Why Your Google Search Console Average Position is Mathematically Flawed (And How to Fix It)

Gerry Hu — Sun, 27 Sep 2026 05:15:37 +0000

If you export your performance data from Google Search Console and run a simple average formula on your ranking position, your SEO metrics are almost certainly misleading you.

Here is why it happens, how to calculate your true organic rank, and a free calculator you can use to check it.

The Problem: Why Simple Average Position Fails

Imagine your article ranks for just two search queries:

Primary Keyword: Position 2.0 (50,000 impressions)
Random Long-Tail Query: Position 92.0 (2 impressions)
If you calculate a simple average: (2.0 + 92.0) / 2 = 47.0

Your report says your average position is 47.0 (Page 5). It looks like your page is failing.

In reality, 99.99% of actual human searchers see your website in the top 3 spots! The single 2-impression query completely skewed the math.

The Fix: Impression-Weighted Average Position

To see what real searchers actually see, each ranking position must be multiplied by its impression volume:

Formula: Weighted Average Position = Sum of (Position × Impressions) / Total Impressions

Applying this to the example: ((2.0 × 50,000) + (92.0 × 2)) / 50,002 = 2.003

Your true effective rank is 2.0, not 47.0.

Ready-to-Use Formulas for Your Workflow

Google Sheets & Excel If Column B has Positions and Column C has Impressions, paste this formula:
=SUMPRODUCT(B2:B, C2:C) / SUM(C2:C)

To automatically ignore queries with fewer than 5 impressions:

=SUMPRODUCT(FILTER(B2:B, C2:C>=5), FILTER(C2:C, C2:C>=5)) / SUM(FILTER(C2:C, C2:C>=5))

Looker Studio (Google Data Studio) Create a new calculated field:
SUM(Average Position * Impressions) / SUM(Impressions)

BigQuery SQL (Search Console Bulk Export)
SELECT url, SUM(sum_position * impressions) / SUM(impressions) AS weighted_avg_pos FROM your_project.searchconsole.searchdata_url_impression GROUP BY url;

Free Interactive Calculator & Sheet

I built a free interactive tool where you can test calculations directly in your browser without signing up:

Try the Free Calculator: https://serppatch.com/tools/weighted-average-position

Free Google Sheets Template: https://serppatch.com/templates/google-sheets-gsc-weighted-average-calculator

How do you currently track position changes across your website? Do you use weighted averages, or rely on Google's default dashboard? Let me know in the comments!

I spent 2 months building a tool to solve the biggest headache in US HR: FMLA compliance (Here is what I learned)

Gerry Hu — Sat, 20 Jun 2026 16:04:28 +0000

Hey Dev.to community,

For the past two months, I’ve been locked in my room, staring at a giant spreadsheet of U.S. labor laws, wondering why on earth I decided to build something in the HR space.

It all started when I was browsing Reddit. I noticed a recurring theme on U.S. small business and HR subreddits: people were losing their minds over FMLA (Family and Medical Leave Act) and ADA compliance.

For many U.S. small businesses, there is no "HR department." It’s usually just one person (what I call a Solo HR) trying to calculate rolling 12-month leave periods, coordinate short-term disability, and draft complex legal notices on a tight deadline. One minor calculation mistake on a spreadsheet, and the company gets sued.

I thought: "Hey, I'm a developer. I can automate this."

Oh boy, I was so wrong about it being "simple."

The Nightmare of Coding State-by-State Laws

The biggest technical pain point I ran into wasn't the database structure or the AI agent integrations. It was the logic.

U.S. labor law is a moving target. Federal FMLA is one thing, but then you have state-specific laws (like California's PFL, New York's DBL, Washington, Colorado, etc.). Each state has its own eligibility rules, leave durations, and look-back methods. To make things worse, they update these laws constantly.

Initially, I tried hardcoding the rules, but that quickly turned into a nested if/else nightmare. I had to completely rewrite the engine to use a dynamic rule-matching schema that separates the state logic from the core calculation.

It took me a full two months of coding and legal fact-checking, but we finally launched the beta version of AI SoloHR.

What We Built (And We Need Your Feedback!)

To help those overwhelmed HR admins, we ended up building a set of free, open tools that handle the heavy lifting:

FMLA Leave & Hours Calculator: Handles federal eligibility calculations, rolling calendar periods, and intermittent leave tracks.
ADA Accommodation & Process Timeline Calculator: Helps small businesses visualize the good-faith interactive process timeline to avoid wrongful termination risks.
A general Compliance Toolkit for document drafting.

We're looking for Beta Users!

We just launched and are actively looking for our first batch of seed users. If you run a small business, manage HR, or just want to break my calculators to see if my state-by-state logic holds up, please check us out and drop your feedback in the comments!

What features should we add next? Let me know!

DEV Community: Gerry Hu

Why Your Google Search Console Average Position is Mathematically Flawed (And How to Fix It)

I spent 2 months building a tool to solve the biggest headache in US HR: FMLA compliance (Here is what I learned)

The Nightmare of Coding State-by-State Laws

What We Built (And We Need Your Feedback!)

We're looking for Beta Users!