The FOG Approach

Each prospect slotted on the Big Board receives a classification of either a SWINGSTABILITY or HYBRID. While there are infinite big boards thrown around that rank the same group of 50-60 prospects, the primary variance for evaluators is the read on how each prospect develops over their career. The breakdown of each prospect using this classification is based on the see-saw balance of their upside versus their potential for imminent production. Each and every prospect has hints of both a swing, or high upside, as well as stability, traits that can translate immediately and are already shading towards their high end value, but their classification leans on which tern makes up the bulk of their stock based on my evaluation. At maximum, 10 prospects of the 50 listed are classified as a hybrid , where they bring forward a safe floor that can translate quickly, but their youth and tools provide strong upside. It is limited to just 20% of the complete board because every prospect has an argument for both, thus how this model can be applicable to for all evaluators based on their perception. In turn, it puts a classification on the type of selection that each prospect is and how they may fit the direction of their organization.

Moving into the Big Board, it becomes an illustration of how I value their stock as a swing – high upside but near equivalent downside – versus their stability – a scale of how strong their floor is and how close they already are to what their ceiling is. At an absolute maximum, each draft class produces 4 “Superstars” or generational talents. On average, it is closer 2 prominent stars per class. Thus, swinging for the fences by vaulting every high upside, or young prospect with enticing tools, towards the top of the board is relatively erroneous. Entering the 2021 NBA Draft for an example, how many organizations are in a complete rebuild? Being generous, I will say 5, in the Houston Rockets, Oklahoma City Thunder, Detroit Pistons, Orlando Magic and the Cleveland Cavaliers. Each have 1-2 young players already showing hints of being a cornerstone, but fair to say each is seeking more spark for the future. Following the top 5 picks, or the picks of these 5 teams, the value of a stable prospect, or one who carries a high floor as a high impact role player, should be equally or more valuable than a big swing. As a case study, the value of inserting Franz Wagner into a New Orleans Pelicans roster stronger than a high upside prospect like Jalen Johnson. Franz Wagner, classified as a stability pick, may not have a path to utter stardom, but he provides winning production from day one and projects, for me, to be high impact, long term role player on championship levels rosters. In simple, Franz Wagner lands 6th overall on my board, not because I am arguing he’s a future multi-time All-Star and has elite upside, but rather because I believe very strongly in his return and the investment in a high level role player in this range due to the sparse quantity of All-Star talent in each draft. In nearly every draft, the first 3 picks are nearly always swings, as those teams landed in the lottery for due reason – they lack direction. Swings come in different shapes and sizes, where their deviation from upside to downside do not necessarily mimic each other. Swing picks can dictate an incredibly positive direction, like Trae Young was for the Atlanta Hawks, Devin Booker was for the Suns or Donovan Mitchell for the Jazz. Yet, they are considered swing prospects because of players like Emmanuel Mudiay, Mario Hezonja, or Dante Exum, where their downside. On the other hand, prospects like Mikal Bridges, DeAndre Hunter, PJ Washington, Marcus Smart and even a guy like Cody Zeller fall into the category of stability picks, but return strong value compared to their draft slot and the rest of the field. Neither denomination carries a negative connotation, but more so a deeper dive into the context of my evaluation.

The concept can lend a hand to organizations to initially target a category – swing, stabilizer, or hybrid.

Teams opting for a SWING selection may fall in the following categories.

  • Seeking to rebuild due to a lack of direction and cornerstone players.
  • Well-structured with depth and minimal cap space, planning for the future beyond their cornerstones.

2021 Primary Examples

  • Houston Rockets
  • OKC Thunder
  • Detroit Pistons
  • Utah Jazz

Teams opting for a STABILIZER selection may fall in the following categories.

  • Contesting franchises looking to add instant impact production between and around their solidified stars.
  • Restructuring franchises comprised of a high percentage of youth, swing prospects still in development phases.

2021 Primary Examples

  • New Orleans Pelicans
  • Boston Celtics
  • Atlanta Hawks
  • Orlando Magic

Teams opting for a HYBRID selection may fall in the following categories.

  • Teams in a gloomy area – not necessarily competing but their high level players are near or in their peak, making it difficult to enter a rebuild.

2021 Primary Examples

  • Toronto Raptors
  • Chicago Bulls
  • Indiana Pacers
  • San Antonio Spurs

CASE study

Research by Aditya Fuldeore

Using data from the last 10 NBA draft first rounds via Basketball Reference.

Data key:

  • Y = Yes, they are a One and Done prospect: spent one year in college before declaring for the NBA draft
  • N = No, not a One and Done prospect, instead spent multiple years in college
  • H = A prospect that last played for a high school before the NBA
  • I = International prospects

From the 2011 to 2020 NBA drafts, 36% of first round selections were One and Done prospects. 48% were non-One and Done college players, 1% were high schoolers, 15% played internationally. In total, 108 One and Dones, 144 non-One and Dones, 3 high schoolers, 45 international prospects.

What is the All-Star rate of One and Dones?

  • Using all drafts except for the 2019 and 20 drafts (too early) – Zion Williamson was the only one out of these two drafts to make an All-Star game
  • The average 1st round One and Done All-Star from 2011 to 2018 was selected at pick 4.8

From the 2011 to 2018 1st rounds, out of 85 One and Done’s, 16 were All-Stars.

[An 18.8% All-Star rate among One and Dones]

Chart, bar chart

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The above bar plot is from 2011 to 2020 first rounds. The “Y” group represents the One and Dones, and they are the group with the most All-Star appearances out of all the other prospect declaration groups.

What is the bust rate of One and Dones?

  • Using all drafts except for the 2019 and 20 drafts – too early
  • Bust: A player that did not meet expectations relative to his draft slot

Out of 85 First round One and Dones from 2011 to 2018, 48 were busts. 

[56.5% Bust Rate]

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This barplot shows the number of busts from the 2011 to 2018 1st rounds. The non-One and Dones have the most total busts, but have a lower bust rate of 50.4% International prospects have the highest bust rate in this draft class range at 61%.

After performing some generalized linear modeling on the data, I found that the odds of a bust increase more with an international player. They increase second most for One and Dones, and non-One and Done college players are last. I deleted the three high school picks from the data for this calculation due to a small sample size.

Where are One and Dones selected?


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All 10 first rounds in the data had a One and Done player go #1 overall. The amount of One and Dones (Y) decreases into the mid-first, while the amount of multi-year college players (N) increases. However, there are more One and Dones taken with the last three picks of the first round, indicating contending teams may want to take chances on raw prospects that won’t have to play immediately at those picks. 

There also seem to be tiers of international player selections. The “best” international prospects are taken in the top 10, then a drop and the next bundle gets taken in the late teens, with the last tier going in the mid to late 20’s.

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Here, we can see that the amount of One and Done draftees in the first round has generally increased over the last decade.

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This boxplot demonstrates the distribution of where players with each declaration type have been taken. One and Dones (Y) have been selected with the most range, international prospects (I) with the most variability, while high schoolers (H), are packed in the 10-25 range, although they only have a 3-player sample size.

According to this boxplot, One and Dones are selected the highest on average, followed by international prospects, then non-One and Done college players. This shows that teams in the draft lottery often go for upside and potential rather than safe production.

Overall, One and Dones “bust” at a higher rate than non-One and Dones (yet less so than internationals), but also “hit” at a higher rate.