Using a Pearson Correlation, we can test the relationship between the ADP results from MockDraftCentral for each player with their default ranking from the site. There are various schools of thought on this but generally a coefficient above 0.750 is considered a strong relationship between two groups of data (0.00 represents no relationship at all while 1.00 represents a perfect relationship). When we analyze the Top 50, Top 100 or Top 180 players from the rankings, the correlations between the site rankings and the resulting ADP show an extremely strong relationship:
Top 50: .975 r value (95.06% variance)
Top 100: .976 r value (95.26% variance)
Top 100: .976 r value (95.26% variance)
Top180: .937 r value (87.8% variance)
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| Average draft position matches site ranking almost perfectly |
Yet nearly every fantasy baseball site, including my own, that determines whether a player is a good bargain or not will reference MockDraftCentral's average draft position data as if it actually means something. I'm guilty of this because there really isn't any viable alternative. The concept of knowing a player's average draft position is wonderful as it's great to know where a player is being drafted versus their expected performance. However, if we go ahead and look at a player's ADP on three different mock draft sites, we get three different values that may or may not be even close to one another. If ADP truly represented what the public thought of a player, that would not be the case.
Simply put, the data that comes from these sites is poor and not reliable. It's something that could be so vital if it was truly usable data but the current system of mock drafting is what creates these poor results. In the next part of this series, we'll take a look into exactly why this current way of doing mock drafts is tailor-made to create bad results.
Simply put, the data that comes from these sites is poor and not reliable. It's something that could be so vital if it was truly usable data but the current system of mock drafting is what creates these poor results. In the next part of this series, we'll take a look into exactly why this current way of doing mock drafts is tailor-made to create bad results.







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