How to ruin your own NBA team in two easy steps
A case study in falling for hype trains in fantasy basketball
I may have made a slight miscalculation.
On a whim, I signed up for a fantasy basketball league with the worst type of preparation; supreme confidence in my gut feelings combined with minimal research. This league plays by the popular category scoring system, where each team competes to produce the best results across nine statistical categories like blocks, rebounds, threes, etc. Players who might be undervalued in a points league suddenly become top options–Mitchell Robinson might not score 20 a game, but with elite shooting efficiency and blocks, he’s a great producer for hard-to-find categories.
Despite my lack of experience in this type of league, I joined twenty-three other guys across the globe in a league run by the wonderful guys at Hashtag Basketball (highest recommendation for their Patreon, stocked with great tools and an endless well of content). Nothing sounds sexier than “inaugural dynasty fantasy basketball draft.” I was determined to show that I, unlike my beloved Knicks, had the vision and foresight to build a perennial contender.
Things quickly took a turn.
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In my lizard brain, fantasy takes concepts like probability and distributions of expected results and replace them with a bad gamblers’ confidence. You can win a poker hand with two pair, and bet accordingly, but the itch of a low-chance flush draw will keep my money in the pot long after the odds tell me to bail.
Everyone knows that LeBron James will produce numbers that rival his wildly unhelpful China comments in terms of scale and impact, but what’s the fun in predicting the predictable? Victories that you expect may be sweet, but getting production out of the 10th man on the worst team in the West to shock a rival will always be sweeter; shout out to Richaun Holmes for our week of glory last year.
In this ridiculous 24-team league, I planned to use my draft collateral to maximize my chances at those a-ha moments, investing exclusively in players younger than 25 and full of upside. In doing so, I made rookie mistakes that will more than likely put me squarely in the Knicks realm of contention.
I’ve pulled some data to try and validate my choices, but like calorie counts on a Cheesecake Factory menu, the numbers only make me feel worse about decisions I’m already made.
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Unlike points leagues, getting one number to quantify a player’s overall value requires a bit more than addition and subtraction. A ton of sites, like Hashtag Basketball, build their own models to understand holistic value, and their documentation hints at using z-scores. Much like my posts on ROY and MVP, this model tries to measure a player’s production relative to the league average for that stat and counts the number of standard deviations from the average. A player like Steph Curry, who hits way more threes than the league average, would have a high z-score for that stat, while someone more paint-bound like Rudy Gobert could be negative in in it. Summarizing the z-score across our nine categories produces one aggregate number that, while imperfect, helps provide context on performance.
I gathered data from Basketball Reference for the last five seasons, filtering to players with at least 41 games played with an average minutes per game of at least fifteen. For each season, I calculated the z-score for each stat and then highlighted rookies within that dataset.
This swarmplot visualizes how they finished in that season’s overall score; in each Christmas tree, the density of the branches correspond to the number of players who hit that mark. The values increase upwardly, with each year’s fantasy MVP sitting at the top of tree like a beautiful, hyper-efficient star.
More often than not, rookies end up producing negative total scores, with some outliers.
Only seven rookies produced top 50 value in their first year: Karl-Anthony Towns (19), Mitchell Robinson (30), Kristaps Porzingis (39), Ben Simmons (43), Deandre Ayton(46), Nerlens Noel (49), and Donovan Mitchell (50). Rookie of the year winners like Luka Doncic (63) just missed, while Andrew Wiggins (124) didn’t even crack the top 100.
Of the rookies who did return top value, they appear to be hyper-efficient big men with solid counting stats, plus a ridiculous season from Donovan Mitchell. Here’s how KAT did as a rookie, which showcases the big man upside perfectly.
Normally, these returns would be priced into the average draft position; KAT and KP were high selections picks in the real life draft, but I’m certain their fantasy cost had the rookie year struggles priced into it.
Yet, like politicians with climate change, I ignored the conventional wisdom entirely. I bought into the hype and I sold everything to get Zion Williamson.
I couldn’t resist. I saw dynasty, imagined my thicc prince dunking on the entire league for twenty years of dominance, and my analytical brain melted.
I snagged Nikola Jokic with my first pick–readers will know I adore that Serbian polar bear–and then went full Herschel Walker and traded the whole arsenal for Zion. After the dust settled, here’s how the trade effectively went:
I can already see the F grades from ESPN piling up.
My traded guys ranked 67th, 71st, 151st, and 126th according to last years’ stats, a solid if unspectacular core; my returning players include a guy who may not play 10 minutes a game in Wilson, two young and unproven bigs on the Cavaliers, and the hopeful ROY.
If Zion lands on the KAT side of the argument–his hyper-efficient preseason gives me hope–I may have a shot at winning this trade in the short-term. If he struggles with efficiency like Luka Doncic, I could be looking at my second-best player falling out of the top 60, a brutal return in such a deep and competitive league.
After selling my soul for Zion, I filled out the rest of my team by overpaying for rookies and high-upside risks. Guys like Darius Garland, who played five games in college but also draws comparisions to Damian Lillard and Kyrie Irving and can do things like this:
I added preseason hype trains like Tyler Herro, the bravado-infused Miami Heat rookie with exciting highlights and constantly growing excitement, and found a home for the island of misfit guards like Malik Monk and Frank Ntilikina. Frank especially inspires irrational joy and hope in my calcified Knicks heart, which will make his eventual benching to Elfrid Payton all the more infuriating.
I, like the Knicks, approach this league and season with a focus beyond binary wins and losses. I almost guarantee that this collection of talent will win less than five games the entire season, alternating between excitement and anguish on a weekly basis.
Instead, I’ll use the team as an itinerary for a more diverse NBA consumption. Researching guys like Jokic and Doncic led me to watching random Tuesday night Mavericks and Nuggets games, which introduced me to the joys of Jamal Murray and Jokic two-man games and the surprising aerial dexterity of Dwight Powell. In a wide-open year like this, finding your guys before they’re everyone’s guys, and watching that growth, can be the most fun you’ll have.
Editor’s note: Huge thanks to the guys at Hashtag Basketball for hosting the league and providing a ton of cool data sources. I strongly recommend checking their site out and supporting their content. Independent creators in the fantasy space should be celebrated.