Football Stats & Props Calculator (Prop Bets)

While the casual public bets on the Match Winner, professional bettors are increasingly moving to the “Small Markets” (Prop Bets). Markets like Shots on Target, Team Fouls, Offsides, and Throw-ins are often less efficient than the 1X2 market, meaning bookmakers make more mistakes in their pricing.

Our Team Stats & Props Calculator allows you to exploit these inefficiencies. By inputting the average performance data of two teams, it uses a modified Poisson Distribution model to generate a probability grid for every relevant line, helping you spot where the bookie has set the Total too low or too high.

Team Stats & Props Calc

Poisson Model
Shots on Target
Fouls
Offsides
Throw-ins
Avg per match
Avg per match
Line Home Over % (Odds) Away Over % (Odds) Match Over % (Odds)

How to Use the Team Stats Calculator

This tool is designed to be a “Swiss Army Knife” for prop betting. Here is the workflow to find value:

  1. Select Your Market: Use the tabs at the top to switch between Shots on Target (SoT), Fouls, Offsides, or Throw-ins.
  2. Input the Averages: Enter the average stats per match for the Home and Away teams.
    • Source: You can find granular data on sites like Opta, FBref, or WhoScored. For example, look for “Shots on Target per Game.”
  3. Calculate: Click the button to generate the grid.
  4. Compare the Lines:
    • Individual Totals: Look at the “Home Over %” and “Away Over %”. If the calculator says there is a 60% chance of Man City getting Over 6.5 SoT, but the bookie offers odds of 2.00 (50%), that is value.
    • Match Totals: The calculator also provides an estimated probability for the combined match total (e.g., Match SoT Over 9.5).

Related Tools: Prop bets often correlate. If you expect a game with many shots, check the xG Calculator for goal probability. If you expect a high foul count, check the Cards & Booking Points Calculator.

Real-World Examples: Winning on Small Markets

Prop markets rely heavily on tactics. Using averages combined with this calculator helps you visualize the outcome.

Example 1: The Offside Trap (Tactical Value)

You are betting on a match involving Aston Villa (known for playing a high defensive line) vs. Liverpool (fast attackers).

  • Stats: Villa forces 4.5 offsides per game. Liverpool is caught offside 2.5 times per game.
  • Calculator Input: You enter these high averages into the “Offsides” tab.
  • Result: The calculator shows a 75% probability of Liverpool having Over 3.5 Offsides.
  • Value: The bookmaker, using generic league averages, sets the line at 2.5. You smash the Over.

Example 2: The “Derby” Fouls

A local derby match usually results in more aggression. The teams average 12 and 13 fouls per game respectively.

  • Calculator Input: Home: 12.0 | Away: 13.0.
  • Result: The “Match Over” column suggests a high probability of 25+ Total Fouls.
  • Strategy: You bet on the Over. Furthermore, since high fouls often lead to set pieces, you might also look at the Corners Calculator to see if the stop-start nature favors corner accumulation.

Frequently Asked Questions (FAQ)

What counts as a “Shot on Target”?

According to Opta (used by most bookies), a Shot on Target is a clear attempt that goes into the net (a goal) or would have gone into the net if not saved by the goalkeeper or the last man. Important: Shots hitting the post or crossbar do not count as shots on target unless they go in afterwards.

Where can I find stats for Throw-ins?

Throw-in stats are niche but available on detailed data sites like FBref (under “Possession” or “Miscellaneous” stats) or specialized sites like TheStatsDontLie. Bookmakers often set throw-in lines based on league averages (approx 40-45 per game), so teams that play for territory often offer value on the “Under.”

Do Extra Time stats count for these bets?

No. Unless the bet specifically says “Including Extra Time” (common in Cup Finals), all statistical prop bets are settled on the result after 90 minutes plus injury time.

How accurate is Poisson for stats like Fouls?

Poisson works well for fouls because they are frequent, discrete events. However, referee strictness is a huge variable. If a lenient referee is in charge, you should manually lower the average inputs in the calculator to get a safer prediction.

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