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About Picks Office

I built this to show what sharp betting looks like — in public.

No hidden records. No selective screenshots. No hype culture. Just a transparent process, documented over 8,100+ plays, built for bettors who think in probabilities.

8,100+

Tracked Picks

Every result public

Since 2019

Public Record

No backfitting

7.4%

Documented ROI

Long-term, not streaks

6

Leagues Covered

NBA · NFL · MLB · NHL · NCAAB · NCAAF

The Origin

Most betting content optimizes for attention. I wanted accountability.

I started betting seriously years ago and quickly realized the industry had a transparency problem. Everyone showed their winners. Nobody showed their process — or their losses.

So I built a format where anyone can verify how decisions are made, how risk is handled, and how results hold up over time. That format became Picks Office.

Transparent ledger. Documented process. No edits when variance hits. Every pick timestamped, every result public.

A sharp bettor is not someone on a hot streak. It's someone who executes with discipline, beats closing numbers over time, protects bankroll, and respects long-term sample size.

Picks Office

Founder

The Journey

From first tracked bet to 8,100+ picks.

19

2019

Started tracking publicly

Began documenting every single play with timestamps, odds, and results. No cherry-picking, no edits after the fact.

21

2021

Built the model pipeline

Developed a systematic approach combining statistical models, line movement analysis, and CLV tracking into one repeatable process.

23

2023

Launched Picks Office

Turned the process into a product. Same transparency, same discipline – now accessible to serious bettors who want the same standard.

25

2025

8,100+ picks tracked

The record speaks for itself. Every win, every loss, every decision documented and available for anyone to verify.

My Framework

Six principles behind every play.

Edge is not one trick. It's the combination of discipline, CLV feedback, bankroll control, and long-term measurement.

Discipline over impulse

I only place a bet when price, model output, and context align. No edge means no action.

CLV as quality control

Beating the closing number over time is the strongest signal that real value is being found.

Bankroll protection

Stake sizing is predefined and tied to confidence tiers. Survival and consistency over hero bets.

Long-term samples

A sharp bettor is evaluated over thousands of plays, not one lucky weekend.

Line shopping

Better entry prices compound over time and reduce avoidable variance.

Post-slate review

Every slate is audited after the games. The next one starts with what the previous one taught me.

The Process

How every pick is made.

No gut feelings, no hot takes. Every position goes through the same systematic pipeline before it gets published.

01

Market Scan

Screen opening numbers and movement to find potential mispricing across covered leagues.

02

Model & Context

Test whether projected edge survives injury news, matchup context, and available line quality.

03

Stake Assignment

Map confidence to units using predefined bankroll rules before anything is published.

04

Post-Result Review

Log result and CLV, then feed that review back into the next slate.

Transparency

Non-negotiable rules.

These aren't marketing promises. They're operating constraints that define how Picks Office works.

  • Every pick is timestamped and remains visible in the track record
  • Losing stretches are reviewed, not deleted
  • Units and stake logic are treated as part of the edge
  • Product claims are anchored to published performance, not hype

Fit Check

Is this for you?

Built for you if
  • You care about CLV, staking discipline, and repeatable execution
  • You value full history over selective screenshots
  • You evaluate outcomes over months and seasons, not single days
  • You want a transparent process, not pick theater
Not a fit if
  • You want daily lock guarantees and instant riches
  • You chase losses with random unit jumps
  • You evaluate a service based on one weekend
  • You expect hidden variance behind marketing language

Next Step

Start with the data. Then decide.

Review the full track record first. If the process and transparency match your standard, the membership is there.