BenCrabtree was crowned Fantasy Premier League champion for e 2016/17 season, with an impressive score of 2564 ย by mainly using a 3-4-3 formation. Often this involved rotating the third defender spot between a trio of low priced centre backs and full backs.
This was a popular strategy among last season’s top managers, who also were flexible enough to opt for 3-5-2 when strong third striker options dried up.
This analysis will explore to what extent 3-4-3 is essential to a successful FPL season, with a goal of finding the best formation that can get closest to Ben’s title winning average ย Gameweek score of 67.5.
Method
To do this I calculated every playersโ average points per game (PPG). Then excluded anyone with less than 15 games as an attempt to avoid outliers.
Next I focused on creating price brackets. I ended up with three levels for Goal Keepers (Low, Medium, High), and five for the other positions (Bargain, Low, Medium, High, Elite)
I then looked at the prices by position, to come up with an even spread across the price brackets. ย Once I had the brackets defined I used several players with prices immediately above and below the bracket price, ensuring that the average price of the selected players was close to my bracket price.
For example with goalkeepers the brackets are 4.5, 5 and 5.5.ย ย To determine the average points for the 4.5 position I used players with prices from 4.3 (Hennessey) all the way up to 4.8 (Mignolet). The average price was 4.55 which was close enough. In total 14 players fell within that price range and the average of their PPG was of 3.6
Goalkeepers
| Bracket | Price | Points Per Game |
| Low | ยฃ4.5 | 3.6 |
| Medium | ยฃ5 | 3.7 |
| High | ยฃ5.5 | 4.0 |
Defenders
| Bracket | Price | Points Per Game |
| Bargain | ยฃ4.5 | 2.6 |
| Low | ยฃ5 | 3.1 |
| Medium | ยฃ5.5 | 3.6 |
| High | ยฃ6 | 3.9 |
| Elite | ยฃ6.5 | 4.5 |
Admittedly there was a very small sample size at the 6.5 range, just 6 players.
Midfielders
| Bracket | Price | Points Per Game |
| Bargain | ยฃ4.5 | 2.8 |
| Low | ยฃ6 | 3.3 |
| Medium | ยฃ7.5 | 4.0 |
| High | ยฃ9 | 4.5 |
| Elite | ยฃ10.5 | 5.9 |
Forwards
| Bracket | Price | Points Per Game |
| Bargain | ยฃ5 | 2.6 |
| Low | ยฃ6.5 | 3.7 |
| Medium | ยฃ8 | 3.9 |
| High | ยฃ9.5 | 4.2 |
| Elite | ยฃ11 | 5.9 |
Finding The Optimal Line Up
I tried to come up with a mathematical formula that would give me the optimal line up, but my maths is not up to that level of sophistication, so I decided to crack it with a sledge hammer instead. After a few Google searches I managed to teach myself enough Visual Basic to enable me to write some script that did the following:
For each valid starting line-up, determine every possible permutation of player positions and price, ensure the total of the player prices are within the budget and sum up the team points, save the line up which has the most points. I varied the budgets based on the types of players that would be on the bench.
The assumption being that benched GK are 4.5, Def and Mid are 4.75 and Forwards are 6.0 ย I also included an additional formations where the third forward was classed as bench fodder at 5.0 ย I also limited the number of elite defenders to a maximum of four players due to there being so few of them.
The code also takes into account the captaincy, it takes the player position with the highest PPG and captains that position, so basically just doubles his points. It does not take into account any other game chips.
The Caveats
There several caveats that I’m already aware of
- I’m using the end of season prices for players. Generally the better performing players will have higher prices at the end of the season than they had at the start of the season, but I’m using the start of the season budget amount of ยฃ100m. I’m trying to achieve a score close to the winning teams but in all likelihood they will have better total points because they picked up players before their prices increased and they have a significantly higher end of season budget.
What this analysis should do though, is give the best overall formation regardless of whether it can compare with the overall winner’s score.
- There is no rotation taken into account. For example when using the 3-4-3 formation last seasonโs winner managed to garner significant points from his low budget defenders by correctly picking the player who would excel on each given week. Turning three budget defenders into the equivalent of an elite defender requires a lot of skill and a fair amount of luck. With a large sample size of four million Fantasy Premier League managers ย itโs not unthinkable that a few people get it right for a high percentage of the season. ย Itโs probably a prerequisite for making the top 1,000 in the rankings.
