With the Cavs and the Warriors still going at it this week in the NBA Finals, this would ordinarily be way too early for me to start working on a fantasy basketball draft strategy for next season. I realized, however, that this may be the last chance I will look back at my 2016-17 fantasy season and critique it for what it was: kind of bad. I’m doing this to both keep a record of what I did and to help me improve next year.
My league was a 12-team auction draft, 9-category league with 13-man rosters (3 of them bench spots). At the end of the regular season, I was in ninth place, which was three spots short of making the playoffs. That was disappointing.
Here is how I drafted my team last October ($200 budget):
|1.||(13)||Giannis Antetokounmpo (Mil – PG,SG,SF,PF)||$62|
|2.||(14)||Hassan Whiteside (Mia – C)||$48|
|3.||(35)||LaMarcus Aldridge (SA – PF,C)||$36|
|4.||(36)||Victor Oladipo (OKC – PG,SG)||$33|
|5.||(100)||Marcus Smart (Bos – PG)||$1|
|6.||(107)||Elfrid Payton (Orl – PG)||$6|
|7.||(111)||Tristan Thompson (Cle – PF,C)||$2|
|8.||(116)||J.J. Redick (LAC – SG)||$3|
|9.||(123)||Zach Randolph (Mem – PF,C)||$2|
|10.||(124)||Marvin Williams (Cha – SF,PF)||$2|
|11.||(129)||Deron Williams (Cle – PG)||$3|
|12.||(142)||Evan Turner (Por – SG,SF)||$1|
|13.||(148)||Cody Zeller (Cha – PF,C)||$1|
My basic strategy going into this was to avoid the top-heavy approach by seeking out the premier top-five players, and instead focus on grabbing multiple second/third tier players who could serve as the heart of my team. I tried to grab multi-cat stars as I could, and I made an attempt to punt three pointers.
At the time, my top four players – Antetokounmpo, Whiteside, Aldridge, and Oladipo – didn’t look too bad on paper (keep in mind this was the beginning of the 2016-17 season). The problem was that only the Greek Freak outperformed his pre-season value (he was ranked as #7 and ended as #5, which is +2 for value). My other top picks performed horribly (Whiteside -15 value, Aldridge -39 value, Oladipo -77 value). Of the players on my roster at the end of the season, only Antetokounmpo and Whiteside ended up as top-50 players based on average stats. Seven other players were ranked between #50 and #100, but most of these were ranked in the 90s.
I spent a total of $179 on my top four picks, which was 89.5% of my budget. The rest of my team cost me $21 and was more or less fodder for the waiver wire at some point during the season. Of those other players, only Elfrid Payton remained on my team the entire season. He was a good return on investment, ending as the #93 player in my league (+28 value). I held on to some other players for large portions of the season (Zach Randolph, Tristan Thompson), but eventually I dropped them when some better players came along.
Analyzing the league by looking at better-performing managers
My ninth-place finish (.439 winning %) put me 29 games behind Bold Thady Quill III, who was the top manager in my league (.608 winning %). Here is how that manager drafted his team:
|1.||(22)||Jonas Valanciunas (Tor – C)||$25|
|2.||(28)||Kevin Love (Cle – PF,C)||$22|
|3.||(33)||Carmelo Anthony (NY – SF,PF)||$28|
|4.||(37)||Kyle Lowry (Tor – PG)||$32|
|5.||(44)||Serge Ibaka (Tor – PF,C)||$25|
|6.||(46)||Dennis Schroder (Atl – PG)||$14|
|7.||(63)||Goran Dragic (Mia – PG,SG)||$11|
|8.||(64)||Jeremy Lin (Bkn – PG,SG)||$11|
|9.||(66)||Trevor Ariza (Hou – SG,SF)||$10|
|10.||(67)||Marc Gasol (Mem – C)||$11|
|11.||(97)||Monta Ellis (Ind – PG,SG)||$4|
|12.||(110)||Clint Capela (Hou – PF,C)||$4|
|13.||(125)||Devin Booker (Pho – SG)||$3|
What sticks out right away is that Bold Thady really sat on the sidelines at the beginning of the draft and scooped up a lot of upper-middle tier players. Whereas I took four top-25 players and then filled out my roster with what must have been nine players ranked #100 or worse, Bold Thady took the bulk of his players ranked between #20 and #100. He was also able to make up a few nice waiver wire pick ups during the season (including Marvin Williams, whom I dropped early in the season) and make a 1-for-2 trade that seems to have worked in his favor.
