FPL Team Selection – Where are we placed? Season 2021/22

WHERE ARE WE PLACED 2020/21

While I was working as a Trader I used to always write a proprietary report for trade ideas called, “Where are we placed?”. The idea was to first analyse where we stand currently and based on that and our forward assumptions (based on historical evidence and future event risks) try and envision the best possible outcomes in the various asset classes.

I have now decided to the do the same here in FPL and I will be publishing this report every 6 to 8 GW’s keeping the above process in mind. In case I can time it with a large fixture swing or Wildcard deadline then I might do that as well.

It was a great summer with the Euro’s and while Covid hasn’t been completely eradicated we are reaching a critical juncture for vaccination globally and hopefully this unfortunate event will be behind us soon.

In this report I will be analysing Team defence and offence. I will be ranking players based on their positions, checking the FDR for fixtures and finally sharing a few pros and cons for a few drafts that I had made. The report will conclude with my final draft with which I will be starting GW1 this season.

Before I deep dive I would like to share the link to our GFCT & IFCT Telegram chats:

Our Mission Statement

The Global FPL chat’s aim is to bring together dedicated FPL managers who have a common goal to win FPL. The chat is filled with managers who understand that the battle to succeed is only against ourselves. To spend time with managers who challenge and inspire us to grow. The ability for us to understand the trends and manage our individual emotions is what leads us to become better managers. The core group of this chat will try and streamline discussions, research and debate so that everyone can improve their knowledge and decision making ability to play the game at their best.

Give me six hours to chop down a tree and I will spend four hours sharpening my axe

– Anonymous Woodsman 

There are two league and within each League we will have two winners as stated below:

Prize for the League Winner: A 1 year subscription to FFHUB

Prize for the League Cup Winner: A 1 year subscription to FFHUB

(Sponsored by FFHub)

We are very particular about our zero-tolerance policy so please have a read before joining the chats. And while you will be missing out you are most welcome to join the leagues even if you don’t want to join the chats. The League final closing will share the deadline of GW9.

So let’s attack the upcoming GW’s and try and learn from the data what it is that it signals and whether there are any moves we can make that can help us accelerate our overall rank going forward. We intend to continue to do well and make better FPL decision, so lets get right to it!

Let’s start with the TEAM DATA:

OFFENCE: GW1 TO GW38 (2020)
ATTACKING STATS for EPL 9/20

The above table has been sorted by Big Chances Created by teams over the season.

The coloured columns at the end of the table are for Goals Per Match – and their deviation from the median. Big Chances Per Match – and their deviation from the median.

We want to target teams that score atleast 55 goals a season which gives us an average of 1.45 per game. If they can do that like Spurs with only 271 shots in the box then nothing like it. It shows how clinical both Son and Kane were.

We had a season xG of 980 but total goals that were scored were only 942.

Teams like LIV, CHE, AVL, BHA, SOU, WOL, BUR underperformed their xG and failed to convert their big chances significantly.

Teams like MCI, TOT, WHU, LEI and ARS outperformed their xG and converted most of their big chances.

Keeping the GPM% and BCPM% in mind looking at last season the teams I would like to target for my attack to begin with are:

LIV, MCI, MUN, CHE, TOT, LEE, WHU, AVL and LEI.

DEFENCE: GW1 TO GW38 (2020)
Defensive Stats for EPL 19/20

The above table was sorted by Big Chances allowed by the teams while defending.

The coloured columns at the end of the table are for Goals Per Match conceded – and their deviation from the median. Clean Sheet percentage – and their deviation from the median.

Ideally we want a team that allows less than 1.25 goals per game and one that achieves atleast 10 clean sheets over the season.

Over the last few seasons only 8/9 teams used to give us 10 CS’s per season but last season we had a whopping 13 teams do that.

This is reflected by these teams who significantly outperformed their xGC – ARS, TOT, MUN, WHU, BUR. With the largest outperformance coming from LIV, AVL and LEE.

