 occurred in a 30 mph speed zone. In the prior year, there were no fatal crashes recorded in any speed zone.

Fatal crashes by zone: 30 mph: 1 of 196 (0.51%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: SAUGUS, MA
  • Total crash records analyzed: 672
  • Total persons involved: 1,553
  • Total vehicles involved: 1,301

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). "SAUGUS, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/saugus/2024-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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Saugus, MA Crash Report — 2024 | ThatCarHitMe.com