In contrast to Bold Thady, the manager of Marc M’s Team, who came in second place in the league (.602 winning %) used a much different strategy. Here are his draft results:
|1.||(1)||Stephen Curry (GS – PG,SG)||$76|
|2.||(3)||Russell Westbrook (OKC – PG)||$73|
|3.||(45)||Derrick Favors (Uta – PF,C)||$22|
|4.||(65)||Dwyane Wade (Chi – PG,SG)||$12|
|5.||(89)||Steven Adams (OKC – C)||$6|
|6.||(119)||Michael Kidd-Gilchrist (Cha – SF)||$1|
|7.||(122)||Joel Embiid (Phi – PF,C)||$2|
|8.||(128)||Al-Farouq Aminu (Por – SF,PF)||$1|
|9.||(132)||Dario Saric (Phi – SF,PF)||$2|
|10.||(136)||Eric Gordon (Hou – SG)||$2|
|11.||(141)||Wesley Matthews (Dal – SG,SF)||$1|
|12.||(147)||Matthew Dellavedova (Mil – PG,SG)||$1|
|13.||(152)||Roy Hibbert (Den – C)||$1|
Rather than waiting, Marc M used around 75% of his budget on two players – BUT, these two players started and ended as top-10 players in the league. The bulk of the rest of his roster was filled with guys ranked over #100. I noticed that most of his roster at the end of the season was not part of his team that he drafted, but some of the guys he got for $2 or less stayed with him. I also noticed that he had quite a few players who significantly out-performed their pre-season rankings. Seven of his players had season-ending values of around +50 or higher compared to their pre-season values. While this kind of thing is great when it happens to you as a manager, I think it’s hard to repeat for most people.
Should I draft stars or should I balance talent on my team?
This leads to the key question: is the optimal draft strategy in fantasy basketball one which involves stars and scrubs, or one which seeks a more balanced approach across the roster? Here are the rankings from my league ($200 budget), along with the number of draft picks each team took that cost above $50, and draft picks between $10-$50:
|Team||Record||Win %||GB||Picks > $ 50||Picks b/t $10-$50|
|– Bold Thady Quill III||103-66-2||0.608||–||0||10|
|– Marc M’s Team||101-66-4||0.602||1||2||2|
|– Team Jozer||96-71-4||0.573||6||1||4|
|– Green Machine||94-73-4||0.561||8||1||5|
|– Jessica M’s Team||95-74-2||0.561||8||1||6|
|– your boy nate||91-76-4||0.544||11||1||5|
|– Vegan Wife’s Team||89-81-1||0.523||14.5||1||6|
|– Jimmy’s Cabin Team||79-90-2||0.468||24||2||2|
|– The Lightning||61-108-2||0.363||42||2||3|
|– Buster Brown’s Team||57-111-3||0.342||45.5||1||5|
While this doesn’t provide much information, it suggests that neither of these draft strategies is a slam-dunk. Loading up on top-tier talent can yield positive results, but only if those a lot of other pieces fall into place over the course of the season and plenty of waiver wire picks outperform their preseason values by a lot. Balancing a team can also yield positive results, but only if those players chosen perform at a level near or better than their preseason value.
Between these two approaches, I think a balanced approach may actually provide more consistent returns for one basic reason: it is easier for a player within the top 100 to finish the season near his preseason value than it is for a player that is over 150 to significantly outperform his preseason value. If you choose the stars and scrubs strategy in a league in which 150 players are drafted, you have to assume that several of your players who rank near the #150 mark will perform at levels that are within the top 100. That is a risky strategy.
While the stars and scrubs strategy is my preferred auction strategy in fantasy leagues involving other sports, it does not seem to work as well in basketball for several reasons. First, players are more interchangeable in fantasy basketball. Any player you get for your team can hypothetically contribute to any stat category in your league. Whereas sports such as hockey and baseball rely on divided stat categories (e.g. between hitters and pitchers, or offense and goalies), all basketball players can potentially help you in every single stat category. I think that this format lends itself better to having balanced talent on your team than concentrating it within only a few players.
Second, basketball player performances are more predictable than players in other sports. Whereas football players’ performances may be highly impacted by the performances of their teammates, it’s not so much in basketball. This means it may be difficult to harvest talent from the waiver wire, and a better bet to draft middle-round talent during the draft.
Third, basketball games are staggered throughout the week, which leads to little in the way of talent rot. All the players on your team will likely contribute to your weekly production, unless you are in a league with a very large bench. This means that having a number of speculative (boom or bust) players on your team can do more harm than having several middle-tier players.
Putting all of this together, I think that the optimal fantasy basketball auction draft strategy may be one which spreads the budget around. In my league discussed above, I dedicated about $180 on four players on a 13-man roster, which means I invested 90% of my budget in 30% of my players. What if instead, I invested 95% of my budget in 75% of my players? This would mean that I would have approximately $20 per draft pick for 10 players. Last season, this would have netted me quite a few solid-caliber players like Kevin Love ($22), DeMar DeRozan ($23), Isaiah Thomas ($21), and Ricky Rubio ($18), to name a few. The underlying idea is that although I would forgo the elite production of few high-priced players on my team, the cumulative effect of drafting many modestly-priced players would end up being greater. In addition, this strategy would lead to lowering the risk that an injury to one key players would decimate the entire team.
I have discovered over the years that there is no one-size-fits-all approach to fantasy sports auction drafts. What works in basketball may not work in hockey, baseball, or football drafts. With the strategy I discussed here, I hope to have a guide that will lead my fantasy basketball team to glory in 2017-2018.
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