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

Süper Lig

Final Season Stats End-of-Season Probabilities
Team Pts Goal Diff
Every Position
↓ 20th1st ↓
Relegation Conference League Europa League Champions League Second Qualifying Round Champions League Win League
102.0 +66 0% 0% 0% 0% ✓ ✓
99.0 +68 0% 0% 0% ✓ 0% 0%
67.0 +19 0% 0% ✓ 0% 0% 0%
61.0 +14 0% ✓ 0% 0% 0% 0%
Besiktas 56 pts
56.0 +5 0% 0% 0% 0% 0% 0%
56.0 -3 0% 0% 0% 0% 0% 0%
54.0 -7 0% 0% 0% 0% 0% 0%
52.0 +3 0% 0% 0% 0% 0% 0%
Rizespor 50 pts
50.0 -10 0% 0% 0% 0% 0% 0%
49.0 -5 0% 0% 0% 0% 0% 0%
44.0 -7 0% 0% 0% 0% 0% 0%
44.0 -7 0% 0% 0% 0% 0% 0%
43.0 -10 0% 0% 0% 0% 0% 0%
42.0 -13 0% 0% 0% 0% 0% 0%
41.0 -7 0% 0% 0% 0% 0% 0%
41.0 -13 0% 0% 0% 0% 0% 0%
40.0 -3 ✓ 0% 0% 0% 0% 0%
40.0 -6 ✓ 0% 0% 0% 0% 0%
37.0 -31 ✓ 0% 0% 0% 0% 0%
16.0 -53 ✓ 0% 0% 0% 0% 0%
Champions League Champions League Second Qualifying Round Europa League Conference League Relegation
Rank Team Pts Pld Goals GD
1 Galatasaray 102 38 92:26 +66
2 Fenerbahçe 99 38 99:31 +68
3 Trabzonspor 67 38 69:50 +19
4 Basaksehir 61 38 57:43 +14
5 Kasimpasa 56 38 62:65 -3
6 Besiktas 56 38 52:47 +5
7 Sivasspor 54 38 47:54 -7
8 Alanyaspor 52 38 53:50 +3
9 Rizespor 50 38 48:58 -10
10 Antalyaspor 49 38 44:49 -5
11 Gaziantep 44 38 50:57 -7
12 Adana Demirspor 44 38 54:61 -7
13 Samsunspor 43 38 42:52 -10
14 Kayserispor 42 38 44:57 -13
15 Hatayspor 41 38 45:52 -7
16 Konyaspor 41 38 40:53 -13
17 Ankaragücü 40 38 46:52 -6
18 Karagümrük 40 38 49:52 -3
19 Pendikspor 37 38 42:73 -31
20 Istanbulspor 16 38 27:80 -53

Season Timeline

Probability evolution over time

A statistical line chart showing the evolution of Süper Lig probabilities for Galatasaray 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