Pricing Strategies

Overview

FIFA Bot uses sophisticated pricing algorithms to maximize profits while accounting for EA’s 5% transaction tax and market dynamics.

All prices are in FIFA coins. The bot automatically calculates optimal buy/sell prices based on your profit targets.

Core Pricing Concepts

EA Tax

EA Sports applies a 5% tax on all sales in the Transfer Market.

# Sale price after EA tax
sale_price = 1000
after_tax = sale_price * 0.95  # 950 coins
ea_tax = sale_price * 0.05      # 50 coins

Always account for the 5% EA tax when setting prices. A 10% listed profit becomes only 5% actual profit after tax.

Price Tiers

The bot uses different increment strategies based on price ranges:

Low Price Tier (< 1,000 coins)

Increment: 50 coins

if price < 1000:
    price_adjustment = 50

Strategy:

Smaller absolute margins
Higher percentage returns
Faster turnover

Medium Price Tier (1,000 - 10,000 coins)

Increment: 100 coins

if 1000 <= price < 10000:
    price_adjustment = 100

Strategy:

Balanced risk/reward
Most common price range
Consistent volume

High Price Tier (10,000 - 50,000 coins)

Increment: 500 coins

if 10000 <= price < 50000:
    price_adjustment = 500

Strategy:

Higher absolute profits
Lower percentage returns
Slower turnover

Premium Price Tier (50,000+ coins)

Increment: 500 coins

if price >= 50000:
    price_adjustment = 500

Strategy:

Large capital required
Significant profits per sale
Very slow turnover

Dynamic Price Range Algorithm

The buscarRango() and revisarPrecio() functions automatically find optimal price ranges.

Algorithm Flow

Start from Target Sale Price

precioVentaActual = int(final.get())  # Target sale price

Begin with your desired sale price.

Search Market at Current Price

campo = driver.find_element_by_xpath(
    "/html/body/main/section/section/div[2]/div/div[2]/div/div[1]/div[2]/div[6]/div[2]/input"
)
campo.click()
time.sleep(2)
campo.send_keys(precioVentaActual)
clickBuscar()

Search for items at the current price point.

Count Available Items

num_items = len(driver.find_elements_by_xpath(
    "/html/body/main/section/section/div[2]/div/div/section[1]/div/ul/li"
))

Determine how many items are listed at this price.

Adjust Price Based on Supply

If no items found (num_items == 0):

if bandera == 0:
    # Price too low, increase it
    if precioVentaActual < 1000:
        precioVentaActual = precioVentaActual + 50
    elif precioVentaActual < 10000:
        precioVentaActual = precioVentaActual + 100
    elif precioVentaActual < 50000:
        precioVentaActual = precioVentaActual + 500
    else:
        precioVentaActual = precioVentaActual + 500

If too many items (num_items > 4):

# Price too high, decrease it
if precioVentaActual < 1000:
    precioVentaActual = precioVentaActual - 50
elif precioVentaActual < 10000:
    precioVentaActual = precioVentaActual - 100
elif precioVentaActual < 50000:
    precioVentaActual = precioVentaActual - 500
else:
    precioVentaActual = precioVentaActual - 500
bandera = 1  # Mark that we've found supply

If optimal supply (1-4 items):

Price is good, proceed to calculate purchase price

Calculate Purchase Price

Once optimal sale price is found:

# For low price tier (< 1,000)
if precioVentaActual < 1000:
    maximo = round((precioVentaActual * 0.95) - (precioVentaActual * 0.20)) - 50
    final = precioVentaActual
    inicial = precioVentaActual - 50

# For medium/high price tiers (>= 1,000)
elif precioVentaActual < 10000:
    maximo = round((precioVentaActual * 0.95) - (precioVentaActual * 0.05)) - 100
    final = precioVentaActual
    inicial = precioVentaActual - 100

# For premium tier
elif precioVentaActual < 50000:
    maximo = round((precioVentaActual * 0.95) - (precioVentaActual * 0.05)) - 500
    final = precioVentaActual
    inicial = precioVentaActual - 500

else:  # 50,000+
    maximo = round((precioVentaActual * 0.95) - (precioVentaActual * 0.05)) - 500
    final = precioVentaActual
    inicial = precioVentaActual - 500

Send Notification

enviarWhatsapp(f"Nuevo Rango Compra: {maximo} Venta: {final}")

Alert you of the new price range via WhatsApp.

