The Rate My Team Machine is a tool that analyses your FPL Squad using advanced algorithms to help you determine the best transfers to earn the most points in the coming weeks.
Try the Rate My Team Machine now
How The Rate My Team Machine Works
Our Fantasy Football Computer calculates the likely number of Fantasy Football points each player will earn by simulating every event in every game many thousands of times. This includes simulating
- player’s time on the pitch,
- their expected number of goals and assists,
- clean sheets, own goals and goals conceded,
- the opponents strength and game style (attacking vs defensive strategies)
- the opponents temperament and how well they fit into the system of play
- chance of injuries, suspensions and international absence
Using this data, we produce a statistically perfect team for each game week. We compare your team to the perfect team to give you an indication of how much work you need to do to improve your team for the coming weeks.
It is very easy to use.
- Import your FPL team, or build a new team.
- Confirm your formation, captain and vice captain
- Click the “Rate My Team”.
We’ll then show you a rating of your team.
You can then go back and change your players to check if transfers are likely to be productive, or if simply changing formation or captain makes a difference. It is great for testing different transfers to see if they will improve your team, and we give you a larger bank balance than on Fantasy Premier League so you can experiment with players that might be slightly out of budget today but might to fall in price over the game week.
For example, my rating with Mannone in net is
but if I swap Mannone for Howard of Everton my rating changes to :
which suggests Mannone -> Howard could be a good transfer for over the coming weeks.
We will also show you the rating of the team with the highest overall rating, and also the highest rated team for each game week, so you can compare your team to other the other teams that have been rated and pick up transfer (or wildcard) ideas.
You can also look at your team rating, then make a copy of your team, change some players and see how your rating compares to your original team. You can import your competitor teams to see how your team stacks up against their team, and the tool will highlight in red when their rating is higher than your rating!
To create a duplicate team, choose “Create duplicate team” on the “COMPARE ONE OF MY TEAMS” option on the rating page.
Wildcard active, transfers made, free transfers and cash in the bank
Its not all about the stats. Even though we know our model is one of the most advanced in the world, you cannot beat the judgement of experienced FPL managers. So once you have your rating and feel you have the best team for your transfers, just click “ASK FOR HELP” and your team is automatically posted into the latest Help My Team article for feedback from our fellow managers.
When you click “ASK FOR HELP”, we look up how much cash you have in the bank, how many transfers you have made (and how many free transfers are available) and if your Wildcard is active, and then post this in the help message. This will get the advice you need quicker. For example,
Please help my team
£0.0m the bank, 0 transfer made from 1FT, Wildcard available.
If you already have a team saved in the RMT Machine, then you will need to re-import your team.
What’s more, your team is saved so that when you come back you do not need to reload your squad. And best of all you can save more than one team, so you can check out the likely transfers of your Head To Head opponents.
This integration of people and statistics makes Fantasy Football First’s Rate My Team tool one of the most powerful on the internet.
We will continue to improve our site in the coming weeks, so be sure to let us know what you think of our changes, and please also let us know your suggestions and improvements.
The model is based on “Competing with Humans at Fantasy Football: Team Formation in Large Partially-Observable Domains.” by Matthews, Tim, Sarvapali D. Ramchurn, and Georgios Chalkiadakis (AAAI 2012) and is provided with thanks to the University of Southampton.