December 2, 2022 | 4:42 am
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ProFitX is looking to change the game of basketball analytics

New episode of The Baseline with CEO/Founder of ProFitX Joshua Ebrahim. He joins the show to explain how he went from a sports agent to an agent of analytics. We discuss how his software is helping to reshape honest conversations on player valuations and analytic transparency in the NBA. Find out why ESPN’s Bobby Marks and the Dallas Mavericks backed by Mark Cuban are all in on ProFitX and how fans can use the software to their advantage too.

Full transcript below

Cal Lee 01:01
This is the baseline, discussing the hot button topics of the end. Be a welcome everybody, you are tuned to the baseline, Callie Warren Shaw. And this is a special episode of the baseline. We’ve been doing this for about a year now. It’s one of our favorite times, where we kind of do things a little bit off the cuff. It’s one of our series that we really love putting ourselves out there. It’s our episode of branded. First one we’re doing for 2022. And definitely not the last. But we are really excited to be able to have a special guest on to help us roll in the new year with this series that we like to we always like to do. And I love it. Because again, man, it takes us in a different space in regards to how the NBA continually just, you know, puts itself in these different spaces when it comes to technology when it comes to entertainment, culture, politics, you name it. We talk about branded, we’re talking about different products that help elevate the NBA in so many different spaces. And I cannot wait for us to be able to have that conversation with another individual who is basically on the precipice again, of moving the ball forward with the NBA, and its pulse his finger on the pulse of technology. So with that being said, you know, I got to be able to do with my right hand man, www dot shot sports.net Big Kahuna PNC my brother Mr. Warren Shaw repping out of Fort Lauderdale, Florida, the mastermind. He’s the guy that puts it together. I guess you can say he’s like the P Diddy when it comes to finding the talent. What’s good, my man, Mr. Shaw.

Warren Shaw 02:50
That’s pretty interesting. I’m happy to be here as always, man. And I think you know, when we do special episodes like this, it takes it takes our fans and listeners a little bit off the beaten path of the NBA kind of the day to day in regular coverage. And obviously, you know, that’s our bread and butter. We love that as well too. But we want our fans and our listeners to be educated fans and listeners as well and to have an opportunity to meet with some of the different guests and people were working within the basketball space. Even if the basketball adjacent. I think he’s just always a great, great look for us as well, too. So excited about this week’s show cannot cannot wait to dive in brother cannot wait at

Cal Lee 03:25
all. Absolutely. And not only is this like a really, really great episode, you know, for our listeners, but it also is a great episode for people who just want to geek out on numbers and metrics and how that is having an impact. Analytics how that is having an impact on the way that we’re looking and viewing the NBA not just the players, but also the teams and how teams are setting themselves up whether it be for short term or long term success. And so we are really, really fortunate to have our guests He is the founder and CEO for profit X. Josh Ebrahim is going to be joining us in a few moments to be able to sit down and talk about his platform and what that means for the NBA what that means for you, the viewer, the listener, the consumer, how his platform can benefit you the tools that they’re making available for you to be able to look at the NBA in a different lens so we cannot wait to get him on and I’m sure you’re going to enjoy the conversation that we have with him but before we do that, as always you know how to get up my man shot at Shaw sports NBA or get me a game face Lee, the show’s twitter handle at NBA baseline, you know where to find us. Just put the baseline NBA podcast and your search engine or whatever platform you use to listen to podcasts and an Amazon and allow us to be a go to resource discussing all things happening in the association. You can catch this episode and all of the shows that we put on for the baseline simply going to www dot the baseline nba.com. That is the home website. You also know that the baseline is also rolling with the 19 Media Group family 19 Media Group runs the content streets. So not only are you blessed to get this kind of good stuff that covers the NBA, but if you want more on culture, music, entertainment, politics, comedy, you name it, we give it to you. And listen, I call it the butter goods. They are so butter man it I mean, you might even have it without toasted. It’s That’s how good the butter is when it comes to 19 media groups. So be sure to go to www dot MIT Media Group comm to check out not just the baseline, but also the litany of shows and personalities that are putting on great content for the listener. So without further ado, we’re excited. I’m know you guys are excited. We’re ready to bring our man Josh, Shawn, this is a great great conversation piece to have. If you people are not familiar with profit X, you will sit tight, let us introduce you to the world of data analysis and the metrics used to help evaluate not just the players, but also the teams. This is a great conversation to be had, you don’t want to miss out with a man Josh Ebron here on branded. Time now to get branded Callie Warren, Shawn baseline APA podcast. And it’s just an awesome, awesome feeling to be able to be back in that space again, where we can have meaningful conversation with individuals and people who do meaningful work, especially when it comes to the culture of basketball. And what better way for us to really had a year for us and doing branded than having one of our premier guests here. He has been putting in major work in the basketball community. But now if you ever find him, he is he is basically the numbers man he is he is forging, really one of the more sought after premier software’s that is that’s just really erupting on the scene. And ultimately, I think it is going to be the ultimate think tank in our ability to appreciate how metrics and analytics is going to play such a major factor in the future when we talk about the NBA. And it’s just an honor, it’s a privilege for us to bring on the CEO for profit X. If people are not familiar with it, it is it developed software that analyzes data in order to determine performance value in the scope of information optimization, and he’s on with us the CEO, Josh Ebrahim, Josh, thank you for hopping on board with this this week to talk about not just the software, but also the movement that you are and you and your team and your families putting together to really help us appreciate how analytics should be looked at when it comes to our ability to visualize and see what’s going on with the NBA.

Josh Ebrahim 08:18
Thank you, cow. Thank you, Warren for having me really excited to be on the baseline today. And thank

Cal Lee 08:24
you well, so So Josh, being that you’re the founder, the first thing that we want to do is we want to understand where your roots come from. What got you to this point. So talk to us, give our listeners an idea of who you are, and how your background puts you in this space now where you are front lining, and helping to kind of be that the brainchild for what we see now in in profit. So

Josh Ebrahim 08:52
originally, originally, um, I grew up in a small town outside of Dallas, Texas called Greenville. Um, my dad my dad you know was a was a huge Pat Riley fan growing up and and put a ball in my hand and the rest is kind of history from from a basketball perspective. I went to school at Washington State University definitely came from a technical technical minded family but I did have that that similar mentality where it was it was a lot about, you know, the x’s and o’s and the end the numbers and what the data says it was. There was a lot more that I was kind of thinking about from a from an outside the box perspective where that kind of translated into my career as a as an MBA sports agent Josh

Cal Lee 09:46
man, I mean, that’s remarkable. So, I mean, it’s hard to imagine or hard to correlate for someone who grows up in a family in which, you know, in Engineering, sciences, mathematics and numbers is actually the stewardship for your ability to be involved in the sports agency business. So, John, so what were your next moves after that? What what took place for you now that you knew that you wanted to be a sports agent,

Josh Ebrahim 10:17
I started out, I got certified by the Players Association in 2016, I started my own little boutique agency, and had some had some success. Starting out, I signed a couple of top tier prospects that, that I was looking to help get drafted in that upcoming NBA draft and, and what I quickly realized is that the agent agent business is cutthroat. It’s difficult, you know, doing it on your own and, and what I realized is that, you know, you can, you can think, whatever trajectory you’re on, and it can be taken from you in a snap. And so both of my clients ended up firing me within a span of 10 days. One of them was poached by another agent, my other client ended up tearing his ACL and kind of my plans were kind of shot him,

Cal Lee 11:21
man. So basically, this seems like a perfect example of life imitating art. So I mean, you’re kind of living the Jerry Maguire story. You know, right before your eyes. So so you know what transpired from there.

Josh Ebrahim 11:39
I recalibrated. I ended up getting an opportunity to to a unique opportunity to work at Rosenhaus sports representation for NFL agent drew Rosenhaus. And they brought me on in in the summer of 2017. And we got right to work we signed diamond stone Anfernee, Simons, mantras, Harold, Chris makalah, to name a few during our first year, and as an agent, where, you know, I noticed a lot of problems within the agency business, which was number one, there weren’t a lot of resources out there to really justify, you know, your your clients valuation when you were going into negotiations with teams. And so during free agency, you kind of you know, there’s a window of 24 to 72 hours where, you know, you have to be quick, you have to make decisions, you need information on the fly. And that just didn’t exist during my time. And so what ended up happening was, I would create these, you know, 60, to 80 page reports, to basically, you know, show the player comps, and really try to use that to leverage in negotiations. But there was a couple of problems with that. Number one, you’re allowing, you’re allowing the teams to basically dictate the market value based on the team cap space, and other different factors that don’t really, that don’t really take into account the entire player’s career and what he’s done up until that point, and that’s, in my opinion, how the how my clients should have been evaluated from a contractual perspective. So so that was one problem. The other problem was there wasn’t there wasn’t a dynamic technology that took into account all of the different factors that you needed to show your clients that number one, you’re working really hard for them. And number two, that your recommendations are supported by hard data. And so there’s a lot of different factors. Through my experiences as as an agent, when I decided to leave Rosen house, I wanted to, you know, create this tool that could really benefit all parties in the sports ecosystem, the fans, the athletes and the teams. And so, you know, we’re trying to help teams be smart with how they build their rosters, we’re trying to help athletes at the end of the day, get paid and get paid what they’re worth, and we’re trying to create transparency and democratize the data for the fans because at the end of the day, they’re the biggest stakeholder in sports and, and COVID did a very good job of showing that I think there’s a lot of synergy with with the with the, the software that we’ve created and and and you know, through our initial You know, results and reports that we’ve generated. It’s it’s been a astounding success. So Josh,

Warren Shaw 15:09
share a little bit even about me because you said something that really hit me hit me hard when you said it. The agency businesses extremely difficult and cutthroat I, at one point thought I was going to be a sports agent coming up in college and so forth and so forth. You know, I’m a little older. And I thought, I think it was one of one of the one of the lockouts happened and agents were getting far left right before the new collective bargaining agreement. And I was like, Man, that doesn’t seem like a good route for me to go, maybe I should work on the team side, do something else so to speak, but even just learning how difficult it is to be an agent and how you have to cater to players, etc, etc, is really, really, really hard. So I commend you for for going that route, reimagining and rien visioning and now creating something to that, maybe can keep you adjacent to that, but really not to be as cutthroat as an agency business. It’s because God dang man, I think is not a game. But my but my question for you, really is, as we dig into the nuts and bolts of this whole entire situation, Prophet x’s, okay, why your brand over some of the other analytical technologies that are out there that are maybe a little bit more established in some teams are more familiar with?

Josh Ebrahim 16:21
Well, that’s a great question. And, and I think it really just goes back to, I think, a, you know, my original, when, when we started development on this, this platform, my original, my, you know, there was definitely a, you know, after I left Rosen house, I spent probably about three months kind of building out the concepts testing out, you know, the real time contract value algorithm to actually see if it could work, right, because, you know, you have this grand idea in your head and, and but at the end of the day, you have to test it, you have to verify it. And that’s the only way it’s really going to, you know, catch the attention of who you want it to, to who you want it who you want, four, to be utilized with. And so I think originally my my concept was, I’m going to build a Bloomberg terminal for athletes, that’s going to be five very financially centric, it’s going to project a lot of different types of contractual values and CBA parameters. And, and so when we finished development, three years later, we did a pilot program with about 2025 NBA teams. And, and honestly, I was I was scared, like I, you know, leading up until we launched the the pilot program, I was terrified, I was like, I hope this works. Like I hope it, it, uh, it generates the type of traction that we were looking for. And, and we actually got introduced to ESPN, NBA insider Bobby marks. And so I had a call with him initially. And he was like, this is, this is amazing, I’ve never seen anything like this. You know, during my time as a as a, as a front office executive, we never had anything like this. And so that really kind of gave me the confidence going into the pilot program that this was that what I built, you know, was was something that, you know, could could go to the next level. And so, so we did, we did a program with 2025 NBA teams, we got amazing feedback from a lot of teams, we had teams requesting new models, we had some areas where we made some enhancements to the models, you know, even Bobby really went back and looked at all of the contractual values and gave his two cents on where we could make enhancements. And, and so when we we went into free agency, I think was kind of my aha moment where I’m like, Okay, we got something here, because when we went through all, you know, we generated about 70 contractual reports from last year’s free agency. And, and, you know, we had numerous agencies reach out to us that had access to the platform teams had access to it as well. And you could just see this, you know, you could see the accuracy of our AI projections versus what the teams were actually the teams and athletes were signing for. And that really kind of gave us that. That validation that we were looking for, I think and that and we also had run contractual reports for the previous two seasons as well during the free agency periods. So collectively, we generated about 163 contractual reports. And and when you, when you analyze it, it’s, it’s pretty, it’s pretty cool to see the kind of impact that that you you had hoped to make with just helping the athletes get paid, helping the teams be smart about building their rosters, because you know, the max guys are going to get max money. But you know, that rest of the 85% of the league, it’s it’s a crapshoot, in my opinion. So, you know, it’s, it’s about creating a baseline, it’s about a starting point where both sides can go off of that’s not driven by the supply and demand a free agency it, it takes into account the the player’s career, the players potential, the development of his career, his injury history, his performance, his versatility. And, and also, you know, bringing Bobby marks on board to our board of directors was a was a big thing for us. And, you know, Bobby doesn’t put his name on, on a lot of stuff. But I think for us, that was just another point of validation, where, you know, we started to kind of gradually validate the software. And then in July, right before free agency, we signed the my hometown team, the Dallas Mavericks to a multi year sports performance partnership. And, and, and Mark Cuban, came out with a quote that, you know, was, was, you know, great for us. And, and, you know, and basically said, you know, our advanced technologies will give the Mavericks a significant competitive advantage, and this was just the beginning. And that kind of summed up where we were at at that time, because, you know, as I told them, This is just the beginning, you were just, you know, wait until wait until we’ve had time to do another, you know, make more enhancements, and add more models and, and optimize and calibrate the software to really be as accurate as possible. Because, you know, if it’s not accurate, no one’s going to listen to it, in my opinion. So I think that’s really the, the point where I kind of realized that, you know, not only does it have to be impactful, and and, and change and potentially change the trajectory of athletes careers, but it’s, you know, the data data is data, and it’s got to be on point. So,

