Yearly Traffic Safety Analysis

626 CRASHES IN
NATICK, MA
2022

All metrics benchmarked against2021

In Natick, total traffic crashes increased by 3.0%, from 608 incidents in 2021 to 626 in 2022. This period also saw total injuries rise from 111 to 124, and fatalities increase from zero to one. The most significant year-over-year change was in hit-and-run incidents, which increased by 175% from 8 to 22 crashes.

626

3.0%was 608

Total Crash Events

1

Persons Killed

124

11.7%was 111

Persons Injured

22

175.0%was 8

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic collisions shows a slight increase year-over-year. Total crashes rose from 608 in 2021 to 626 in 2022, an increase of 18 incidents. Concurrently, the number of people injured in these crashes grew from 111 to 124, and the year saw one fatality, compared to zero in the prior year.

22

Hit-and-Run Crashes — 2022

175.0% vs prior (8)

Hit-and-run crashes increased significantly between the two periods. The absolute count of hit-and-run incidents rose by 175%, from 8 in 2021 to 22 in 2022. Consequently, the hit-and-run rate, as a percentage of total crashes, more than doubled, increasing from 1.3% in 2021 to 3.5% in 2022.

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%

4

Pedestrians Injured

Prior: 40.0%

10

Cyclists Injured

Prior: 3233.3%

109

Motorists Injured

Prior: 1044.8%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal crash patterns shifted between the two periods. In 2022, the peak day for crashes was Thursday with 104 incidents, a change from Monday (103 incidents) in 2021. The peak hour for collisions also shifted later in the day, from 4 PM (67 crashes) in 2021 to 5 PM (90 crashes) in 2022, with a notable increase in the volume of crashes during that hour.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes worsened slightly in 2022, with one fatal crash recorded, compared to zero in 2021. This resulted in a fatal crash rate of 0.2% for 2022. The count of serious injury crashes decreased from 6 to 5, while crashes involving possible injuries increased from 30 to 39. The number of crashes resulting in no injuries increased from 458 in 2021 to 512 in 2022.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
Serious Injury5serious injury crashes0.8%
-16.7%prior 6
Minor Injury55minor injury crashes8.8%
0.0%prior 55
Possible Injury39possible injury crashes6.2%
30.0%prior 30
No Injury512no injury crashes81.8%
11.8%prior 458

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the leading contributing factor in both years, with the count of related crashes increasing by 11.2% from 178 in 2021 to 198 in 2022. The number of crashes attributed to 'Followed too closely' grew by 27.8%, from 54 to 69 incidents, and 'Failed to yield right of way' crashes increased by 30.6% from 49 to 64. Conversely, crashes involving 'Other improper action' decreased from 60 in 2021 to 40 in 2022.

Officer-Reported Primary Contributing Cause

Inattention198 (31.6%)11.2%prior 178
No improper driving111 (17.7%)-5.1%prior 117
Followed too closely69 (11%)27.8%prior 54
Failed to yield right of way64 (10.2%)30.6%prior 49
Other improper action40 (6.4%)-33.3%prior 60
Failure to keep in proper lane or running off road33 (5.3%)-2.9%prior 34
Disregarded traffic signs, signals, road markings21 (3.4%)61.5%prior 13
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner17 (2.7%)-5.6%prior 18
Driving too fast for conditions16 (2.6%)-23.8%prior 21
Made an improper turn9 (1.4%)12.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained largely consistent year-over-year. In both 2022 and 2021, the majority of incidents occurred in clear weather (73.2% and 70.9% of crashes, respectively) and on dry road surfaces (81.5% and 80.3%). The number of crashes in daylight was identical at 451 for both years, though its share of total crashes decreased slightly in 2022 due to the higher overall crash volume.

Weather

Clear458 (73.6%)
6.3%prior 431
Cloudy59 (9.5%)
-3.3%prior 61
Rain42 (6.8%)
-6.7%prior 45
Snow17 (2.7%)
-5.6%prior 18
Cloudy/Rain13 (2.1%)
-45.8%prior 24
Clear/Other12 (1.9%)
20.0%prior 10
Snow/Sleet, hail (freezing rain or drizzle)4 (0.6%)
Rain/Cloudy4 (0.6%)
Cloudy/Other3 (0.5%)
Fog, smog, smoke2 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight451 (72.2%)
0.0%prior 451
Dark - lighted roadway117 (18.7%)
15.8%prior 101
Dark - roadway not lighted28 (4.5%)
16.7%prior 24
Dusk18 (2.9%)
-5.3%prior 19
Dawn10 (1.6%)
66.7%prior 6
Dark - unknown roadway lighting1 (0.2%)
-85.7%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry510 (81.6%)
4.5%prior 488
Wet84 (13.4%)
-6.7%prior 90
Snow17 (2.7%)
-19.0%prior 21
Ice12 (1.9%)
100.0%prior 6
Sand, mud, dirt, oil, gravel1 (0.2%)
Water (standing, moving)1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained Toyota, Honda, and Ford in both years, though the count for Toyota and Honda decreased from 212 and 184 to 199 and 164, respectively. Analysis of persons involved shows a shift in age demographics; the 26-34 age group saw its involvement increase from 226 to 256 individuals, becoming the most represented group in 2022. Meanwhile, involvement of the 16-20 age group decreased from 179 to 134 persons.

Top Vehicle Makes (1,198 vehicles)

1
TOYOTA199 (16.6%)
-6.1%prior 212
2
HONDA164 (13.7%)
-10.9%prior 184
3
FORD134 (11.2%)
16.5%prior 115
4
JEEP65 (5.4%)
18.2%prior 55
5
NISSAN63 (5.3%)
37.0%prior 46
6
SUBARU60 (5%)
-1.6%prior 61
7
CHEVROLET60 (5%)
0.0%prior 60
8
DODGE33 (2.8%)
106.3%prior 16
9
HYUNDAI33 (2.8%)
3.1%prior 32
10
VOLKSWAGEN31 (2.6%)
0.0%prior 31

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (1,321 persons with recorded sex)

Male713 (54.0%)
0.1%prior 712
Female607 (46.0%)
0.0%prior 607
X / Unspecified1 (0.1%)
0.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

There was a noticeable shift in crashes toward 35 mph zones, which saw an increase from 126 incidents in 2021 to 155 in 2022. The single fatal crash recorded in 2022 occurred within a 35 mph speed zone. The number of crashes in 30 mph zones was unchanged at 217 for both years, while incidents in 40 mph zones decreased from 53 to 46.

Fatal crashes by zone: 35 mph: 1 of 155 (0.645%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: NATICK, MA
  • Total crash records analyzed: 626
  • Total persons involved: 1,404
  • Total vehicles involved: 1,198

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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/natick/2022-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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Natick, MA Crash Report — 2022 | ThatCarHitMe.com