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
↓ 21th1st ↓
Relegation Conference League Second Qualifying Round Conference League Third Qualifying Round Europa League Champions League Second Qualifying Round Champions League Win League
Besiktas 84 pts
84.0 +45 0% 0% 0% 0% 0% ✓ ✓
84.0 +44 0% 0% 0% 0% ✓ 0% 0%
82.0 +31 0% 0% 0% ✓ 0% 0% 0%
71.0 +13 0% 0% ✓ 0% 0% 0% 0%
65.0 +11 0% ✓ 0% 0% 0% 0% 0%
61.0 +9 0% 0% 0% 0% 0% 0% 0%
60.0 +13 0% 0% 0% 0% 0% 0% 0%
60.0 +12 0% 0% 0% 0% 0% 0% 0%
58.0 +8 0% 0% 0% 0% 0% 0% 0%
Göztepe 51 pts
51.0 0 0% 0% 0% 0% 0% 0% 0%
50.0 +1 0% 0% 0% 0% 0% 0% 0%
48.0 -12 0% 0% 0% 0% 0% 0% 0%
Rizespor 48 pts
48.0 -16 0% 0% 0% 0% 0% 0% 0%
46.0 -10 0% 0% 0% 0% 0% 0% 0%
45.0 -4 0% 0% 0% 0% 0% 0% 0%
44.0 -14 0% 0% 0% 0% 0% 0% 0%
41.0 -17 0% 0% 0% 0% 0% 0% 0%
40.0 -24 ✓ 0% 0% 0% 0% 0% 0%
38.0 -19 ✓ 0% 0% 0% 0% 0% 0%
38.0 -32 ✓ 0% 0% 0% 0% 0% 0%
28.0 -39 ✓ 0% 0% 0% 0% 0% 0%
Champions League Champions League Second Qualifying Round Europa League Conference League Third Qualifying Round Conference League Second Qualifying Round Relegation
Rank Team Pts Pld Goals GD
1 Besiktas 84 40 89:44 +45
2 Galatasaray 84 40 80:36 +44
3 Fenerbahçe 82 40 72:41 +31
4 Trabzonspor 71 40 50:37 +13
5 Sivasspor 65 40 54:43 +11
6 Hatayspor 61 40 62:53 +9
7 Alanyaspor 60 40 58:45 +13
8 Karagümrük 60 40 64:52 +12
9 Gaziantep 58 40 59:51 +8
10 Göztepe 51 40 59:59 0
11 Konyaspor 50 40 49:48 +1
12 Basaksehir 48 40 43:55 -12
13 Rizespor 48 40 53:69 -16
14 Kasimpasa 46 40 47:57 -10
15 Malatyaspor 45 40 49:53 -4
16 Antalyaspor 44 40 41:55 -14
17 Kayserispor 41 40 35:52 -17
18 Erzurumspor 40 40 44:68 -24
19 Ankaragücü 38 40 46:65 -19
20 Gençlerbirligi 38 40 44:76 -32
21 Denizlispor 28 40 38:77 -39

Season Timeline

Probability evolution over time

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