From the perspective of GPM% and CS% it clear to see that MCI and CHE are miles ahead of the pack. LIV & ARS while lower on the CS% never conceded too many even when they did. AVL on the other hand outperformed it’s expected CS data.

Based on the above data the teams I would like target from a defensive perspective are:

MCI, CHE, LIV, BHA, ARS, TOT, MUN, WHU, AVL and EVE.

A gentle reminder:

The worst teams give us around 7 to 9 CS’s a season. So anything above 10 CS’s is good and anything above 12/13 was fantastic!

13GW’s out of 38GW’s is 34%.

So before jumping the ship on decent defending FPL assets please realise that most of the time (66% in this case) you will not have a CS even with the best. We are relying on their attacking threat for returns and attacking defenders in good teams cost top dollar!

I also wanted to show a pictorial representation of how a few teams improved or weakened in the second half of the season:

The Blue highlight is from GW1 to GW20 and the Red highlight is from GW20 to GW38.

A larger Right side shows greater Attacking ability while a larger Left side shows greater defensive ability.

It’s quite self-explanatory for example: without Grealish AVL suffered both on the defensive and offensive side in the first image. BHA on the other hand improved significantly in the second half of the season with regards to their Defence.

The final comparison is to highlight how much Liverpool had deteriorated since the their 21 CS season in defence. As they were trying their best make it to the UCL one could assume that they had to prioritise attack in the final weeks last year. Liverpool conceded a whopping 84 Big Chances last season – worst in the league along with SOU, LEE and CRY. But this is a theme we have noticed since before VVD got injured and it will be interesting to see how they get on this season.

Please keep in mind that a few teams have new coaches and the above data might not truly hold for them. If it was mid-season we might have or might not have jumped on their assets due to a managerial change.

Fixture Difficulty Rating – FDR

FDR at the very start of the season is a very opinion oriented process and I rather depend upon others who know what they are doing.

I prefer using Tim Bayer’s FDR which is available for free. The link to the same is here:

From GW 1 to GW 7 this is the table:

Tim Bayer FDR

From GW 8 to GW 14 this is the table:

Tim Bayer FDR

MUN, WHU, BHA, WAT, EVE that have good fixtures in the first 7 GW’s hit the bottom of the table in the next 7.

MCI, CHE, SOU, NOR who have tougher fixtures at the start move to the top of the table post GW7.

TOT, LIV, WOL, LEE, LEI, NEW, ARS remain in the mid to top range throughout the first 14 GW’s.

Please keep in mind that fans are back and we expect the Home and Away advantage to have an impact on team form once again.

PLAYER DATA:

Now lets try and analyse how the players did and whether that could help us analyse the potential for them this upcoming season.

I have taken a few liberties as I have tried to maximise the possible potential for each player and then try and zero down on how they could provide points maximisation for our teams.

1. For players like Kane, Salah, Doherty, KDB, TAA, Robbo, Auba etc who are premiums who have played over 2/3 seasons and might have or might not have had a good season last year I have smoothened their data out by the average of the last three years.

2. I have then generated a rank using the weightages below. This again can vary from manager to manager but these are how I have come to my conclusions.

I have chosen the per 90 metric for the FWD’s and MID’s because we want to maximise potential returns with those attacking assets. I have chosen and given CS instead of per 90 metric to DEF’s because we don’t want to to be wasting transfers on our defenders and hold them for longer if possible.

The metric does not showcase a players talent per se. It is about maximising points. Hence if a KDB comes lower than others in the rank metric it could be because of lower minutes, less goals than players in a similar bracket etc.

3. I have shown two tables for each category. One for the rank achieved by the above metric and another one based on points per match along with the players rank above or below the median %.

We need to add our personal gut, eye test and FPL playing style to formulate a team based on these stats. Please use these table only as a sound board. After all these are past performances.

So lets have a look!

FORWARDS:

FWDS SORTED BY RANK

These are the forwards ranked by the weightages given to different sets of data.

