Monthly Traffic Safety Analysis

59 CRASHES IN
WAREHAM, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

In January 2023, Wareham recorded 59 crashes, an increase of 9.26% compared to the 54 crashes in January 2022. A significant change was observed in fatalities, rising from 0 in the prior year to 2 in the current period.

59

9.3%was 54

Total Crash Events

2

Persons Killed

8

33.3%was 6

Persons Injured

1

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for January 2023 indicates an upward trend in Wareham, with total crashes increasing by 9.26% from 54 to 59 compared to January 2022. This period also saw an increase in total fatalities from 0 to 2, and total injuries rose by 33.33%, from 6 to 8.

1

Hit-and-Run Crashes — January 2023

1.7% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 0%

1

Cyclists Injured

Prior: 0%

7

Motorists Injured

Prior: 475.0%

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

When Crashes Happen

The peak day for crashes remained Monday, increasing from 13 crashes in January 2022 to 15 crashes in January 2023. The peak hour for crashes shifted from 2 PM with 5 crashes in the prior year to 5 PM with 8 crashes in the current period, indicating a change in high-risk times.

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

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

Crash Severity Breakdown

A notable shift in crash severity occurred, with fatal crashes increasing from 0 in January 2022 to 2 in January 2023. Minor injury crashes increased from 5 to 6, representing a slight rise in their share from 9.3% to 10.2%, while possible injury crashes doubled from 1 to 2, increasing their share from 1.9% to 3.4%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes3.4%
Minor Injury6minor injury crashes10.2%
20.0%prior 5
Possible Injury2possible injury crashes3.4%
100.0%prior 1
No Injury49no injury crashes83.1%
4.3%prior 47

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

The leading contributing factor, 'No improper driving,' decreased by 22.73% from 22 crashes in January 2022 to 17 crashes in January 2023. Conversely, crashes attributed to 'Inattention' increased by 66.67%, from 6 to 10 incidents, and 'Disregarded traffic signs, signals, road markings' saw a 300% increase, rising from 1 to 4 crashes.

Officer-Reported Primary Contributing Cause

No improper driving17 (28.8%)-22.7%prior 22
Inattention10 (16.9%)66.7%prior 6
Failed to yield right of way5 (8.5%)
Disregarded traffic signs, signals, road markings4 (6.8%)
Driving too fast for conditions3 (5.1%)
Failure to keep in proper lane or running off road3 (5.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.4%)
Fatigued/asleep2 (3.4%)
Glare1 (1.7%)
Physical impairment1 (1.7%)

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

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 31 to 23, while 'Rain' related crashes increased from 6 to 10, and 'Sleet' related crashes doubled from 3 to 6. Regarding road surface, crashes on 'Wet' roads significantly increased from 7 to 19, whereas 'Ice' and 'Snow' related crashes decreased.

Weather

Clear23 (39.0%)
-25.8%prior 31
Rain10 (16.9%)
66.7%prior 6
Sleet, hail (freezing rain or drizzle)6 (10.2%)
Snow5 (8.5%)
0.0%prior 5
Clear/Unknown4 (6.8%)
Cloudy4 (6.8%)
Snow/Cloudy2 (3.4%)
Cloudy/Snow1 (1.7%)
Rain/Cloudy1 (1.7%)
Cloudy/Rain1 (1.7%)

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

Lighting

Daylight35 (59.3%)
12.9%prior 31
Dark - lighted roadway14 (23.7%)
27.3%prior 11
Dark - roadway not lighted8 (13.6%)
-11.1%prior 9
Dark - unknown roadway lighting1 (1.7%)
Dusk1 (1.7%)

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

Road Surface

Dry29 (50.0%)
-3.3%prior 30
Wet19 (32.8%)
171.4%prior 7
Ice7 (12.1%)
-22.2%prior 9
Snow3 (5.2%)
-57.1%prior 7

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

Vehicles & Demographics

Among vehicle makes, Toyota crashes increased from 8 to 12, while Ford crashes decreased from 13 to 11. In terms of person demographics, the 65+ age group saw a substantial increase in representation, rising from 5 persons involved in crashes in January 2022 to 19 in January 2023.

Top Vehicle Makes (99 vehicles)

1
TOYOTA12 (12.1%)
50.0%prior 8
2
FORD11 (11.1%)
-15.4%prior 13
3
CHEVROLET11 (11.1%)
0.0%prior 11
4
HONDA10 (10.1%)
42.9%prior 7
5
GMC7 (7.1%)
6
HYUNDAI6 (6.1%)
7
NISSAN5 (5.1%)
8
MAZDA5 (5.1%)
9
JEEP4 (4%)
-33.3%prior 6
10
KIA3 (3%)

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

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

Sex Distribution (108 persons with recorded sex)

Male65 (60.2%)
16.1%prior 56
Female43 (39.8%)
79.2%prior 24

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

Speed Limit Zones

Crashes at the 25 mph speed limit decreased from 8 to 4, but a fatal crash occurred in this zone in January 2023, where none were recorded previously. Crashes at 30 mph increased from 2 to 6, also seeing a fatal crash in the current period, while 35 mph and 65 mph zones both experienced an increase in crash counts without any fatalities in either period.

Fatal crashes by zone: 25 mph: 1 of 4 (25%) · 30 mph: 1 of 6 (16.667%)

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

Data Coverage

  • Reporting period: 2023-01-01 through 2023-01-31 (31 days)
  • Geographic scope: WAREHAM, MA
  • Total crash records analyzed: 59
  • Total persons involved: 114
  • Total vehicles involved: 99

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). "WAREHAM, MA Crash Intelligence Report: January 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wareham/january-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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Wareham, MA Crash Report — January 2023 | ThatCarHitMe.com