Premier League Fixtures Dashboard

Use the charts below to find out who has the easiest or hardest set of matches based on the Premier League Power Index (PPI). The PPI is inspired by FiveThirtyEight's Soccer Power Index (SPI) and follows a very similar methology that computes Team Strength Ratings based on past performances using xG and Adjsuted Goals.

Created by @timbayer93 Data Sources | Fantasy Premier League | Fbref

Fixture Ticker

The below table ranks the fixtures of Premier League teams from most favourable to least favourable using Opta's Power Ranking ELO scores.

Select the current or future GW

The number of GWs to show

Compact View

Notes:

Apply a "Time Decay" modifier to the fixture difficulty ranking

The fixture difficulty uses a time decay which means fixtures "now" carry more weight than those in the future. E.g., GW1 fixtures are weighted higher than GW2 which in return are slightly higher weighted than GW3, and so on. If you like to view the difficulty of fixtures regardless of when they take place turn the toggle OFF.

Forecasted Expected Goals & Clean Sheet Probabilities by Gameweek

The below table ranks teams based on the total Expected Goals (xG) or the total Expected Clean Sheets (xCS) over the next n matches. Select between "Attack" to view Expected Goals or "Defense" to view Clean Sheet probabilities.

Select the current or future GW

The number of GWs to show

ATTACK

DEFENSE

Compact View

↑↓ Click on the column header to sort the table

Notes:

Team Strength Ratings (OFF | DEF) are derived from historical matches using shot-based xG (fbref) and Adjusted Goals scored (i.e., goals are downweighted when the opponent had an on-field disadvantage such as red cards and goals late in a match when already leading).

Match Predictions are then made using Team Strength Ratings using a Poisson model.

Match Forecasts

For each upcoming match, we calculate the expected number of goals each team would score based on their Offense & Defense ratings, a home advantage and a league strength factor.

We then simulate match scores by using a Poisson distribution to get the full probability distribution for 0, 1, 2, 3, and 4+ goals for each team.

Select Match: