Justin

@StephNoh @KevinOConnor @JonathanTjarks RIP Tjarks

My other story, this one on the media side: When I was very early in my career, there were a few industry people who were actively rooting for me to fail, which led to me having anxiety during scrums. @KevinOConnor and @JonathanTjarks (RIP) knew me only from Twitter. When I met them IRL, both independently gave me pep talks, told me to get my questions out there, and not worry about the old heads. They were established writers and I was a nobody at the time. I needed to hear that message. Kindness goes a long way.

Many of us have shared stories of players being kind during interviews. Here's one from a coach. This clip went viral last week. Here's the part that didn't. After the cameras were off, Mazzulla walked to the back of the room, shook my hand, and apologized for being so gruff. I'm not on the C's beat and I don't know Mazzulla personally at all. He didn't have to, but he took extra time to ask me a few questions about myself and get to know me a little bit better.

@CalvinAndHobo @goldenpants013 @Sports__Proj I try to develop a sense of whos reliable and gives good answers (Kerr not so much). Time constrained so only watch a small portion of pressers across nba and cbb. Also find the more i know about the tm going into presser, the more i get out of it

@goldenpants013 @Sports__Proj @LazyBrain64 @LazyBrain64 The people (aka just me) need to know. Did your background give you any alpha in Steve Kerr's press conferences? Or even with that, were his pressers specifically still neutral or -EV overall for you?

New Episode out today where me and @Sports__Proj interview @LazyBrain64. Justin is an NBA originator who only bets main markets. You will hear him make the case for having manual inputs for your model - and drop many more gems. Links below ⬇️

@Novig @HarryDCrane @BigBuckHunterrr @Flupnolide “Cant win by listening to podcasts”. Id also point out books dont help either and buying courses our best option

New Episode of Inside Prediction Markets @HarryDCrane joins @BigBuckHunterrr & @Flupnolide 0:00 Ohio's Bill to Kill Sports Betting 1:12 Perps Coming to Kalshi? 3:12 Chris's Substack on his Journey 4:51 @HarryDCrane joins the show 6:45 Harry's Scoop on Election Markets & 538 14:00 Having a Seat at the CFTC Table 19:00 Are Sharps Losing Faith in Prediction Markets? 26:00 The Full Kelly vs. Half Kelly Debate 35:00 What a $3M Drawdown Teaches You 43:00 Card Counting, Kelly, & Conditional Fills

@KirkEvans0 Using a table to measure a ruler

Hmmmmmm who’s having a better season. Very hard to tell. I’m not sure

@SportsCheetah losses hurt more than gains for all humans, but this is still a rec take. outcomes like that happen all the time, so what makes this one any harder to stomach? i had clara and under

Have Santa Clara in my Calcutta I can’t believe people do this shit every day lol

@sharp_fake @maple420069 reflexivity?

@maple420069 so its not just me 🥲

is anyone else damn tired of getting inf clv in the nba and losing?

@GestaltU @urpolitikcs Regarding super forecasters, i never understood how they adjusted for effort (time spent predicting). Seemed like major confounder. My top 3: mandelbrot’s misbehavior of mkts, antifragile, and @breakingthemark blog

@urpolitikcs Yup those are great.

Fooled by Randomness, Expert Political Judgment, and this book are my top 3 investment books. No other books come close.

@sportsmatters sports matters

Quiet court, 9:30. Story later. Safe travels. ✌️

@goldenpants013 @RufusPeabody How much more do top golfers and cbb coaches know about their sport than you? And how much of your model error comes from that knowledge gap?

First episode of the new year is going to be a banger. We have one of the best sports bettors/predictors of the modern era, @RufusPeabody , joining us. Leave your questions below - there's a very good chance Rufus will leak alpha in the 2-hour+ format⬇️

@kmedved @mattyglesias i disagree. RAMP is merely explanatory and shouldn't take credit for celtics coaching/org effects. swap celtics and kings org (leave players) and ramp would take an L for a while

Not sure RAPM totally works for the midwit curve (left side of the curve has presumably not heard of RAPM), but there is a certain degree of annoying efficacy to just presuming that NBA teams are the products of linearly adding up the production of the players. I say annoying since one of the things many people like about basketball, is that unlike baseball, it has a bunch of complex interactions effects, and you need different skillsets to win (e.g., too many shooters), matchups matter, and coaches can have a big impact. And that's all true, but it's also true that for the vast majority of outcomes, the "durrrr, just add up the RAPM scores" approach works almost annoyingly well.