Supply-Based Pricing Logic

0 Items

Market undersuppliedIncrease sale price to find market ceilingContinue searching upward

1-4 Items

Optimal supplyCalculate purchase priceLock in this range

5+ Items

Market oversuppliedDecrease sale priceFind competitive price point

Profit Margin Formulas

buscarRango() Profit Calculation

Used when finding new price ranges without specific profit targets.

# Target: 70-75% of sale price after tax
sale_price = 1000
max_buy = round((sale_price * 0.95) - (sale_price * 0.20)) - 50
# max_buy = round((1000 * 0.95) - (1000 * 0.20)) - 50
# max_buy = round(950 - 200) - 50
# max_buy = 700

profit = (sale_price * 0.95) - max_buy
# profit = 950 - 700 = 250 coins (25% margin)

revisarPrecio() Profit Calculation

Used when you have a specific expected profit target (iEsperada).

# Use the iEsperada field from GUI
sale_price = 5000
expected_profit = int(iEsperada.get())  # e.g., 300

max_buy = round((sale_price * 0.95) - expected_profit)
# max_buy = round((5000 * 0.95) - 300)
# max_buy = round(4750 - 300)
# max_buy = 4450

profit = (sale_price * 0.95) - max_buy
# profit = 4750 - 4450 = 300 coins (guaranteed)

Use buscarRango() for initial market discovery and revisarPrecio() for fine-tuning based on your specific profit goals.

Price Configuration

Manual Price Setting

Set prices directly in the GUI:

maximo

number

required

Maximum Buy PriceThe highest price the bot will pay for items

maximo.insert(0, 1200)  # Won't buy above 1,200 coins

inicial

number

required

Minimum Sale PriceStarting bid price when listing items

inicial.insert(0, 1300)  # Lists at 1,300 minimum

final

number

required

Maximum Sale Price (Buy Now)Buy Now price for listed items

final.insert(0, 1500)  # Buy Now at 1,500 coins

iEsperada

number

Expected ProfitTarget profit per transaction (for revisarPrecio())

iEsperada.insert(0, 200)  # Target 200 coins profit

iReal

number

Actual ProfitCalculated real profit after EA tax

iReal = (int(final.get()) * 0.95) - int(maximo.get())
# iReal = (1500 * 0.95) - 1200 = 225 coins

Example Price Configurations

Conservative Strategy (High Safety)

# Target: 15-20% profit margin
maximo.insert(0, 1000)   # Buy at 1,000
inicial.insert(0, 1150)  # List at 1,150
final.insert(0, 1200)    # Sell at 1,200

# Profit calculation:
profit = (1200 * 0.95) - 1000
# profit = 1140 - 1000 = 140 coins (14% margin)

Pros:

Higher success rate
Faster sales
Lower risk

Cons:

Lower profit per card
Requires high volume

Balanced Strategy (Medium Risk)

# Target: 8-12% profit margin
maximo.insert(0, 5000)   # Buy at 5,000
inicial.insert(0, 5300)  # List at 5,300
final.insert(0, 5500)    # Sell at 5,500

# Profit calculation:
profit = (5500 * 0.95) - 5000
# profit = 5225 - 5000 = 225 coins (4.5% margin)

Pros:

Good balance of volume and profit
Moderate competition
Consistent returns

Cons:

Market fluctuations impact success
Requires price monitoring

Aggressive Strategy (High Risk)

# Target: 5-8% profit margin
maximo.insert(0, 50000)  # Buy at 50,000
inicial.insert(0, 52000) # List at 52,000
final.insert(0, 53500)   # Sell at 53,500

