Yearly Traffic Safety Analysis

402 CRASHES IN
HINGHAM, MA
2025

All metrics benchmarked against2024

In Hingham, total traffic crashes increased by 12.3%, rising from 358 in 2024 to 402 in 2025. This period also saw total injuries climb from 105 to 113. The most significant year-over-year change was the registration of one fatal crash in 2025, whereas none were recorded in the prior year. Additionally, rear-end collisions increased by 42.4% to become the most common crash type, with 121 incidents compared to 85 the previous year.

402

12.3%was 358

Total Crash Events

1

Persons Killed

113

7.6%was 105

Persons Injured

23

9.5%was 21

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Hingham shows an upward trend year-over-year. The total number of crashes rose from 358 to 402, an increase of 12.3%. Correspondingly, the number of people injured in these incidents grew by 7.6% from 105 to 113, and fatalities increased from zero to one.

23

Hit-and-Run Crashes — 2025

9.5% vs prior (21)

The absolute number of hit-and-run crashes in Hingham saw a slight increase, rising from 21 incidents in 2024 to 23 in 2025. However, due to the overall increase in total crashes, the hit-and-run rate as a proportion of all crashes experienced a marginal decrease. The rate went from 5.9% in the prior year to 5.7% in the current year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 4-50.0%

1

Cyclists Injured

Prior: 3-66.7%

110

Motorists Injured

Prior: 9812.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two periods. While Thursday remained the day with the most incidents, the count on this peak day rose from 60 to 72. The peak hour for crashes shifted slightly earlier from 3 PM (35 crashes) in 2024 to 2 PM (38 crashes) in 2025. The month with the highest crash volume also changed, moving from January (39 crashes) in the prior year to June (47 crashes) in the current year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes worsened in 2025, with one fatal crash recorded, compared to zero in 2024. This resulted in an increase in the fatal crash rate from 0% to 0.25%. While the count of serious injury crashes decreased slightly from 5 to 4, minor injury crashes increased from 47 to 66. Consequently, the proportion of all crashes that resulted in any type of injury rose from 19.8% in 2024 to 22.4% in 2025.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
Serious Injury4serious injury crashes1%
-20.0%prior 5
Minor Injury66minor injury crashes16.4%
40.4%prior 47
Possible Injury20possible injury crashes5%
5.3%prior 19
No Injury301no injury crashes74.9%
7.9%prior 279

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the leading contributing factor in both years, though its count decreased slightly from 86 to 84 incidents. The most significant shift in contributing factors was the increase in crashes attributed to 'Followed too closely,' which rose in count from 35 to 57, a 62.9% increase, moving it from the third to the second-ranked cause. Conversely, crashes involving 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' saw a substantial decrease in count from 29 to 6.

Officer-Reported Primary Contributing Cause

Inattention84 (20.9%)-2.3%prior 86
Followed too closely57 (14.2%)62.9%prior 35
No improper driving53 (13.2%)65.6%prior 32
Failed to yield right of way46 (11.4%)-14.8%prior 54
Failure to keep in proper lane or running off road25 (6.2%)47.1%prior 17
Disregarded traffic signs, signals, road markings18 (4.5%)100.0%prior 9
Distracted16 (4%)60.0%prior 10
Other improper action11 (2.7%)0.0%prior 11
Driving too fast for conditions10 (2.5%)25.0%prior 8
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway9 (2.2%)12.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes on dry roads and in daylight conditions increased in absolute numbers, consistent with the overall rise in total crashes. Collisions on dry surfaces grew from 278 to 320, and those in daylight increased from 248 to 295. However, crashes occurring during rainy weather decreased from 31 to 19 incidents. The proportion of crashes happening in daylight increased from 69.3% to 73.4% of all incidents.

Weather

Clear276 (69.0%)
4.9%prior 263
Clear/Clear43 (10.8%)
Cloudy19 (4.8%)
-17.4%prior 23
Rain19 (4.8%)
-38.7%prior 31
Cloudy/Rain14 (3.5%)
-6.7%prior 15
Snow7 (1.8%)
40.0%prior 5
Rain/Cloudy7 (1.8%)
40.0%prior 5
Snow/Blowing sand, snow2 (0.5%)
Snow/Sleet, hail (freezing rain or drizzle)2 (0.5%)
Snow/Snow2 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight295 (73.6%)
19.0%prior 248
Dark - lighted roadway53 (13.2%)
-10.2%prior 59
Dark - roadway not lighted31 (7.7%)
6.9%prior 29
Dawn10 (2.5%)
Dusk7 (1.7%)
-53.3%prior 15
Dark - unknown roadway lighting4 (1.0%)
Other1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry320 (79.8%)
15.1%prior 278
Wet62 (15.5%)
-7.5%prior 67
Snow13 (3.2%)
44.4%prior 9
Slush3 (0.7%)
Sand, mud, dirt, oil, gravel2 (0.5%)
Ice1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained Toyota, Ford, and Jeep, though their order shifted, with Jeep (65 vehicles) overtaking Ford (64 vehicles) for the second spot. The number of Toyotas involved in crashes saw a notable increase from 105 to 152. Analysis of persons involved shows the 65+ age group grew from 141 to 158 individuals, while the 16-20 age group decreased from 107 to 97.

Top Vehicle Makes (741 vehicles)

1
TOYOTA152 (20.5%)
44.8%prior 105
2
JEEP65 (8.8%)
12.1%prior 58
3
FORD64 (8.6%)
0.0%prior 64
4
HONDA63 (8.5%)
31.3%prior 48
5
CHEVROLET53 (7.2%)
12.8%prior 47
6
NISSAN37 (5%)
12.1%prior 33
7
SUBARU35 (4.7%)
-10.3%prior 39
8
GMC24 (3.2%)
84.6%prior 13
9
VOLKSWAGEN20 (2.7%)
-25.9%prior 27
10
KIA19 (2.6%)
-17.4%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (833 persons with recorded sex)

Male457 (54.9%)
19.3%prior 383
Female375 (45.0%)
-4.6%prior 393
X / Unspecified1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes continued to be most prevalent in 30 mph zones, with the count rising from 94 to 99 year-over-year. There was a notable increase in crashes within 60 mph zones, which grew from 43 to 56 incidents. The single fatal crash recorded in 2025 occurred in a 25 mph zone. In 2024, there were no fatal crashes reported across any speed zone.

Fatal crashes by zone: 25 mph: 1 of 52 (1.923%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: HINGHAM, MA
  • Total crash records analyzed: 402
  • Total persons involved: 909
  • Total vehicles involved: 741

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). "HINGHAM, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hingham/2025-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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Hingham, MA Crash Report — 2025 | ThatCarHitMe.com