- Form. With all the players used in the analysis I took their average points per game. Itโs an average of their good weeks and their bad weeks. However, a Fantasy manager has the ability to guess when a playerโs form will take a hit, due to knowing the upcoming schedule, transferring him out for another player with a better schedule and hopefully better form to come. Similar to the rotation comment above the more successful managers will be the ones that correctly predict a change in form and transfer in players about to go on a good run of games whilst transferring out players before a bad run starts.
With a ย four million sample size there are going to be some managers who optimise points by correctly predicting form. This analysis does not cater for form
- The average points are used for the price bracket, not the highest points, managers correctly selecting the top performers in the price bracket will optimise their scores above and beyond the scores produced by this analysis.
- This analysis assumes that you can field a full team every week with the positions that are identified. For example if the formation states you need an elite midfielder that will score on average 5.9 PPG, then you need to field an elite midfielder in that position for 38 GWs. If that elite midfielder misses games and has to be replaced by your bench guy who only scores 2.8 PPG then you’re not going to be able to maintain a season long average. Of course if a player gets an injury then you can replace them with another similar elite player, it’s more an issue relating to random weekly benching, as we often see with the teams playing in Europe.
Given all the caveats itโs fair to assume there are more factors influencing my results being a lower score than a higher score.
380 million permutations were evaluated. (3x5x5x5x5x5x5x5x5x5x5x13). Taking 4 hours to process.
The Best and Worst Formations Are…
Here are the results in highest PPG order
| Formation | Team PPG |
| 532x | 56.5 |
| 523 | 56.2 |
| 442x | 55.9 |
| 433 | 55.8 |
| 532 | 55.7 |
| 541x | 55.7 |
| 442 | 55.5 |
| 541 | 55.3 |
| 352x | 55.1 |
| 343 | 55.1 |
| 451 | 54.9 |
| 352 | 54.6 |
(where x signifies the benched forward is ยฃ5m compared to ยฃ6m)
There is only a two point difference between the best formation 5-3-2x and the worst formation 3-5-2.ย ย Itโs interesting to see that the worst formation was 3-5-2, which was used by many successful managers at the end of last season, whilst 3-4-3, the most successful formation overall, was thirdย from bottom on the list.
This tells me that the bench (rotation) must play a significant part in the overall score.
The optimal line up for 532x was:
| Position | Bracket | Price | PPG |
| GK | Low | ยฃ4.5 | 3.6 |
| DEF1 | Elite | ยฃ6.5 | 4.5 |
| DEF2 | Elite | ยฃ6.5 | 4.5 |
| DEF3 | Elite | ยฃ6.5 | 4.5 |
| DEF4 | Elite | ยฃ6.5 | 4.5 |
| DEF5 | High | ยฃ6.0 | 3.9 |
| MID1 ยฉ | Elite | ยฃ10.5 | 5.9 + 5.9 |
| MID2 | Elite | ยฃ10.5 | 5.9 |
| MID3 | Elite | ยฃ10.5 | 5.9 |
| FWD1 | Low | ยฃ6.5 | 3.7 |
| FWD2 | Low | ยฃ6.5 | 3.7 |
| Total | ยฃ81 | 56.5 |
In terms of the objective, which was to try and determine an optimal lineup that compared favourably with the winning score these results are 11 points too low. But these based on average players at the price range. When we substitute in actual players with high PPG in the price ranges, you get this a more comparable figure
| Position | Bracket | Player | Price | PPG |
| GK | Low | Jakupovic HUL | ยฃ4.3 | 3.9 |
| DEF1 | Elite | Alonso CHE | ยฃ6.9 | 5.7 |
| DEF2 | Elite | Cahill CHE | ยฃ6.7 | 4.8 |
| DEF3 | Elite | Kompany MCI | ยฃ6.0 | 5.2 |
| DEF4 | Elite | Rose TOT | ยฃ5.8 | 4.7 |
| DEF5 | High | Valencia MUN | ยฃ5.8 | 4.3 |
| MID1 ยฉ | Elite | Sรกnchez ARS | ยฃ11.7 | 6.9 + 6.9 |
| MID2 | Elite | Hazard CHE | ยฃ10.5 | 6.2 |
| MID3 | Elite | Eriksen TOT | ยฃ8.9 | 6.1 |
| FWD1 | Low | Defoe SUN | ยฃ7.4 | 4.5 |
| FWD2 | Low | Llorente SWA | ยฃ6.3 | 4.4 |
| Total | ยฃ80.3 | 63.6 |
The recommended 532x formation was based on the average PPG across several players, but there were two players last season that were outliers, Junior Stanislas of Bournemouth and Spurs striker Harry Kane. If we switch the formation by replacing an elite mid with a bargain mid and a low forward with an elite forward we get this.
