FootySim Football Predictions

Season projections, standings, match predictions, and betting odds for 15 leagues and tournaments, updated nightly.

Purely mathematical simulations. Why is this different from betting odds?

Final Season Results

EFL Championship

Final Season Stats End-of-Season Probabilities
Team Pts Goal Diff
Every Position
↓ 24th1st ↓
Relegation Promotion Playoffs Direct Promotion Win League
Burnley 101 pts
101.0 +52 0% 0% ✓ ✓
91.0 +34 0% 0% ✓ 0%
Luton 80 pts
80.0 +18 0% ✓ 0% 0%
75.0 +28 0% ✓ 0% 0%
70.0 +12 0% ✓ 0% 0%
69.0 +13 0% ✓ 0% 0%
69.0 -2 0% 0% 0% 0%
Millwall 68 pts
68.0 +7 0% 0% 0% 0%
66.0 +6 0% 0% 0% 0%
66.0 +4 0% 0% 0% 0%
Watford 63 pts
63.0 +3 0% 0% 0% 0%
63.0 -14 0% 0% 0% 0%
62.0 +3 0% 0% 0% 0%
59.0 -1 0% 0% 0% 0%
58.0 -10 0% 0% 0% 0%
53.0 +1 0% 0% 0% 0%
53.0 -11 0% 0% 0% 0%
53.0 -15 0% 0% 0% 0%
50.0 -11 0% 0% 0% 0%
QPR 50 pts
50.0 -27 0% 0% 0% 0%
49.0 -17 0% 0% 0% 0%
Reading 44 pts
44.0 -22 ✓ 0% 0% 0%
44.0 -24 ✓ 0% 0% 0%
42.0 -27 ✓ 0% 0% 0%
Direct Promotion Promotion Playoffs Relegation
Rank Team Pts Pld Goals GD
1 Burnley 101 46 87:35 +52
2 Sheffield United 91 46 73:39 +34
3 Luton 80 46 57:39 +18
4 Middlesbrough 75 46 84:56 +28
5 Coventry City 70 46 58:46 +12
6 Sunderland 69 46 68:55 +13
7 Blackburn Rovers 69 46 52:54 -2
8 Millwall 68 46 57:50 +7
9 West Brom 66 46 59:53 +6
10 Swansea City 66 46 68:64 +4
11 Watford 63 46 56:53 +3
12 Preston North End 63 46 45:59 -14
13 Norwich City 62 46 57:54 +3
14 Bristol City 59 46 55:56 -1
15 Hull City 58 46 51:61 -10
16 Stoke City 53 46 55:54 +1
17 Birmingham City 53 46 47:58 -11
18 Huddersfield 53 46 47:62 -15
19 Rotherham 50 46 49:60 -11
20 QPR 50 46 44:71 -27
21 Cardiff City 49 46 41:58 -17
22 Reading 44 46 46:68 -22
23 Blackpool 44 46 48:72 -24
24 Wigan Athletic 42 46 38:65 -27

Season Timeline

Probability evolution over time

A statistical line chart showing the evolution of EFL Championship probabilities for Burnley and others based on 10,000 Monte Carlo simulations.

* Mathematical projections reflect the engine's state at the time of daily simulation. Probabilities may lag real-world match results by up to 48 hours due to upstream data processing.

How this works

FootySim uses a custom Monte Carlo simulation engine to project match results and the final outcome of the season.

Analytical Comparison

Betting markets are influenced by public sentiment and financial liability. This model is strictly performance-based. By focusing solely on Elo ratings and xG distributions, this method provides a pure statistical perspective, fueled by on-pitch results rather than media sentiment or betting volume.

Note on Statistical Variance:

  • Regional Rating Bubbles: Elo is a relative system. In global tournaments, teams from isolated confederations may occasionally display "inflated" ratings if they haven't faced top-tier international opposition recently.
  • The "Pure Data" Trade-off: By ignoring "soft data" (injuries, lineup news, or tactical shifts), this model remains objective but may lag behind real-time squad changes that haven't yet manifested in a final scoreline.

1. Team Power (Elo Ratings): Every team is assigned a power rating based on the Elo system. This rating reflects their current real-world strength based on historical results, opponent quality, and recent form.

2. Match Probabilities & xG: For every unplayed fixture, the engine compares the Elo ratings of the two competing teams. This difference dictates the win probabilities, which are then converted into an Expected Goals (xG) metric for each team, anchored to a real-world average of 2.77 goals per match.

3. Scoreline Generation: The engine feeds these xG values into independent Poisson distributions to generate a realistic final scoreline. It also applies a Dixon-Coles adjustment—a statistical modifier that accounts for late-game human psychology (like "parking the bus" or pushing for a late equalizer) to ensure mathematically accurate draw rates.

4. Dynamic Tournament Momentum: The simulation is path-dependent. As the engine simulates through the schedule, teams dynamically gain or lose Elo points after every simulated match. A team that goes on a giant-killing run in the group stage becomes mathematically stronger before the knockout rounds.

5. The 10,000 Simulations: The engine plays out the remainder of the tournament 10,000 times. Every match is decided by a random number generator weighted by these dynamic metrics. It then tallies up where each team finished across all 10,000 simulated universes to generate the final percentage chances and match probabilities shown across the site.

Interactive Engine

Want to run your own "what-if" scenarios using the exact engine behind these forecasts? Head over to FootySim.io to time-travel through matchdays and simulate alternate realities ⚽

Data Sources: This engine is powered by these incredible community resources:

• eloratings.net: For national team ratings
• clubelo.com: For club elo ratings
• fixturedownload.com: For schedules and results