Warren Shaw 22:33
Josh, so let me let me just tap in right, quick, right. So you and shout out to Bobby marks, we actually had him on our show some years ago, as well, too. It’s super, super insightful individual. Always, well, at least reply to some of my tweets. If I ask him a question like that just a great guy who really cares about this side? This side of the game, you know, intimately? But I do want to ask this kind of just one question, because you touched on it a little bit. And I don’t know if this is where you’re trying to go. So teams are obviously going to be interested in this. Absolutely. Right. But is is that the I won’t say the end all. But is that the the major crux of who you want to be kind of be the consumers of this product? Or is it the players themselves kind of maybe looking to see what their value may be? And you know, some players will not some players in general are smarter nowadays, and are looking at more ways to BB evil to equate their value to their teams. Is it agents, fans, journalists, who are the primary consumers for profit X?

Josh Ebrahim 23:29
Yeah, so the primary consumers right now for the for our for our NBA NBA platform, you know, we’re definitely targeting you know, NBA teams, sports agents, we’ve been in discussions with with multiple NBA teams, multiple large sports agencies, media partnerships, from from the NBA athletic side, that’s more of our enterprise SAS software, where we sell on a on a b2b kind of perspective. And then we also have a different product, the sports probability platform that’s built for the fans. And so our our main focus has kind of shifted after we really validated the athletic software, we kind of shifted our focus because there’s only 30 teams, right? And, you know, it’s it’s really tough kind of trying to track down these teams and get them at the right times to really get in front of them explain the benefits of the software, how it’s going to help them in in a lot of different capacities. But I would say our main focus is more driven towards the consumer side with our sports probability platform. And we’ve really built a product that kind of harnesses the power of the NBA athletics. It’s a it’s a database of 450 plus NBA athletes. With 2020 Time Series and performance visual models that are powered by AI, and we harness all of those individual athlete insights into a team performance platform, that gives you a lot of different models and widgets, from a individual athlete performance projections for the next 10 days on as well as the Team Performance AI projections from a pre match perspective for the next five days. So it’s, it’s really, it’s really just kind of, you know, the, the model that we have is really built more towards the the fans because they are, they are the biggest stakeholder. And, you know, when it comes to the type of uses that they can use it for, it can range from sports, betting to fantasy sports, to, you know, just a aspiring sports agent or front office executive. It’s a really, really thorough platform that has a lot of different tools and widgets that can be used for really whatever you want, but its ultimate goal is to really enhance the decision making process. And I think that’s where the real the real power is behind both of the products.

