Monthly Traffic Safety Analysis

56 CRASHES IN
NATICK, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

Total crashes in Natick increased from 46 in January 2022 to 56 in January 2023, representing a 21.7% rise. This period also saw a 36.4% increase in total injuries, from 11 to 15. The most notable shift was the substantial increase in crashes occurring in wet road conditions, rising from 3 to 17.

56

21.7%was 46

Total Crash Events

0

Persons Killed

15

36.4%was 11

Persons Injured

0

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 1 crash with unreported severity is not shown in the severity breakdown.

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 activity in Natick increased year-over-year. Total crashes rose by 10, from 46 in January 2022 to 56 in January 2023, marking a 21.7% increase. Concurrently, total injuries increased by 4, from 11 to 15, representing a 36.4% rise.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 10.0%

14

Motorists Injured

Prior: 1040.0%

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

In January 2022, the peak day for crashes was Sunday with 9 incidents, shifting to Monday with 20 incidents in January 2023. The peak hour for crashes remained 5 PM in both periods, with 7 crashes in January 2022 and 8 crashes in January 2023. This indicates a shift in crash concentration from weekends to weekdays.

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

Fatalities remained at 0 in both January 2022 and January 2023. Total injuries increased from 11 to 15 year-over-year, with serious injuries remaining constant at 1 in both periods. Minor injuries rose from 3 to 8, while possible injuries decreased from 4 to 2. The share of crashes resulting in no injury slightly decreased from 80.4% in the prior period to 78.6% in the current period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.8%
0.0%prior 1
Minor Injury8minor injury crashes14.3%
166.7%prior 3
Possible Injury2possible injury crashes3.6%
-50.0%prior 4
No Injury44no injury crashes78.6%
18.9%prior 37

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

Inattention remained the leading contributing factor, increasing from 12 crashes in January 2022 to 17 crashes in January 2023, an increase of 5 crashes. Followed too closely saw a significant increase, rising from 3 crashes to 7 crashes, a 133.3% increase in count. Conversely, 'Other improper action' decreased from 6 crashes to 1 crash, and 'Failed to yield right of way' decreased from 6 crashes to 4 crashes.

Officer-Reported Primary Contributing Cause

Inattention17 (30.4%)41.7%prior 12
No improper driving10 (17.9%)0.0%prior 10
Followed too closely7 (12.5%)
Failed to yield right of way4 (7.1%)-33.3%prior 6
Failure to keep in proper lane or running off road3 (5.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (5.4%)
Driving too fast for conditions2 (3.6%)
Disregarded traffic signs, signals, road markings2 (3.6%)
Distracted2 (3.6%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (1.8%)

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 decreased from 32 to 26, while those in wet road conditions significantly increased from 3 to 17. Crashes during dark conditions also rose, with incidents on dark-lighted roadways increasing from 14 to 18 and on dark-unlighted roadways increasing from 2 to 7. This suggests a shift towards more crashes under adverse environmental conditions.

Weather

Clear26 (46.4%)
-18.8%prior 32
Cloudy8 (14.3%)
Snow8 (14.3%)
Rain7 (12.5%)
Snow/Cloudy3 (5.4%)
Cloudy/Rain2 (3.6%)
Snow/Sleet, hail (freezing rain or drizzle)2 (3.6%)

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

Lighting

Daylight28 (50.0%)
3.7%prior 27
Dark - lighted roadway18 (32.1%)
28.6%prior 14
Dark - roadway not lighted7 (12.5%)
Dawn2 (3.6%)
Dusk1 (1.8%)

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

Road Surface

Dry28 (50.0%)
-15.2%prior 33
Wet17 (30.4%)
Snow6 (10.7%)
-25.0%prior 8
Ice4 (7.1%)
Slush1 (1.8%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 83 to 105 year-over-year. Toyota vehicles involved in crashes rose from 10 to 19, while Ford vehicles increased from 8 to 13. The age group 35-44 experienced the largest increase in persons involved, rising from 11 to 24, while the 21-25 age group saw the largest decrease, from 17 to 7.

Top Vehicle Makes (105 vehicles)

1
TOYOTA19 (18.1%)
90.0%prior 10
2
HONDA13 (12.4%)
18.2%prior 11
3
FORD13 (12.4%)
62.5%prior 8
4
SUBARU6 (5.7%)
5
HYUNDAI6 (5.7%)
6
NISSAN6 (5.7%)
-25.0%prior 8
7
ACURA4 (3.8%)
8
CHEVROLET4 (3.8%)
-42.9%prior 7
9
JEEP3 (2.9%)
-50.0%prior 6
10
VOLKSWAGEN3 (2.9%)
-50.0%prior 6

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 (121 persons with recorded sex)

Female63 (52.1%)
31.3%prior 48
Male58 (47.9%)
13.7%prior 51

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 in 30 mph zones increased from 14 to 20, and in 35 mph zones from 11 to 17. Crashes in 65 mph zones quadrupled from 2 to 6. Conversely, crashes in 25 mph zones decreased from 5 to 3. No fatal crashes were recorded in any speed zone during either period.

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: NATICK, MA
  • Total crash records analyzed: 56
  • Total persons involved: 127
  • Total vehicles involved: 105

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). "NATICK, 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/natick/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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Natick, MA Crash Report — January 2023 | ThatCarHitMe.com