# Profit calculation:
profit = (53500 * 0.95) - 50000
# profit = 50825 - 50000 = 825 coins (1.65% margin)

Pros:

High absolute profits
Less competition at high prices
Fewer transactions needed

Cons:

Large capital required
Slow turnover
Higher risk of market crashes

Volume Strategy (Speed Focus)

# Target: 10-15% margin, maximum speed
maximo.insert(0, 400)    # Buy at 400
inicial.insert(0, 450)   # List at 450
final.insert(0, 500)     # Sell at 500

# Profit calculation:
profit = (500 * 0.95) - 400
# profit = 475 - 400 = 75 coins (18.75% margin)

# But with high volume:
# 20 sales/hour * 75 profit = 1,500 coins/hour

Pros:

Very fast turnover
High percentage margins
Low capital required

Cons:

Small profit per card
Requires constant operation
More bot competition

Dynamic Range Adjustment

Automatically recalculate price ranges based on market conditions.

Enable Dynamic Ranging

# In GUI, check the "Buscar Rango" checkbox
eR.set(1)  # Enable dynamic ranging
numeroRango.insert(0, 31)  # Recalculate every 31 searches

Set Recalculation Frequency

numeroRango

number

default:31

How often to recalculate price range (in number of searches)

if int(eR.get()) == 1:
    if int(cuantos) % int(numeroRango.get()) == 0:
        enviarWhatsapp(f"Van {cuantos}")
        enviarWhatsapp("Calculando Rango")
        revisarPrecio()  # Recalculate based on iEsperada

Monitor Price Changes

The bot notifies you of price adjustments:

"Van 150"  # Progress update
"Calculando Rango"  # Starting recalculation
"Nuevo Rango Compra: 1200 Venta: 1500"  # New range

Dynamic ranging can cause price fluctuations if the market is volatile. Monitor your first few recalculations to ensure prices remain profitable.

Advanced Pricing Techniques

Minimum Search Price Adjustment

The bot adjusts minimum search prices to avoid missing deals:

def aumentaMinimoCompraYa():
    # Increase minimum "Buy Now" price by 1 increment
    driver.find_element_by_xpath(
        "/html/body/main/section/section/div[2]/div/div[2]/div/div[1]/div[2]/div[5]/div[2]/button[2]"
    ).click()

def disminuyeMinimoCompraYa():
    # Decrease minimum "Buy Now" price by 3 increments
    for x in range(0, 3):
        driver.find_element_by_xpath(
            "/html/body/main/section/section/div[2]/div/div[2]/div/div[1]/div[2]/div[5]/div[2]/button[1]"
        ).click()

Strategy:

if espera == 3:
    aumentaMinimoCompraYa()  # Search higher prices
    espera = espera + 1
else:
    disminuyeMinimoCompraYa()  # Search lower prices
    espera = espera - 1

This oscillation ensures the bot searches across the entire price spectrum.

Maximum Price Boundary

def precioMaximoBusqueda():
    precioMax = driver.find_element_by_xpath(
        "/html/body/main/section/section/div[2]/div/div[2]/div/div[1]/div[2]/div[6]/div[2]/input"
    )
    precioMax.click()
    time.sleep(1)
    precioMax.send_keys(maximo.get())

Sets the upper limit to prevent buying overpriced items.

Stop Price (numeroDetener)

numeroDetener.insert(0, 1000)  # Stop when price drops below 1,000

Prevents the bot from operating in unprofitable price ranges during market crashes.

Profit Optimization Tips

EA Tax Awareness

Always calculate profit AFTER 5% tax:

net_profit = (sale * 0.95) - cost

Never use gross profit for decisions.

Price Tier Strategy

Higher margins on low-value cards:

< 1K: 20% margins
1-10K: 10% margins
10K+: 5% margins

Supply Monitoring

Optimal supply: 1-4 items

Too few: Increase sale price
Too many: Decrease sale price
Just right: Lock in range

Dynamic Adjustment

Recalculate every 30-50 searches:

numeroRango.insert(0, 31)

Adapts to market changes.