Cal Lee 26:20
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Cal Lee 28:24
Founder CEO for profit X. Josh, Ebrahim joining his joining us here on the baseline branded. So, Josh, I want to stay on this this this track that you and Shaw kind of put us on where the focus of the product was geared for it. I’m really interested. Because you know, you had mentioned a little bit earlier before that you you basically were able to strike a partnership with the Dallas Mavericks, right. So kind of staying a little bit on this trajectory. Obviously, what our podcast what we normally talk about is, you know, within the confines of the NBA, we speak about, you know, the teams and you know what, what it’s going to take for teams to put themselves in the best position possible, you know, towards the ultimate goal, which is winning an NBA championship. In the beginning, when the Dallas Mavericks had the combination of Luca Dockage and Kristaps Porzingis. I saw I saw potential in there. Maybe I did not get my subscription of profet X and see what kind of models you guys were designing. But speak to me in regards to I’m not saying specific to what you would provided them obviously, you know, we don’t get a need to get into semantics. But do you think that even your model that you would have provided say the Dallas Mavericks had an influence on the decision decision making process that the executives needed to make about the long term future of this team with Luca Dockage. And the combination of having a person like a Kristaps, Porzingis, and then saying, you know, what, we need to probably change course, very quickly, if we’re going to find something that can maximize what we’re seeing from an MVP caliber type player in Luka doncic, does your software help facilitate a lot of those numbers and projections that can that can help in that decision making process from an executive perspective?

Josh Ebrahim 30:34
Absolutely. 100%. And, and, you know, the, the the athletics was built from a lot of different experiences that I had, as an agent where I needed, I wanted to present information to my clients to really show them, the the athlete team dynamic. And so I really tried to harness all of my experiences in building each of these customized calibrated models to really project and and, yeah, I would definitely say that there was there was a lot of, there was definitely a lot of use case, you know, I like to respect the the Dallas Mavericks as a client. So, you know, I won’t go into how they utilized it and, and, and what they were looking at, but from my perspective, there’s no doubt about it in my mind that, that our insights are projections, that, you know, even even with AI projections, you know, you can’t, you know, it’s from my perspective, what I learned about artificial intelligence and technology is, it’s really tough to predict the future, right. And so, you know, projecting five years out, it’s, you know, the accuracy level is probably between 60 and 70%, if you’re projecting out that far. So what we tried to do is really, really try to find a balance of, of high end accuracy, but not too far into the future that can give them a glimpse, in real time with the dynamic trajectory of if it’s going up if it’s going down. And and I think the Mavericks have done a, you know, have have utilized it in a in a very unique and strong perspective, when they’re when they’ve gone and building their roster. So yeah, I would say, there’s a lot of different insights from the injury perspective to the player synergy, roster lineup cards, where you can you can generate lineup cards, in real time that, you know, will will give you some very interesting insights into kind of the, the, the future, you know, the current present state, and then also, you know, maybe a year in advance maybe two years in advance, and you can kind of make those make those determinations based off the data and, and, you know, move forward. So, yeah, I would say from from the Mavericks perspective, they’ve, they’ve definitely done a very good job of of utilizing it and the way that they intended to use it. And I think you’re you’re seeing you’re seeing the end result, you know, with how they’re playing right now and the transactions that they’ve made.

Warren Shaw 33:32
Oh, cow, I think we just got another quarter double. I think Josh said, I say he’s crediting Prophet x for the Dallas Mavericks recent surge, right, that we’re doing Josh, I feel I mess with you. I’m messing with you. So. Yeah, no, no, I mean, again, like you said, you want to respect them as a client. And we understand that for sure. And, and Mr. Cuban is one of the better governors or smarter governors out there. And he’s always on the cutting edge of technology. So not surprising to see him connecting with you on this great product, and then potentially having a success, even if you’re not saying and I’ll go ahead and say it for you. So pushing the thing along my guy, you know, one of the things that I really do like about the software, and thank you for allowing me to kind of poke around and kind of see what’s going on there as well, too. So it gives me It lets me be kind of a nerd and the kid I guess, at the same time, because it has to me in some ways, it has some like almost like 2k ish type terminology things going on in here when it comes to kind of like the player archetypes. And then you have these ratings and things that are in there as well, too. And I don’t mean that in any dismissive way at all, too. I just, I just think it really connects to me as somebody who’s like, Alright, maybe I’m not, I’m not Bobby marks right here. It means so. So I can understand kind of the terminology that’s going on here to us almost like you assign the players these roles, and it’s almost like having like a badge over the case of B. And what was kind of the decision making process into that. I mean, I understand like It’s like that religious basketball terminology really? And truly, so is it really just that simple? Or was it that you’re trying to make a little bit more user friendly? In general?

