00:00 - Rob Pizzola (Host)
Every week during Monday Night Football, I host a watch-along on Forward Progress YouTube. It's usually just reacting to the game, talking betting angles, that kind of thing, but during a recent stream I had Jay Croucher on. He used to be the head of trading at PointsBet, now works for NBC Sports, and we ended up going way deeper than usual. Jay said something that really stuck with me. I think it perfectly sums up how people should think about sports betting content and sports betting analysis.
00:26 - Rob Pizzola (Host)
Take a listen to this be held accountable for their analysis, but then hold them accountable for their analysis, not the results, which can fluctuate in the given sample. So, yeah, if someone goes on and has a huge platform and it's given like kind of presents themselves as giving out gambling advice or financial advice, uh, and their analysis is, yeah, I think the jets win because they're due, like that is stupid and you should criticize someone for that. But if someone gives a reasoned, intelligent analysis about why they think the Jets will win and then the Jets lose, it's like all right. Well, it's not. Yeah, they can't tell Source Gardener to make the play in the end zone. That's just how it is.
01:21 - Rob Pizzola (Host)
That clip hit me hard because it's a very interesting point of view. There's this obsession and betting content with results, win, loss records, unit counts, hot streaks but hardly anyone is talking about analysis and process. So in this video I want to unpack two questions. Number one should we judge people based on their analysis instead of the results? And number two what actually separates good analysis from bad analysis? If you like videos that go deeper into how betting really works, tap that like button. Subscribe to Circles Off here, presented by Kalshi, and I'd love to hear what you think about what Jay said. Drop a comment below after you've watched the whole video. Do you agree that we should judge people on their analysis, not their betting records? Let's get into it. So, for anyone who doesn't know Jay, he used to be the head of trading at PointsBet, meaning he literally helped shape the betting markets that a lot of us play into nowadays, and now he's with NBC Sports doing great work on the media side. So when he talks about process over results, that's coming from someone who's seen both ends of this industry and I really agree with him.
02:41
I've been betting professionally for a long time now. I've also been creating content for years and I see the same pattern over and over and over again. People judge everything based on wins and losses. If you're a casual, better I get it. A record is easy to understand. It's a shortcut for credibility. It's like saying this guy's up 20 units, he must be sharp. But that's not how betting actually works. Even the best bettors in the world are going to have losing months, sometimes losing seasons, but if their process is sound, they're still going to beat the market long-term. The average better doesn't see that. They see the number next to your name. They make a judgment call and, just like I talked about in my video on buying picks links down in the description below for that one if you haven't watched it yet records are one of the easiest things in the world to manipulate. People can cherry pick timeframes, they can hide losing stretches. They can even grade bets at numbers that never even existed. So when someone flashes a clean winning record, it might not actually mean anything. Which brings us to the real question If results can be faked, what should we actually be judging? Instead, let's talk about why analysis might tell you a lot more about someone's skill than their win-loss record.
04:01
One of the biggest issues with judging people based on win-loss record is just variance. Even elite with judging people based on win-loss record is just variance. Even elite bettors, like the best of the best in the world, can go 7 and 20 over a small stretch. That doesn't mean they suddenly forgot how to bet. It just means that short-term results can be random. The problem is most people don't have the sample size to see through that variance. They're looking at a few weeks, maybe a month, of results and deciding whether someone's sharp or not. So if the results are noisy and short-term records don't mean much, what does actually matter?
04:35
Well, the process behind the bets is what matters, and that's why win-loss records are such an easy marketing tool. You can slice and dice them any way you want. Had a bad football season last year, but you're off to a good start this year. Easy Promote this year's record. Had a few good seasons in the past, but you're losing right now. Well, suddenly it's your lifetime record that matters.
04:58
Content creators and totes they do this all the time because they know how people think. They know that good records sell. It gets even worse when people start grading bets at numbers the audience could never actually get. Maybe they're giving out a line that was long gone. Maybe they're using contest lines where they already know how the market has moved before they're making their picks. Hell, some people don't even give out a number that they are betting. At that point, the record becomes meaningless. It's not a reflection of skill in betting. It's a reflection of timing and optics. So when you strip away all the noise, a record on its own tells you nothing about how good someone actually is.
05:40
Without context, the number bet, the line move, the reasoning, is just math without meaning, which is exactly why I think that analysis, the thought process behind a bet, is a much better way to measure credibility. Results in sports betting are random. You can do everything right and still lose in the short term, but process process is repeatable. That's why the best bettors in the world focus on having good process. They know that if the reasoning is sound, the math checks out and the market moves in their favor, the profits are eventually going to follow.
