Advanced Fantasy Football Tools & Analytics

Buy Low Sell High
Trade Targets
Finder

Identify real trade edges using role-based opportunity data.

The StatChasers buy low sell high tool analyzes real NFL usage data from the Sleeper API to find true buy low and sell high trade targets based on opportunity, regression signals, and production gaps —across WR, RB, and TE. Select your week and scoring format. The model handles the rest. 

✕ Not rankings. ✕ Not hot takes. ✕ Not box score chasing.
See How It Works

Coming Soon • PPR / Half / Standard • Week selector • WR / RB / TE filters

Buy Low / Sell High Trade Targets Analyzer mobile preview

Why the Buy Low Sell High Tool Exists

In-season trades are where leagues are won — but most managers are chasing last week’s points. This tool exists to identify role-based trade targets using opportunity and regression signals so you can buy before the breakout and sell before the drop.

Common Trap

Box Scores Create False Value

Touchdowns, busted coverages, and game script spikes can make a player look “hot” — even when their weekly role isn’t changing.

  • TD-driven points are volatile
  • Big plays aren’t predictable
  • Opportunity is the signal
Market Lag

Rankings Update Too Late

By the time consensus reacts, your league has already priced the player up (or down). The best deals happen before the fantasy points follow the role.

  • Targets & snaps move first
  • Points follow later
  • Trade ahead of the crowd
Core Idea

Opportunity-Based Buy Lows Win

A player can be underproducing with an elite role (buy-low) — or overproducing on thin usage (sell-high). This tool surfaces both using weekly usage + regression context.

  • High opp, low points = buy
  • Low opp, high points = sell
  • Designed for weekly action
Not rankings. Not hot takes. Not box score chasing — just opportunity-driven trade targets.

How the Buy Low Sell High Trade Target Finder Works

The model doesn’t chase last week’s fantasy points. It measures role, detects trend, and compares expected vs actual production to surface true buy-lows and sell-highs — weekly.

1 Set Your Week + Scoring

Choose the current week (or any week range) and your scoring format (PPR / Half-PPR / Standard). The tool auto-detects completed weeks in-season.

  • Week slider defaults to latest completed
  • Position filters: WR / RB / TE (or All)
  • Fast results via cached Sleeper API pulls
2 Measure Role (Opportunity Index)

The Opportunity Index scores each player’s role using real usage signals — so you can see who’s actually earning volume and high-value work.

  • Usage signals: targets/touches + snap share
  • High-value work: red zone + efficiency proxies
  • Trend tags: surge, stable, cliff, volatile
3 Compare Expected vs Actual Points

A position-specific regression estimates what a player should be scoring given their role, then compares it to what they actually produced — exposing regression windows.

  • Expected FPG vs actual FPG gap (Δ)
  • TD dependency flags (regression risk)
  • Reliability context to avoid noise
4 Get Trade Targets (Buy/Sell)

The engine labels players as Buy Low or Sell High based on role vs production — with confidence and plain-English reasoning you can use immediately.

  • Buy Low: strong opportunity, points lagging
  • Sell High: points outrunning role (flat/falling usage)
  • Export: CSV tables + mobile PNG charts

Example Trade Target Scenarios

This is what the tool is built to catch: role-based buy-lows before the points spike — and sell-highs before the usage reality hits.

BUY LOW
Market undervaluing role

High Opportunity, Low Points

Usage says the breakout is coming — production hasn’t caught up yet.

  • Targets / Game 8.2
  • Snap Share 82%
  • TDs (Season) 1
  • FPG vs Expected -3.4
What this means
The role is already strong (targets + snaps). If scoring is lagging, it’s often variance — the price is cheaper than the usage profile suggests.
Trade for them before the points catch up.
SELL HIGH
Production outrunning opportunity

Thin Role, Spiked Production

Points are inflated by TDs / efficiency — the usage foundation isn’t there.

  • Targets / Game 4.3
  • Snap Share 58%
  • TDs (Last 3 Games) 5
  • FPG vs Expected +3.4
What this means
The production is beating the role. If targets/snaps are flat or falling, the market price is often higher than what the usage can support long-term.
Trade them away while perception is high.
These are archetypes — the tool finds the real players each week using Sleeper usage data + role-based expected scoring.

FAQ

Quick answers on how the Buy Low/Sell High Trade Target Finder works — and how to use it during the season.

What does “Buy Low” mean in this tool?
“Buy Low” means the player’s opportunity profile (targets/touches, snaps, high-value work) is strong, but their fantasy production is lagging what the role would typically produce. That gap often signals regression in your favor — making them a trade target before the points catch up.
What does “Sell High” mean in this tool?
“Sell High” means the player is scoring more than their underlying role suggests — often driven by TDs, efficiency spikes, or short-term variance. If usage is flat or declining, the tool flags regression risk so you can trade while market perception is high.
Where does the data come from?
The tool uses real NFL player-week data sourced through the Sleeper API. It supports WR, RB, and TE, and scoring formats including PPR, Half-PPR, and Standard.
Is this tool just another rankings list?
No. Rankings are opinion + consensus lag. This tool focuses on opportunity vs production to find trade edges. Think of it as a weekly detector for “role changing” players and “unsustainable scoring” players — without hot takes.
How should I pick the week range?
Default to the latest completed week for the cleanest in-season signal. If you’re diagnosing a role shift, narrow the window (recent weeks). If you want stability, expand the window. The goal is to balance trend detection with noise reduction.
Does this work for dynasty or only redraft?
The signals are built for in-season usage evaluation, so it’s strongest for redraft trade timing. Dynasty managers can still use it to identify undervalued roles — just remember dynasty value includes age, contract outlook, and long-term situation beyond weekly role.
How does TD dependency factor into recommendations?
The tool flags players whose production is heavily driven by touchdowns (higher regression risk), especially when the underlying usage is not elite. For TD volatility context, see Pro-Football-Reference and compare weekly TD rates to targets/touches.
Can I export the results?
Yes — exports are designed for real usage: CSV tables (for deeper analysis) and mobile-friendly PNG charts you can save and share.
Is the tool free? When does it launch?
It’s currently marked Coming Soon. Once released, this page will include access details and launch notes. In the meantime, you can explore other StatChasers tools like Pick Tracker and the Orphan Hub.

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