Closed Beta — Coming Soon

How it works

The mechanics, in detail.

A proposed model for squads, valuations, trading, scoring and competition. Everything on this page is subject to confirmation before the closed beta.

Step 01

Build your squad

Your squad. Your strategy.

Start with 100 virtual credits and pick five footballers inside your budget: a goalkeeper, a defender, a midfielder, a forward and one flexible slot. Every player carries a credit valuation shaped by projected performance, so a strong squad is as much about price as talent.

100 virtual credits to start
GK, DEF, MID, FWD and one flexible slot
Valuations move with projected performance

Build your squadPreview data

GKL. Okafor12.0 cr·8.4 pts

DEFT. Brandt16.5 cr·11.2 pts

MIDM. Castellanos24.0 cr·16.9 pts

FLEXJ. Lindqvist14.0 cr·12.2 pts

FWDK. Dubois28.0 cr·19.1 pts

GKL. Okafor12.0 cr

DEFT. Brandt16.5 cr

MIDM. Castellanos24.0 cr

FLEXJ. Lindqvist14.0 cr

FWDK. Dubois28.0 cr

Budget94.5 / 100 credits

5.5 credits remaining

GK
DEF
MID
FLEX
FWD

Step 02

Scout the market

Find value before the crowd.

Every player comes with market price, projected points, recent form, the upcoming fixture, team win probability where available, price movement, a value score and performance history. Relevant Polymarket markets can contribute signals to the analysis.

Compact charts for rising and falling valuations
Fixture context from market-implied probabilities
Value score: projected output against price

A team's probability of winning is a fixture signal, not a player's probability of scoring.

Scout the marketPreview data

Swipe to see more

Player	Fixture	Price	Proj	Win	Value
MIDJ. Lindqvist	ASH (A)	14.0	12.2	33%	91
MIDP. Nowak	BRI (A)	10.5	8.9	38%	84
FWDN. Ferreira	KIN (A)	15.5	11.8	29%	80
DEFT. Brandt	NOR (A)	16.5	11.2	28%	77
MIDH. Takahashi	HAL (H)	18.0	13.1	54%	75

Win probability is a fixture-level, market-implied signal and is shown for context only. It is not a scoring probability for the player.

Step 03

Trade your conviction

Every decision has a price.

Adjust your squad any time before the gameweek locks. Sell players whose valuation has risen, replace the ones you believe are overpriced, and keep your budget working. Football knowledge, timing and budget discipline all make a difference.

Virtual credits only in the initial product
Sell high, buy early, stay inside budget
Squads lock at the gameweek deadline

Trade your convictionPreview data

SellRising

T. Brandt

DEF · NOR (A)

16.5 cr

+4.6% since bought

BuyRising

P. Nowak

MID · BRI (A)

10.5 cr

value score 84

Budget 5.5 → 11.5 creditsWindow open · locks GW 9, Sat 11:00 UTC

Step 04

Performance meets expectation

Great players score points. Great managers spot value.

Real football performances generate fantasy points. On top of that, a clearly defined bonus rewards players who outperform their published pre-match expectation. A superstar expected to score 9 who delivers 10 earns a small bonus. An overlooked player expected to score 3 who delivers 9 earns a much larger one.

Base points from real performances
Outperformance bonus against published expectation
Final scoring weights confirmed before beta

The numbers shown are hypothetical examples under the proposed model.

Performance meets expectationPreview data

K. Dubois
Superstar forward · 28.0 cr
Expected 9 · Actual 10
Outperformance +1 → bonus +0.5
Expected
Actual
Bonus
J. Lindqvist
Overlooked midfielder · 14.0 cr
Expected 3 · Actual 9
Outperformance +6 → bonus +3.0
Expected
Actual
Bonus

Proposed model: bonus = points above published expectation × 0.5. Hypothetical example. Final scoring weights are confirmed before beta.

Step 05

Climb the leaderboard

Prove you know the game.

Global rankings and weekly competitions track fantasy points, squad value, value discovered, win streaks and manager reputation. The initial product is competitive and free to play. Crypto functionality is prospective, not launched.

Global and weekly rankings
Value discovered as a tracked statistic
Reputation that follows the manager

Global leaderboardPreview data

Swipe to see more

#	Manager	Pts	Squad	Found	Streak	Rep
1	marginal_gains	612	108.5	+14.2	5	96
2	xg_merchant	598	104.0	+11.8	3	93
3	northstand	591	101.5	+9.4	2	90
4	deeplying	577	99.0	+12.6	1	88
5	fullback_fc	569	102.5	+6.1	0	85

Fictional managers and demonstration statistics.

Squad rules

Six rules. No small print.

Starting budget

100 credits

Virtual credits. No monetary value.

Squad size

5 players

Small squads make every pick matter.

Required slots

GK · DEF · MID · FWD

One of each, no exceptions.

Flexible slot

Any outfield position

Your edge pick.

Changes

Until the gameweek locks

Sell, buy, rebalance.

Valuations

Move with projections

Price reflects expected output.

Scoring model

Points for performance. A bonus for being right early.

Real football performances generate base points. A separate, clearly defined bonus rewards players who beat the expectation published before kickoff. Because the bonus scales with the gap, an overlooked player who delivers can be worth more to a manager than a superstar who merely meets expectations.

Weights confirmed before betaIllustrative weights

Action	Points
Appearance (60+ minutes)	2
Goal · forward	4
Goal · midfielder	5
Goal · defender or goalkeeper	6
Assist	3
Clean sheet · defender or goalkeeper	4
Every 3 saves · goalkeeper	1
Yellow card	−1
Red card	−3
Outperformance bonus	(actual − expected) × 0.5

Example: K. Dubois, expected 9, scores 10 → bonus +0.5. J. Lindqvist, expected 3, scores 9 → bonus +3.0. Hypothetical numbers under the proposed model.

Valuations

What moves a price.

Valuations are designed to be explainable. Every input is visible on the player page, so a manager can see why the market thinks what it thinks and decide whether to disagree.

Projected points

A per-gameweek projection built from role, minutes, output and opponent.

Recent form

Rolling points over the last five gameweeks, weighted towards the most recent.

Fixture context

Market-implied team probabilities, including relevant Polymarket markets, where available.

Price momentum

How the market has moved on the player over the last seven days.

Demand

How many managers hold the player and how that is changing.

Value score

Projected output relative to price. The number scouts look at first.

Fixture context uses team-level probabilities. A team being likely to win says nothing on its own about whether a specific player will score, and the model does not treat it as if it did.

See it as a product.

Explore the game preview Join the waitlist