| Position | Bracket | Player | Price | PPG |
| GK | Low | Jakupovic HUL | ยฃ4.3 | 3.9 |
| DEF1 | Elite | Alonso CHE | ยฃ6.9 | 5.7 |
| DEF2 | Elite | Cahill CHE | ยฃ6.7 | 4.8 |
| DEF3 | Elite | Kompany MCI | ยฃ6.0 | 5.2 |
| DEF4 | Elite | Rose TOT | ยฃ5.8 | 4.7 |
| DEF5 | High | Valencia MUN | ยฃ5.8 | 4.3 |
| MID1 | Elite | Sรกnchez ARS | ยฃ11.7 | 6.9 |
| MID2 | Elite | Hazard CHE | ยฃ10.5 | 6.2 |
| MID3 | Low | Stanislas BOU | ยฃ4.6 | 5.1 |
| FWD1ยฉ | Elite | Kane TOT | ยฃ11.9 | 7.5 + 7.5 |
| FWD2 | Low | Llorente SWA | ยฃ6.3 | 4.4 |
| Total | ยฃ80.5 | 66.2 |
66.2 PPG gives 2516 points per season, which would be fifth in the FPL Overall Ranking.
The flaw is that this uses average weekly points and assumes the players will play for 38 games.
Looking at players in similar prices ranges to the recommended 5-3-2x formation, who played a lot of games and use their total seasonโs points we get this.
| Position | Bracket | Player | Price | Season Pts | Weeks |
| GK | Low | Boruc BOU | ยฃ4.5 | 120 | 35 |
| DEF1 | Elite | Cahill CHE | ยฃ6.7 | 178 | 37 |
| DEF2 | Elite | Alonso CHE | ยฃ6.9 | 177 | 31 |
| DEF3 | Elite | Coleman EVE | ยฃ5.6 | 133 | 26 |
| DEF4 | Elite | Walker TOT | ยฃ6.2 | 142 | 33 |
| DEF5 | High | Baines EVE | ยฃ5.8 | 135 | 32 |
| MID1 ยฉ | Elite | Sรกnchez ARS | ยฃ11.7 | 264 + 264 | 38 |
| MID2 | Elite | Hazard CHE | ยฃ10.5 | 224 | 37 |
| MID3 | Low | Alli TOT | ยฃ9.1 | 225 | 37 |
| FWD1 | Elite | Defoe SUN | ยฃ7.4 | 166 | 33 |
| FWD2 | Low | Llorente SWA | ยฃ6.3 | 146 | 37 |
| Total | ยฃ80.7 |
Assuming that when a player doesnโt play, a bench player will contribute 2.5 points.
Total Points = 2174 + 108 bench points = 2282
This team if left unattended for the season, with decent bench, would have finished in the top 17,000.
Conclusion
I don’t think that the formation is a key differentiator, success is more dependent on player selection and timing, transferring in players as they are about to hit form, getting lucky with captaincy and the making good bench rotation decisions.
What I’m taking from this analysis is that you can really use any formation you like the look of and still be successful, as long as you utilise your bench correctly.
So for the start of the season I’m going with the following line-up, my rotation will be concentrated around all the defenders and the four 6.0 priced midfielders. The aim is to rotate the best seven players from the nine focusing on home fixtures and weak opponents.
The best for 2017/18 could be a mixture of 5-3-2 and 4-4-2.
| GK | Low | ยฃ4.5 | 3.6 |
| DEF1 | Elite | ยฃ6.5 | 4.5 |
| DEF2 | Elite | ยฃ6.5 | 4.5 |
| DEF3 | Medium | ยฃ5.5 | 3.6 |
| DEF4 | Medium | ยฃ5.5 | 3.6 |
| DEF5 | Medium | ยฃ5.5 | 3.6 |
| MID1 | Elite | ยฃ10.5 | 5.9 |
| MID2 | Low | ยฃ6 | 3.3 |
| MID3 | Low | ยฃ6 | 3.3 |
| FWD1 | Elite | ยฃ11 | 5.9 |
| FWD2 | Elite | ยฃ11 | 5.9 |
| Bench | |||
| GK | Low | ยฃ4.5 | 3.6 |
| MID2 | Low | ยฃ6 | 3.3 |
| MID2 | Low | ยฃ6 | 3.3 |
| FWD | Bargain | ยฃ5 | 0.0 |
After some quick analysis of the defenders and midfields schedules, I believe I can attain 60% home fixture for the defenders and an 80% home fixture for the midfielders, with most fixtures being against teams in the bottom half of the table.