Josh Ebrahim 35:07
Yeah, I think I think it was a combination of both, I think, you know, and I like to tell this story, you know, I grew up watching the NBA in the, in the early 90s, where the game was so much different than what it is now, it was way more physical, it was way more defensive oriented. And, and now, you know, it’s, it’s a, it’s a completely, you know, modernized style of basketball, where there’s a heavy emphasis on shooting, you know, up tempo, more athleticism. And so I really tried to, to factor in kind of the, the modern style of, of how the game is being played at this point. And also trying to make it user friendly, because it’s, you know, a lot of the feedback that I get is, there’s a lot of people that are, you know, they’re overwhelmed when they first look at it, like, it’s so much data. And, and I tell them, Well, that’s, that’s just like a third of, of what we actually created, you know, so when we went into the r&d process, we created over 140, individual athlete performance tracking metrics. And so what we tried to do is, is harness all of those, all of those metrics to power the platform. But what we realized during the design phase is that, you know, if you put all this data in these models, it’s gonna look like spaghetti. And so meaning is just gonna, they’re the volatility of the lines. And, and so we really did a lot of work on trying to, like, smooth out the lines to show the career trajectory and more. So the the evolution of the athlete’s career, as opposed to the the analytics that are out there right now. And I think that’s one key distinction is that, you know, we take a different approach, where we want to show the evolution of the athlete that show the story of the athlete through financials through performance data. And, and I think it’s, it’s been a good blend of, of catering the platform to how the game is being played right now. And it also sets us up for the future, you know, if the game does end up changing, you know, there may be a four point, you know, shot coming coming soon, who knows, but we’re trying to be flexible and adaptable to how the game is being played in its current current state, and then also just really trying to, because it’s so much data really trying to make it user friendly, so that, you know, the users can extract the insights that they need, and not really spend time scratching their head going, what are what are what are we looking at here,

Cal Lee 38:05
Josh, just to quickly follow up these particular metrics, are these metrics in which you and your team have have created? Or are they the metrics that is pretty much the standard of that we’ve been using over you know, the last few years? And and it’s basically to fusion or combination there have to help you know, I’m saying for you to put together the models that you’re putting together I was just I was just kind of curious, you know, you get to some point where yes, you you you look at player efficiency and you know, war and you know, things of that nature, but I’m just wondering if whether or not like a lot of the the the particular metrics that you and your team have been putting together? Are they proprietary, like your own, you know, with a combination of formulas and things of that nature, that is different from what the standard is, or you’re using the standard and building upon that for your own metrics?

Josh Ebrahim 39:04
No, we we create everything and in the athlet the MBA athletics is all created internally by our by our r&d team, our development team and myself. Every model is custom built, calibrated. And and we use different sets of data that we’ve created to power each of those models and project the insights that that though those models were built for so yeah, I would say everything is is the technology, the data, the data creation of of all of these metrics is is all built in house and and proprietary is your

Cal Lee 39:49
hope that you’re looking for what you guys have put together to be the standard like to really use SERP what we’ve basically kind of relied on over the last Two years is our standardized, you know, look or, you know, our standardized conversation pieces that we use in order to kind of put the idea out that we understand the metrics of what’s being used currently right now.

Josh Ebrahim 40:16
Yeah, I think I think that that is definitely my hope. I think, you know, when I look at the data, when I look at the data that exists right now, it doesn’t really tell me anything other than, you know, the, the baseline, you know, the baseline performance, and, you know, some advanced metrics that have that have been created. And so, you know, I just feel like there, there needs to be a new, you know, usher in a new, you know, definitely want to be the industry standard for contractual value per, you know, performance value and how that’s how that’s been being utilized. now and in the future, because I just think that, you know, creating financial data is easy, but making it accurate is not easy. And it’s and it requires a lot of testing requires a lot of optimizations and calibrations. And, and so I think that’s really where we spend our time trying to, you know, essentially become the industry standard for financial, financial performance value, and contract and contracts, because you’re starting to see that trend of athletes, you know, negotiating their own contracts and hiring individual data scientists to build you reports that that justify what these these players are, are worth. But what we offer them is the dynamic real time capabilities that and the technology where you have all this data in the palm of your hand. And it’s a resource that you can utilize for really a lot of different situations from the front office to the agent side to the fan side. So yeah, I would say, our our hope is to become the industry standard, I think, you know, up until now, we’ve kind of put some solid footing down in the ground where a lot of people will come to us for for Financials. But we’re so much more than just a financial platform, we have eight different AI powered financial models, we have 12, different performance performance models. And so we’re really trying to bridge that gap and just kind of be that that not that go to for for really everything moving forward.

