MFL10 Roster Construction: What Worked in 2016?

In January, I took at look at the players with the best and worst win rates across 2016 MFL10 best-ball leagues. Here, the focus shifts to roster construction. Roster construction is defined by the number of players a team drafts at each position.

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Understanding Win Rates: The Picks that Won MFL10s in 2017

The following looks at the win rates[1]Win rate is a ratio defined by the number of times a player was on a first place roster divided by the total number of times that player was drafted. This analysis encompasses players drafted in at least 500 MFL10, MFL25, MFL50 or MFL100 leagues. of players drafted in close to 5,000 MFL10 best-ball leagues in 2017.((“2X,” or double-up,…...

MFL10 Optimization Part 2: Quarterback, Tight End and Defense

In part one of this project, we followed the evolution of a fictional 2016 MFL10 draft from an inefficient mess into a league full of optimized rosters. That first step provided us with some general guidelines for roster construction. Now we dig a bit deeper, in search of more detailed and more actionable conclusions. We’ve already learned, for example, that we want to roster either two or three…...

MFL10 Optimization: Evolution of a Perfect Draft

What would an MFL10 draft look like if all twelve players knew exactly what they were doing? You may never have asked yourself that question, but I have spent more time thinking about roster construction than I care to admit, so I decided to find out how an “optimized” draft might play out…....

Understanding Win Rates: The Picks that Won MFL10s in 2017

The following looks at the win rates[1]Win rate is a ratio defined by the number of times a player was on a first place roster divided by the total number of times that player was drafted. This analysis encompasses players drafted in at least 500 MFL10, MFL25, MFL50 or MFL100 leagues. of players drafted in close to 5,000 MFL10 best-ball leagues in 2017.((“2X,” or double-up,…...

MFL10 Optimization Part 2: Quarterback, Tight End and Defense

In part one of this project, we followed the evolution of a fictional 2016 MFL10 draft from an inefficient mess into a league full of optimized rosters. That first step provided us with some general guidelines for roster construction. Now we dig a bit deeper, in search of more detailed and more actionable conclusions. We’ve already learned, for example, that we want to roster either two or three…...

MFL10 Optimization: Evolution of a Perfect Draft

What would an MFL10 draft look like if all twelve players knew exactly what they were doing? You may never have asked yourself that question, but I have spent more time thinking about roster construction than I care to admit, so I decided to find out how an “optimized” draft might play out…....

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