The coloured column at the end is their net score and how it stands against the median for all the players in this table in percentage terms.

Kane is in a league of his own despite the smoothening. Vardy, Jimenez, Bamford and Watkins are the next best bets based on the rating.

FWDS SORTED BY PPM

In this table I have simply sorted the FWDS based on their PPM.

We need to maximise our returns from our assets and hence PPM plays an important role. We should think of this as a kind of second filter to the first table.

For example we can see that Wilson, Abraham and DCL have moved up the table here.

RANK + PPM =

So my inference from the two tables would be that Kane and Vardy are season keepers.

Jimenez, Bamford and Watkins should keep ticking along through the season but at a lower run rate.

Wilson, DCL and Abraham can be depended upon when their fixtures are good and probably give us higher returns per match during this period.

MIDFIELDERS:

MIDS SORTED BY RANK

These are the midfielders ranked by the weightages given to different sets of data.

The coloured column at the end is their net score and how it stands against the median for all the players in this table in percentage terms.

Bruno, Son and Salah are in a league of their own despite the smoothening. Mane, Harrison, Rashford, Mount, Raphihna, KDB, Gundo, Grealish and JWP are the next best bets based on the rating.

MIDS SORTED BY PPM

In this table I have simply sorted the MIDS based on their PPM.

We need to maximise our returns from our assets and hence PPM plays an important role. We should think of this as a kind of second filter to the first table.

For example we can that KDB, Mahrez, Grealish and Gundo have moved up the table here.

RANK + PPM=

So my inference from the two tables would be that Bruno, Son and Salah are season keepers.

KDB, Mahrez, Grealish, Sterling, Mount, Harrison, Raphinha, Foden, Mane, Rashford should keep ticking along through the season at a slightly lower run rate.

Maddison, Zaha, Jota, JWP, Barnes can be depended upon when their fixtures are good and give outsized returns per match.

DEFENDERS:

DEF SORTED BY RANK

These are the defenders ranked by the weightages given to different sets of data.

The coloured column at the end is their net score and how it stands against the median for all the players in this table in percentage terms.

TAA, Robbo and VVD in a league of their own despite the smoothening. Cresswell, Doherty, AWB, Shaw, Targett, Digne, Coufal, Chilwell, Cancelo are the next best bets based on the rating.

DEF SORTED BY PPM

In this table I have simply sorted the DEFS based on their PPM.

We need to maximise our returns from our assets and hence PPM plays an important role. We should think of this as a kind of second filter to the first table.

For example we can that KDB, Mahrez, Grealish and Gundo have moved up the table here.

RANK + PPM=

So my inference from the two tables would be that TAA, Robbo and VVD have consistently been good over the years. (CS’s have been an issue lately and we will have to monitor this as the season progresses)

Chilwell, Digne, Cancelo, Shaw, AWB, Cresswell, Coufal, Targett, Doherty, Stones should keep ticking along through the season – run rate should be good but rotation is the key factor reducing the appeal for a few (MCI & CHE assets) while the rest are expected to return in the form of attacking returns even when we don’t get CS’s.

Dias, Dunk, Rudiger, Mings, James, Keane, Evans, Azpi are the next best bet within the bracket.

Phillips is the only 4.5 mln asset that has made the PPM table and had attacking returns. If he gets a move to another club then he would be my first preference in the 4.5 mln bracket.

GOALKEEPERS:

GK’s SORTED BY CS’s

These are the goalkeepers sorted by the amount of CS’s they kept last season.

The last three columns are GCPM – Goals conceded per match, CS % – Clean sheets percentage and BPS Mean – how many bonus points they have and how far they stand from the median returns of the players.

As per the GCPM data:

We see that Ederson, Mendy, Sanchez, Allison and Henderson do well. We also see that they all fail in the bonus department because they have such good defensive assets ahead of them.

