As we approach football season kickoff, fantasy football leagues are starting to draft. I am in a league myself and was discussing with some friends what the best draft position is. Many said the first; others said the last; and some said the position doesn’t really matter. I then realized I have the ability to see which position is *statistically* the best. I do run a statistical analysis website, after all.

For this analysis we assume your league is using a snake draft, which means that the team with the first pick in the first round gets the last pick in the second round (and the team with the last pick in the first round gets the first pick in the second round). This creates a more balanced draft. If your league does not use a snake draft, and rather has the same draft order in every round, the first pick should always be best since you’re getting the first pick of players.

To determine which position is “best”, we must first define what “best” is. I define it as *the pick that will most help a team win the championship*. In this article when I say a “higher” pick, I mean a lower number pick (so the “highest” pick is the 1^{st} pick).

The following is a bar chart of the first-round pick number that the winning team of the league had in 10-team fantasy leagues on ESPN Fantasy Football.^{1} All data is from the 2015 fantasy football season.

## 10-team leagues

From this data, no single pick has a definite advantage. However, we can still find useful information to help decide what picks are better than others. The data shows that the 1^{st} pick is not necessarily the best, as some believe. In fact, the trend line shows an upward progression as the draft position gets lower, meaning a lower pick tends to be better. The 1^{st} pick is the third worst (out of 10) since seven other draft positions won more often (the worst pick is the 3^{rd}, while the second worst pick is the second).

While the data surely isn’t conclusive, the team with the tenth (or last) pick wins most often. The 10^{th} pick wins 33% more often than the 3^{rd} pick, a fairly significant margin.

## 12-team leagues

12-team leagues give us a more broad view than 10-team leagues of what draft picks are better. Again, a lower draft pick appears to be advantageous, although in 12-team leagues this seems more pronounced. The worst pick, in this data at least, is the third, while the best is the ninth (the 9^{th} pick wins 27% more of the time than the third). The 1^{st}, 2^{nd}, and 3^{rd} pick are almost exactly equally bad. In our data, they each won 610, 609, and 607 times respectively. Likewise, the 9^{th}, 10^{th}, and 12^{th} pick are all approximately equally good (769, 763, and 766 wins each respectively).

**In conclusion, a lower draft position (e.g., #10, 11, and 12 in a 12-team league) generally wins more often than a higher position. Again, this is not conclusive, and depending on your draft strategy, might not hold true. There is no decisive advantage to having a certain pick; the most important thing still comes down to what actual players you draft and how you manage your team.**

Just for fun, here is a pie chart of the number of teams in all leagues:

This means that 41.6% of all leagues have 10 teams, 38.2% have 12 teams, and 9.41% have 8 teams.

## Technical explanation behind analysis

I first had to decide how to obtain my data. My friends and I use ESPN to host our league, so I decided to use ESPN fantasy league data. This caused a couple problems:

- Many ESPN leagues are set to private, meaning you must be in the league to view them.
- There are not the same number of teams in every league. Some leagues might have 4 teams, others might have 20, and everywhere in between.

To solve problem #1, I only collected data from leagues that are public. There was no way around this that I could think of. For problem #2, I collected data for the number of teams in every league along with the winner’s first-round draft position. I then analyzed 10-team and 12-team leagues separately. You can feel free to use the data at the bottom of this article to perform your own analysis with different league sizes.

Next I had to actually obtain the data. I wrote a script (the code is at the bottom of this article) to go through 100,000 leagues and get the data I needed. With the data finally in hand, it was time to analyze! Read above for the analysis of the data.

^{1}: If the winning team did not have a pick in the first round (because they traded that pick away and did not receive another first round pick in return), that league was not included in this article’s data.