Pricing FAQ

What's a good profit margin?

It depends on price tier:

Low tier (< 1K): 15-25% margins are achievable
Medium tier (1-10K): 8-15% margins are realistic
High tier (10K+): 5-10% margins are competitive

Remember: EA tax reduces all margins by 5 percentage points.

Should I use buscarRango or revisarPrecio?

buscarRango():

Initial market discovery
No specific profit target
Dynamic margins based on price tier
Better for testing new filters

revisarPrecio():

Fine-tuning existing ranges
Specific profit target (iEsperada)
Consistent margins across prices
Better for stable markets

Start with buscarRango(), then switch to revisarPrecio() once you know your target profit.

How often should I recalculate ranges?

Volatile markets: Every 15-30 searchesStable markets: Every 30-50 searchesHigh-value items: Every 10-20 searches (higher risk)Monitor your WhatsApp notifications to see if ranges are changing significantly.

What if my items won't sell?

Causes:

Sale price too high
Market oversupplied
Card demand dropped

Solutions:

Run revisarPrecio() to update range
Decrease final price by 5-10%
Check if SBC ended (if selling SBC fodder)
Wait for market recovery

Can I use negative margins for volume?

Not recommended.Even at high volume, negative margins lose money. Instead:

Target different filters with natural demand
Use tighter margins (3-5%) on high-volume items
Ensure iReal is always positive

# Always verify profit is positive
iReal = (final.get() * 0.95) - maximo.get()
if iReal <= 0:
    print("UNPROFITABLE - Adjust prices")

Get Started

Core Features

Guides

Reference

Pricing Strategies

Overview

Core Pricing Concepts

EA Tax

Price Tiers

Dynamic Price Range Algorithm

Algorithm Flow

Supply-Based Pricing Logic

0 Items

1-4 Items

5+ Items

Profit Margin Formulas

buscarRango() Profit Calculation

revisarPrecio() Profit Calculation

Price Configuration

Manual Price Setting

Example Price Configurations

Dynamic Range Adjustment

Advanced Pricing Techniques

Minimum Search Price Adjustment

Maximum Price Boundary

Stop Price (numeroDetener)

Profit Optimization Tips

EA Tax Awareness

Price Tier Strategy

Supply Monitoring

Dynamic Adjustment

Pricing FAQ

Next Steps

Core Features

FAQ

Build docs developers (and LLMs) love

Get Started

Core Features

Guides

Reference

​Overview

​Core Pricing Concepts

​EA Tax

​Price Tiers

​Dynamic Price Range Algorithm

​Algorithm Flow

​Supply-Based Pricing Logic

0 Items

1-4 Items

5+ Items

​Profit Margin Formulas

​buscarRango() Profit Calculation

​revisarPrecio() Profit Calculation

​Price Configuration

​Manual Price Setting

​Example Price Configurations

​Dynamic Range Adjustment

​Advanced Pricing Techniques

​Minimum Search Price Adjustment

​Maximum Price Boundary

​Stop Price (numeroDetener)

​Profit Optimization Tips

EA Tax Awareness

Price Tier Strategy

Supply Monitoring

Dynamic Adjustment

​Pricing FAQ

​Next Steps

Core Features

FAQ

Build docs developers (and LLMs) love

Overview

Core Pricing Concepts

EA Tax

Price Tiers

Dynamic Price Range Algorithm

Algorithm Flow

Supply-Based Pricing Logic

Profit Margin Formulas

buscarRango() Profit Calculation

revisarPrecio() Profit Calculation

Price Configuration

Manual Price Setting

Example Price Configurations

Dynamic Range Adjustment

Advanced Pricing Techniques

Minimum Search Price Adjustment

Maximum Price Boundary

Stop Price (numeroDetener)

Profit Optimization Tips

Pricing FAQ

Next Steps