In this post, I take a look at the final top 10,000 teams of this season in a similar manner to season 13/14.
Top 10K History Pages
Let’s start our acquaintaince with the best teams with a background check:
|Previous top10K finishes||6,406||2,076||893||377||169||59||17||3||0||10,000|
|Previous top1K finishes||9,179||683||121||17||0||0||0||0||0||10,000|
- Experience mattered a lot this season, much more in comparison with last season. Successful novices accounted for just 4% of the final top 10K, 26% of the teams had no more than 2 years of experience behind them. That’s a pretty big drop compared to last season’s respective values of 9% and 40%.
- The amount of teams without a single top 10K finish in the past has declined by 15.2 percentage points. Could this be down to the fact that the amount of such teams in FPL has increased by 7,925 teams that made their first top 10K finish last season? Doesn’t look so. Only 1,022 teams, or 10.2%, have managed to finish in top 10K for a second season in a row. Being successful in the past was a more important factor this season as well.
Top 10K Heroes
- You might have noticed that not a single FPL player has managed to accomplish 9 top 10K finishes since season 06/07. Bono’s Heroes (tommie åkesson), finished only at 25K this time and, thus, has lost his unique status. He is now one of four FPL managers who have 8 top 10K finishes, with Costa del Kuqi (Jay Egersdorff ESP), whom I also singled out a year ago, having the most impressive history. The other two heroes are Sumo McNulty (Jack Kennedy) and Mill Hill Villans (Ulrik Nylund).
- For 17 teams it was a 7th top 10K finish:
- Just 2 previous FPL champions have been spotted in the final top 10K of this season:
Road to Success
a. Getting there for the first time
At what point of season did the final 10K teams get into top 10K?
The diagram above shows what share of the final top 10K teams:
- were in top 10K after any particular gameweek (dark bars);
- had already been in top 10K at least once after a particular gameweek (light bars).
A year ago, I described a corresponding chart in the following way:
Teams that finished the season in top 10K got there gradually… A great start wouldn’t hurt, but it’s far from necessary.
Oh well, what did I know?🙂 Even though the general pattern was similar, this season was rather different in this regard as the first half of the season was more important. After a few calm weeks, there was an explosion in GW8: 25% of the final top 10K were already in top 10K at that point.
The final top 10K teams arrived to the top echelon of the rankings much earlier compared to last season. Two-in-three broke into top 10K for the first time during the first half of the season; one-in-two were in top 10K at the season midpoint. The difference between the two seasons is obvious in the charts below:
One thing that seasons 13/14 and 14/15 had in common was the importance of the final eight gameweeks for determination of the final top 10K. Roughly four-in-five final top 10K teams got into top 10K for the first time some time before GW31, but only three-in-five were in the top 10K at that time. For two-in-five final top 10K teams these final gameweeks were a crucial period for securing a top 10K finish, I guess wildcards were an important factor during this spell.
b. Overall Ranks
The charts below show the importance of the first half of this season from another perspective. 75% of the final top 10K teams were inside 25K by the season equator.
Above, I calculate average overall ranks for different percentiles of the final top 10K:
- the median, or 50%, shows where was the ‘middle team’ of the sample, i.e. so that 50% of the final top 10K were above and 50% of the final top 10K were below this team;
- the 75th percentile corresponds to the current overall rank so that 25% of the final teams were below it;
- the 95th percentile corresponds to the current overall rank so that 5% of the final teams were below it;
Because of scaling issues, I divide this diagram into two, one for each half of the season. I don’t include the worst team’s overall rank for the same reason.
c. Overall Points
Gaps in points that could be closed by teams lagging behind were also smaller than in season 13/14. The Golden Boys (Tom Alden) closed a 114 point gap in the final eight gameweeks in a spectacular rise from 140K to 7K.
The diagram above shows how a distance from concurrent top 10K mark changed during the season for:
- the median team of the final top 10K teams, i.e. so that 50% of the final top 10K teams had less points at that moment;
- the 75th percentile;
- the 95th percentile; and
- the worst team of the final top 10K at each point.
Transfers and Point Hits
An average top 10K team made 42.9 transfers. Numbers ranged from 8 (park lane coys by thomas Walton) to 84 (Monkeys With Crayons by Tim Upson) transfers in total. The distribution for the number of transfers is below; the graph also shows average overall ranks calculated for each number of transfers made.
The diagram below shows the distribution of points spent on transfers. For an average final top 10K team extra transfers cost 35.0 points. Only 241 teams took no point hits at all, and this number includes the champion, Simon March. Monkeys With Crayons by Tim Upson spent 196 points on extra transfers.
There are some other interesting charts with respect to transfers and wildcards, I’ll publish them in separate posts some time soon🙂