GW 31 Transfers and Team Selection

Please welcome to the statistics on team selection and transfer activity for GW 31. As usual, see this post for highlights and graphs, full stats are availbale in this google spreadsheet.

TRANSFERS AND TEAM VALUE

Random Sample Top 10K
Number of Managers 20,000 10,000
Average Transfers Made 0.59 1.73
Point Hits Taken 12.5% 45.7%
Average Points Deducted (Incl. No Hits) 0.93 2.66
Wildcards Played 1.1% 4.5%
Wildcard Status
– played 50.3% 92.8%
– available 49.7% 7.2%
– active 0.0% 0.0%
Average Team Value ₤100.5m ₤108.9m
Average Money in the Bank ₤0.8m ₤0.9m

TRANSFERS MADE

Number Random Sample Top 10K
0 72.3% 11.6%
1 8.0% 24.1%
2 10.9% 37.9%
3 4.6% 16.6%
4 and more 3.1% 5.3%
Wildcard 1.1% 4.5%

POINT HITS TAKEN

Point Hit Random Sample Top 10K
0 points 87.5% 54.3%
4 points 6.7% 29.7%
8 points 3.4% 12.4%
12 points 1.3% 2.8%
16 points and more 1.1% 0.8%

TRANSFERS IN

Random Sample Top 10K
1 Gerrard 3.7% 1 Silva 20.8%
2 Silva 3.4% 2 Gerrard 16.7%
3 Sturridge 3.3% 3 Zabaleta 12.3%
4 Dzeko 3.0% 4 Lukaku 12.2%
5 Lukaku 2.6% 5 Dzeko 11.4%
310 different players bought 230 different players bought

TRANSFERS OUT

Random Sample Top 10K
1 Lallana 5.1% 1 Lallana 32.8%
2 Adebayor 4.2% 2 Adebayor 15.7%
3 Hazard 3.9% 3 Hazard 11.5%
4 Rodriguez 2.6% 4 Rodriguez 8.6%
5 Dawson(TOT) 1.7% 5 Mata 7.5%
383 different players sold 308 different players sold

FORMATIONS

Formation Random Sample Top 10K
‘3-4-3’ 41.4% 72.0%
‘3-5-2’ 7.4% 5.5%
‘4-3-3’ 16.1% 15.2%
‘4-4-2’ 31.3% 6.1%
‘4-5-1’ 1.0% 0.1%
‘5-2-3’ 0.7% 0.4%
‘5-3-2’ 1.8% 0.6%
‘5-4-1’ 0.4% 0.1%

CAPTAINCY

Random Sample Top 10K
1 Suárez 39.6% 1 Suárez 92.0%
2 van Persie 9.9% 2 Sturridge 6.0%
3 Sturridge 9.3% 3 Hazard 0.7%
4 Hazard 3.7% 4 Gerrard 0.3%
5 Rooney 3.5% 5 Rooney 0.3%
238 different captain choices 26 different captain choices

STARTING GOALKEEPERS

Random Sample Top 10K
1 Mignolet 26.4% 1 Mannone 22.2%
2 Szczesny 12.0% 2 Adrián 16.4%
3 Cech 8.9% 3 Szczesny 13.7%
4 De Gea 6.7% 4 Mignolet 10.3%
5 Howard 6.1% 5 McGregor 5.9%
59 different goalkeepers 30 different goalkeepers

STARTING DEFENDERS

Random Sample Top 10K
1 Coleman 37.0% 1 Coleman 72.7%
2 Mertesacker 26.3% 2 Mertesacker 27.9%
3 Zabaleta 20.9% 3 Koscielny 24.3%
4 Ivanovic 16.6% 4 Zabaleta 22.0%
5 Fonte 15.8% 5 Ivanovic 17.1%
200 different defenders 97 different defenders

STARTING MIDFIELDERS

Random Sample Top 10K
1 Yaya Touré 43.3% 1 Yaya Touré 81.7%
2 Hazard 37.5% 2 Hazard 72.6%
3 Lallana 27.2% 3 Gerrard 39.0%
4 Nolan 14.8% 4 Sterling 31.4%
5 Gerrard 13.6% 5 Nolan 30.3%
242 different midfielders 95 different midfielders

STARTING FORWARDS

Random Sample Top 10K
1 Suárez 49.9% 1 Suárez 98.3%
2 Sturridge 33.4% 2 Sturridge 78.6%
3 Giroud 21.5% 3 Lukaku 40.5%
4 Lukaku 17.4% 4 Rooney 18.1%
5 van Persie 14.1% 5 Dzeko 13.5%
113 different forwards 44 different forwards

BENCHED PLAYERS

Random Sample Top 10K
1 Kelvin Davis 12.9% 1 Ward(CRY) 21.5%
2 Whittaker 10.2% 2 Kelvin Davis 18.0%
3 Baker 7.8% 3 Lallana 16.8%
4 Boruc 7.4% 4 Fonte 15.6%
5 Harper 6.9% 5 Boruc 14.8%
628 different players on the bench 402 different players on the bench

OWNERSHIP AND CAPTAINCY DISTRIBUTION FOR MOST CAPTAINED PLAYERS

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About This Post

In this post, I take a look at 2 samples: randomly selected 20,000 FPL teams and the top 10,000 FPL teams. Because of the law of large numbers, we can make inferences about the overall FPL league based on the statistics for the random sample. Interval estimates for most statistics for the whole FPL game are also available. If you’re familiar with the concept of confidence intervals, you can point at a specific number characterising the random sample to see 99% confidence intervals for the respective number characterising all the 3 million FPL managers.

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9 comments on “GW 31 Transfers and Team Selection

  1. Hey Metrician, brilliant work always, would it be possible to do some analysis around double game weeks? Like the average number of dgw players in a team and the variance from that number etc? Cheers. Keep up the good work!

    • Nah, unfortunately, I didn’t keep double gameweeks in mind when I was writing my scripts, so I can’t calculate these data easily. I think the only indicator of the number of DGW players per team will be points for minutes played, but these data will only be available after this gameweek… I’ll take a look into this, maybe there is something I can do that won’t take too much time.

    • I did a crude calculation based on the clubs for the players selected by the top 10k and not allowing for autosubs that comes to an average of 8,9 players per team.

  2. Pingback: DGW Player Analysis | FPL Discovery

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