The Celtics being good is a real win for RAPM-type models.

@databallr i had same thought regarding favorable conditions. also, distinguishing half-court vs transition seems tricky off misses.

Spent a good 5 min looking at this chart. It’s deep. At first look, it seems like very strong evidence suggesting teams should crash more. Lots of ways you could segment this data (shot type etc). Would be curious to know what the avg transition ppp is for both graphs. Even if transition ppp exceeds half court ppp by +0.4, if an orb is worth +1.2, you’re still breaking even at 1% orb for 3% transition given up. Also gotta think about whether there’s some favorable condition occurring to trigger the multiple crashers that is not necessarily there on the low-crasher subset of plays. There might also be a tiny bit of extra orb% from drawing loose ball fouls during the crash (which is basically an orb) — is that factored in?

is @spraguerTOUT gonna re-write the tout chart for 2026? #CircleBack

@ShipTheJustice @NateDuncanNBA We only get another mention of “put your 5 on him” how unsatisfying

@NateDuncanNBA i want to hear literal sobbing on the pod when you are talking about how wrong you were about steph castle. i wanna taste those tears as i drift off to sleep

Victor Wembanyama is flat out embarrassing Anthony Davis these last few plays.

No one can beat you at being you experimental-history.com/p/face-it-your…

@egfalken @MebFaber exactly! so many dots but how many independent, non-overlapping samples are there?

@MebFaber I know nothing about his work, but presenting all those dots is misleading. It implies many degrees of freedom, and thus a highly statistically significant estimate.

Can I post something without everyone getting mad? "To put the current valuation extreme in perspective, the chart below shows our estimate of 12-year S&P 500 total returns over-and-above Treasury yields. This is the most reliable estimate of the “equity risk premium” that we have examined or developed, and is better correlated with actual subsequent outcomes than the “Fed Model” (S&P 500 operating earnings yield – the Treasury yield), the “Excess CAPE Yield” of Shiller, Black, and Jirav, and annual estimates produced by Aswath Damodaran, all whose work I admire even when I might disagree." - @hussmanjp hussmanfunds.com/comment/mc2507…

@d_feustel @SethBurn @mr_peanutbettor @canzhi @capjack2000 sure, though some ML limits get big. my point is the ml/spread conversions is an inferior approach to modeling the entire distribution

@LazyBrain64 @SethBurn @mr_peanutbettor @canzhi @capjack2000 Generally the higher the limits, the more efficient the market is. MLs have lower limits than spreads, so I'm not optimistic that approach would work.

Conversion nerds: what's the fair no-vig moneyline in NBA, if the parent liens are Indiana +6 -115 and 227 -110 (using Bookmaker as source of truth)?

@SethBurn @d_feustel @mr_peanutbettor @canzhi @capjack2000 there's also a circularity issue with the question. what about using the ML and tot to predict the spread?

@d_feustel @mr_peanutbettor @canzhi @capjack2000 We appreciate the honesty.

@KirkEvans0 Strong disagree. 99% the first one. Other two will naturally follow.

Winning in betting is 20% being good at it, 50% connections/liquidity, and 30% having the balls to bet big.

@NekiasNBA In her defense, she gets the worst whistle in the league

@NekiasNBA you're allowed to say she's bad. probably the worst big in a W rotation? its a zero sum game. if you're willing to identify the relatively bad players, it puts more meaning to your praise.

trying to wrap my mind about the Li Yueru trade request. Clear she wants a bigger role, & it’s clear SEA needs some 3/4 depth. My first thought was calling up Golden State for any of their veterans (Talbot, Thornton, Zandalasini) but Yueru’s minimum salary complicates things.