06:15
Good analysis is actually measurable, it's logical, it's transparent and it shows that you understand how markets actually work. And personally, that's what I care about. I don't really care who someone picks. I care how they got there, what data they looked at, how they weighed context what assumptions they made. If you assembled a room full of professional bettors and you gave them the records of a hundred different content creators and then had them actually watch each creator break down a game, I'd bet that almost every pro would agree. The video tells you more than the record ever could, because a good process leaves clues. You can hear when someone knows what they're talking about. You can spot when someone is just guessing. That's what separates people who can sustain success in betting from people who just got lucky for a few months.
07:06
So now that we've talked about why analysis matters more than results, let's take a look at what actually constitutes bad analysis. And, to be clear, not all bad analysis sounds bad. Sometimes it sounds really sharp, referencing stats, models, narratives that sound professional. But if it's built on information that the market already knows or ignores timing and context, it's still bad analysis. And one of the most common examples this has been around forever is the whole pros versus Joes, sharp versus square public narratives. You'll see it all over betting content.
07:38
Here's the thing Betting against the public used to work 20 years ago. Markets weren't as efficient. Sportsbooks would actually shade lines based on public action. That's not the world we live in anymore. Let's use an example. Let's say the Dallas Cowboys are playing the Carolina Panthers. Dallas is minus three, carolina's plus three. Both of those are minus 110. If the public is all over Dallas, the sportsbook's real position is Carolina plus three. At plus one, 10 for the book to break Even. They only need to win 47.6% of the time for you to break even at Carolina plus three, minus one, 10. You need to hit 52.4%. You can't just follow the pros. If a sharp better hits Dallas minus three, that line moves to minus three, minus 120, or minus three and a half. Once that happens, you're no longer betting their edge, you're betting a worse number. They stop betting once the number moves. So why are you tailing that? So when you hear analysis based purely on public versus pros, it's outdated. You're chasing ghosts, not value.
08:44
Another form of bad analysis you'll often hear is when someone says I talked to a few other pros and they're on this side. Well, that sounds convincing, but in reality, the whole idea of inside info from sharps is wildly overstated. Now, I say this as someone who's a sharp better myself and works in this industry. It's not that sharp betters never talk to one another. It's just incredibly rare for anyone to share full opinions before they've bet. When real money is on the line, information is currency. If you tell another sharp what teams you like or what numbers you're going to hit, that doesn't just affect one game. It tips them off about how you rate certain teams. Long term, this information can be used against you in future weeks. Sure, sometimes sharps will share things after the fact, once the number's gone, once there's no edge left. But the idea that people are out there comparing their full betting cards or swapping sharp sides in real time is just fantasy. So when you hear someone say I talked to the sharps and they're on this, they're not giving you inside info, they're selling you a narrative.
09:49
Another kind of bad analysis you'll see all the time is when people chase trends. You'll hear stuff like I'll fade any NFL team when the line moves through zero, as if there's some sort of secret hidden edge there. Zero isn't even a key number in football. There's no logical hypothesis behind that. It's just a random pattern that someone found in a tiny sample and they decided to treat it like gospel. The same goes for things like teams coming off a Monday win don't cover if they're playing on the road the following week Sounds fun for trivia night, but it's not predictive. If you can't explain why a trend should hold up, it's not analysis. It's just superstition dressed up in spreadsheets. And the problem is, once you slice data enough ways, you can find a trend for anything Teams wearing blue jerseys after daylight savings time there's probably a winning record somewhere there. Real analysis starts with logic and builds to data, not the other way around.
10:47
One of the biggest giveaways of bad analysis is when people ignore context. You'll see this all the time. Someone's breaking down a matchup using past stats without realizing the lineup is completely different this week. Let's say, a team is missing three starting offensive linemen, but the analysis leans on how they're the best rushing team in the league. Well, that's meaningless now. Those rushing numbers were built with healthy starters. Once those players are gone, that historical data doesn't apply anymore. Injuries, depth chart changes, even who's actually practicing during the week all of that matters. Data only has value when the underlying conditions still exist. Football isn't played by spreadsheets, it's played by people, and if your analysis doesn't account for who's actually on the field, you're not analyzing, you are pretending.
11:42
Another form of bad analysis that's everywhere right now is what I call empty model talk. Everyone seems to have a model these days. It's almost become a status symbol. We make this game a pick-em. So we're getting three points of value on Carolina. Well, that sounds great on paper, but here's the reality. Having a model doesn't mean anything if it can't beat the market.