As per the CS % data:

We once again see Ederson and Mendy but we also see De Gea, Sanchez, Pope and Martinez amongst the best.

As per the BPS data:

We see Guita and Lloris do okay with Pope and Meslier doing very well but Martinez is in a league of his own.

We have seen over the last few seasons that we never know when the defence of a team will improve and even in the case of teams like Liverpool, when the defence will collapse.

Therefore I like a combination of the metrics shown above so that even when my GK doesn’t get a CS he can get save points and be on the bonus chart. Based on that my preference for a keeper with outsized returns are Martinez, Pope or Meslier if Leeds can keep up their latter half of the season defending.

For more steady returns betting purely on CS’s I would invest in Ederson, Mendy or Sanchez.

Guita is one to keep an eye on if they are able to improve defensively.

TEAM CONSTRUCTION:

A couple of things I will be looking at with regards to the construction of the team:

1. Extrapolation of points

2. Total Big chances for the team

3. Total Big chances created by the team

4. Total Bonus points for the team

5. Average Points per match

6. Captaincy Options in the team

A few other considerations one should keep in mind while constructing their teams:

Talisman Theory by Who Got the Assist:

This is very important to dissect who the main player from a team is with regards to FPL points.

For example: City scored 83 goals but none of their assets crossed 160 points. Where as Everton scored only 47 goals and DCL scored 165 points.

When you hear managers talk about can a certain player be covered in FPL – the Talisman report is the one shop stop to understand why certain players/teams can be covered and others that cannot.

Please refer to FDR spoken about earlier with regards to fixtures spoken about below.

Full budget used in all drafts.

TEAM 1 – Attacking the opening fixtures:

TEAM 1ATTACKING OPENING FIXTURES
TEAM 1 – ATTACKING OPENING FIXTURES

4-4-2 formation with decent amount of BC and BCC. Bonus and total points is healthy as well. We get 2 solid Captaincy options to choose from.

TEAM 2 – 3 Big Hitters:

3 Big HItters
3 Big hitters

4-4-2 with all 3 popular premiums in the draft. Overall team score and bonus drops while overall goals and assists do not rise.

TEAM 3 – Balanced Squad:

Balanced Squad

Balanced squad

Lot of flexibility with this draft as price points are well covered and one can move easily between positions and price points. However, lack of 2 premiums leads to a drastic drop in overall points.

TEAM 4 – All out attack:

All out attack
All out attack

A 4-3-3 formation with attacking players across the board. Healthy total goals and assists but still we do not see a significant rise in the overall points expected.

TEAM 5 – Big at the back!

Big at the back
Big at the back

A 5-3-2 formation where the overall score jumps nicely for the team due to the attacking defenders being bonus magnets. Goals drop significantly for the team.

TEAM 6 – Long Haul fixture agnostic team:

Long Haul fixture agnostic

Long haul fixture agnostic

A 4-4-2 formation with teams that remain in the middle to top of the FDR table with most of their steady returning players. If one is confident in Captaining Son then one has 3 captain choices in this.

Overall Table:

Overall Table for drafts

I hope this has helped give a fair indication of where the different drafts have advantages and disadvantages.

Captaincy is a very important decision where we FPL managers get to double our points every week. In good weeks it can help us catapult in rank and in bad weeks it can help us hold rank. This is where the balance between a few concentrated assets versus a very balanced team comes in.

I really hope that you have found this enjoyable and I hope that we can use this to our advantage this season.

Thank you so much for reading and I look forward to your constructive feedback as always. I look forward to learning every game week and I wish you all the very best for your FPL teams!

Regards,

Ajit Dhillon.

I would also like to thanks FFHUB for the data used in this publication.

Published by Ajit Dhillon

Living life to the fullest! A father to Ahaan and husband to Ayesha. Creator of the GFCT Project, Chats & Mini Leagues! A financial market participant by profession who absolutely loves sports! I'm a die hard Real Madrid Fan who loves playing Fantasy Football!

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