SFM Tracker

Weekly Top 20 Predictions by League

Season to date: Premier League (Completed Games Only)
Every graded pick so far. The boards below show each league's next round.
SFM Top 20 Predictions
119
Predictions
39
Scored
32.8%
Hit Rate
Naive Top 20 Predictions
90
Predictions
27
Scored
30.0%
Hit Rate
SFM outperforms Naive:
32.8% vs 30.0% (+2.8 pp)
Brier Score: Premier League
0.2081
SFM
0.1947
Naive
Naive 0.1947 < SFM 0.2081
Calibration: Premier League
Hit Rate Over Time: Premier League (SFM vs Naive)
Premier League 2026/27 GD08 Upcoming
Overall: 32.8% (39/119) 7 gamedays completed
History: GD01 GD02 GD03 GD04 GD05 GD06 GD07 GD08
Rank Player Team vs SFM Naive Result
1 Erling Haaland Manchester City Aston Villa 64.4% 58.1% Pending
2 Alexander Isak Liverpool Brighton & Hove Albion 55.1% 34.9% Pending
3 Joao Pedro 10 Chelsea Tottenham Hotspur 47.4% 25.8% Pending
4 Bryan Mbeumo Manchester United AFC Bournemouth 43.7% 26.4% Pending
5 Kai Havertz Arsenal Everton 38.0% 24.5% Pending
6 Bukayo Saka Arsenal Everton 35.5% 23.7% Pending
7 Brian Brobbey Sunderland Leeds United 35.3% 20.2% Pending
8 Morgan Rogers Chelsea Tottenham Hotspur 32.5% 21.9% Pending
9 Benjamin Sesko Manchester United AFC Bournemouth 32.4% 33.2% Pending
10 Nicolas Jackson Aston Villa Manchester City 31.1% 30.1% Pending
11 Cole Palmer Chelsea Tottenham Hotspur 30.9% 33.6% Pending
12 Bruno Fernandes Manchester United AFC Bournemouth 30.9% 22.3% Pending
13 Dominic Calvert Lewin Leeds United Sunderland 30.2% 23.1% Pending
14 Zian Flemming Ipswich Town Nottingham Forest 27.0% 31.6% Pending
16 Joergen Strand Larsen Crystal Palace Newcastle United 25.9% 22.1% Pending
17 Kevin Schade Brentford Hull City 25.9% 18.0% Pending
18 Matheus Cunha Manchester United AFC Bournemouth 25.5% 22.7% Pending
19 Arnaud Kalimuendo Muinga Nottingham Forest Ipswich Town 25.1% 27.4% Pending
20 Emanuel Emegha Chelsea Tottenham Hotspur 24.9% 33.0% Pending
19 Dan Ndoye Nottingham Forest Ipswich Town 24.7% 10.2% Pending
4 Igor Jesus Nottingham Forest Ipswich Town 24.2% 15.0% Pending
5 Liam Delap Nottingham Forest Ipswich Town 23.8% 17.6% Pending
17 Emersonn Ipswich Town Nottingham Forest 23.6% 19.9% Pending
20 Cody Gakpo Liverpool Brighton & Hove Albion 22.9% 22.3% Pending
6 Chris Wood Nottingham Forest Ipswich Town 22.0% 28.4% Pending
7 Morgan Gibbs White Nottingham Forest Ipswich Town 20.8% 15.9% Pending
8 Chuba Akpom Ipswich Town Nottingham Forest 18.2% 15.3% Pending
12 Callum Hudson Odoi Nottingham Forest Ipswich Town 13.6% 10.7% Pending
13 James Mcatee Nottingham Forest Ipswich Town 13.1% 9.2% Pending
10 Jaden Philogene Bidace Ipswich Town Nottingham Forest 13.0% 9.1% Pending
11 Julio Enciso Ipswich Town Nottingham Forest 12.9% 10.2% Pending
15 Nicolas Martin Dominguez Nottingham Forest Ipswich Town 8.9% 3.6% Pending
14 Exequiel Palacios Ipswich Town Nottingham Forest 8.2% 8.4% Pending
Understanding Hit Rate vs Brier Score

You might notice that hit rate and Brier Score can tell different stories.

Hit Rate

Simply counts: "How many of my top 20 picks scored?"

A naive model that always picks proven strikers (Haaland, Kane) will have a high hit rate because these players score often, regardless of the match context.

Brier Score

Asks: "How accurate were the probability estimates?"

If SFM says "32% chance" and Naive says "38% chance" for the same player who doesn't score, SFM gets a better Brier Score because its estimate was closer to reality.

Bottom line: Hit rate measures selection quality (who you pick), while Brier Score measures probability quality (how well-calibrated your predictions are). A model can pick slightly fewer scorers but still be more valuable if its probabilities are more trustworthy for betting or decision-making.
SFM Tracker
Top 20 Selection

For each league and gameday, we select the 20 players with the highest median probability of scoring at least one goal as predicted by the SFM.

Frozen Predictions

Predictions are locked before matches are played. This ensures transparent, verifiable performance tracking.

Fair Comparison

We compare SFM's top 20 picks against Naive's own top 20 picks (ranked by historical average). This is apples-to-apples.

Brier Score

Evaluation metric for probabilistic predictions. Measures both calibration and discrimination. Lower is better.