12:04
If your numbers are truly that far off and you're actually a winning better, the market should move. Sharp books will take $20,000, $30,000 a side. Midweek. They'll take $100,000 plus on game day. If your model really made Carolina pick them and you consistently win in the NFL, well, you'd be hitting that plus three until it disappeared. So if the line's not moving, your model probably isn't as sharp as you'd like to think it is. And listen, I'm not discouraging people from building models. It's actually a great way to learn how markets work. But if you make a game of pick them when it's plus three in the market, you should be able to explain why you are so far off. What assumptions did you make? What are you seeing? That the market isn't Just throwing out a number is an analysis, it's noise.
12:53
So we've covered what bad analysis looks like. Now let's flip it. What does good analysis actually sound like? At its core, good analysis is about identifying what might be mispriced, something that's either over-accounted for or under-accounted for in the market, and being able to explain why. Let's take an example from earlier this NFL season. The Cleveland Browns had a brutal travel stretch two straight road games, then another trip overseas to Europe before heading to Pittsburgh for a third consecutive road game. That's a really tough schedule spot. Now, the market's not blind. Betters and oddsmakers know about travel and rest advantages, but what separates sharp analysis is someone who can maybe articulate how much it matters and why the market might still be off. How much it matters and why the market might still be off. Maybe the argument is that the fatigue effect is worse than usual because of time zone changes and short rest, or maybe someone believes it's already priced in and the market actually overreacted. Either of those sides can be valid as long as you give clear reasoning. That's what good analysis is not guessing, not following a narrative, but identifying where the market might have mispriced a situation and backing it up with some logic.
14:11
Good analysis starts with logic and process. It's not about throwing random stats around. It's about using data and actually fitting the situation that you're analyzing. To use another example quarterbacks playing their first game back from injury. Through years of data, we can measure how they perform relative to market expectations and there's a pretty clear pattern right now. On average, they underperform in that first game back. That's a testable hypothesis. You can break it down even further what type of injury did they have? Was it a foot or leg injury? That's different from a non-throwing shoulder injury. Did the quarterback practice all week? Was he limited? Did he miss Friday entirely? Each of those things matters. You can look at how similar situations have played out historically, measure performance against team totals or market closing lines, and you can use that information to account for that situation and adjust your ratings. That's what makes analysis credible. It's logical, transparent, supported by data. It's not about saying I have a feeling this team is gonna play better. It's about identifying a measurable edge and explaining why it exists.
15:21
The last key trait of good analysis to me is market awareness. Strong analysts understand how prices move and why it exists. The last key trait of good analysis to me is market awareness. Strong analysts understand how prices move and why they move. They know when a shift is caused by real information, like bad weather or an injury. Good analysis connects market movement to reasoning. It recognizes how limits, liquidity, timing, all those things factor in, because understanding the market isn't about chasing the move. It's about knowing what the move actually means.
15:50
One of the most underrated traits of good analysis is being willing to admit uncertainty. There's a weird pressure in this space for people to sound confident all the time, like if you don't talk in absolutes, people are not going to take you seriously. But the the truth is uncertainty is part of every bet Injuries, variance, weather, even officiating. There are dozens of factors that no one can perfectly control or predict. Good analysts don't hide that. They quantify it. They say things like I like this side, but it's worth less. If the wind picks up in the game or if this player is out, the market should move by X amount of points.
16:28
Being transparent about what's unknown doesn't make you less credible. It makes you more trustworthy, because anyone pretending to have all the answers in betting is trying to sell themselves or they're lying to themselves and you. So, to wrap this up, results are always going to fluctuate, but process endures. You can fake a record, you can hide losing streaks, you can cherry pick samples, you can grade at numbers nobody could get, but you cannot fake understanding. You can't fake the ability to think through a market and explain why something is mispriced. That's why judging people by their analysis is so much more meaningful to me than judging them by their record. Records are snapshots. They tell you what happened. Analysis tells you why it happened and whether it's likely to happen again.
17:16
Jay Croucher, in my opinion, said it perfectly in that clip Hold people accountable for their analysis, not their results. Someone's reasoning is bad. They're saying, oh, the jets are due. Or they're basing everything on trends and public percentages. Criticize that all day long. That kind of thinking deserves to be called out. The goal isn't to sound smart after the fact. It's to think clearly before each bet is made, because that's the only thing that actually scales in this business Process logic, consistency. If you actually care about getting better at betting, judge people by how they think, not by what their record says. I want to hear from you. Drop a comment down below with an example of what you think is either good or bad analysis that you've seen lately what stood out, what felt off. And if you found this video helpful, hit like, subscribe to Circles Off and maybe share it with a friend who still quotes betting public percentages like it's 2008. And remember, if your edge is betting against the public, you just might be the public.