Warren Shaw 42:52
So Josh, couple more who let you slide up out of here, man. And again, thank you so much for joining us here today. In what you said, right there, there’s two things that kind of caught my attention again, too, because you said kind of in the palm of your hand. So is the mobile app coming as well. And I also wanted to know, at what stage like how many years of data do you need to collect or seasons, I guess to collect before a player can be inputted into profit x? Because I guess I’m trying to see a college player has nothing to kind of go off of so how would they eventually get into the system where they just kind of have to start playing games before you can start analyzing, especially when it comes to the overall fit and things of that nature as well, too with a new team?

Josh Ebrahim 43:31
Yeah, yeah, that’s a great question. So, so our platform takes into account, at least for some, for some players over over 10 years of career data. But the newer players, typically it requires to get to have their models fully powered, and and running properly, it takes usually about one a half a season to a full season, to really get their their profile fully up and operating. I like to tell a lot of the the teams that utilize the software and are focusing more on one or first or second year players that that, you know, the the accuracy from an AI perspective doesn’t fully hit, where we like to say the the sweet spot, which is around 90% until they hit a year three when they have around three years of full data. You know, that’s where, you know, we feel comfortable saying that, yeah, this is moving forward. This is where the models will be at at full, full accuracy and full, full power. But that’s not to say that we’ve we’ve had we’ve had a lot of players from a contractual standpoint that have had less than three years of data and we’ve we’ve projected their contracts, you know, pretty pretty identical, you know, very identical to what they signed for. So, you know, I think the the sweet spot is around year three, when all these players are going into their eligibility for their their rookie extension. So it’s kind of perfect timing for that. We also have a lot of AI widgets, that project on Team options, non guaranteed contracts, restricted free agency, and it really kind of gives you that, that full decision making mode that you can utilize, you know, when the players, you know, have decisions to make. So, yeah, I would say 90% accuracy after year three, but there are a lot of use cases where we’ve we’ve had some success with, with players under an under that that data threshold as well.

Cal Lee 45:52
Basically, in a nutshell, Josh, what you’re saying is, is just like wine, you put it in the barrel, and let it age quite nicely. And you will, you will, you will reap the benefits of, you know, I’m saying of everything that comes out of that casket. So the more data, obviously, the more strength in the numbers that get projected. I’m just curious, I showed I know, Shaw, you you had a follow up real quick. But I just I was just curious, when it comes to those numbers, you were talking about the numbers that that players are obviously, you know, what they’re doing, essentially, on the court, that includes all numbers, like even if, let’s say, for example, a player, you know, participates in the playoffs? Or are we just looking at strictly the numbers and the metrics that’s geared toward the data that you’re that you’re collecting?

Josh Ebrahim 46:55
Yeah, we we definitely we actually, last season before we did our like, official, official, like soft launch, we actually, we were actually only factoring in the regular season data. And then, and then when we the first week of the playoffs, I noticed that there was a bit, you know, obviously, there’s a big shift in the, in the atmosphere of how the games are played during the playoffs, everything’s a lot more, you know, tight, everything’s more defensive, you know, and everything becomes tougher for, you know, tougher than the regular season. So we made a quick adjustment to start factoring in the the playoff, the playoff performance for a lot of these players. We we noticed when we started generating the results during the playoffs that some players were enhancing their value during during the playoffs, which is which is common, you know, and, and we felt like That was a great addition to really show, you know, the difference between how the regular season and the playoffs and, you know, there’s not as much volatility during the playoffs. But you can see that gradual that gradual enhancement, you know, obviously, if they make it past the first and second rounds, you’ll really because it’s again, a small sample size, potentially four to, you know, four to seven games. So it’s really designed for, you know, like Terrence Mann, Trey young, Bobby, Portis were some of our big risers during during the playoffs last year. And it was it was really cool to kind of display that for for everyone to see, because I think it just, you know, really brings eyes on to kind of the the dynamic between the regular season and the playoffs.

Warren Shaw 48:54
So Josh, there are a couple of things in this software that again, I really do not a call that a lot of things are really like, what some of the things that like really stick out, I think you touched on too earlier was the the capability of the software to potentially predict fit for a team and kind of like the best lineup. So if you were in free agency, and like you said, a guy like I don’t know, Jaco Pirtle was was going to be available, hey, he might fit best best in this type of lineup for this type of team, so forth and so forth. I want to just kind of touch on that, like, what’s your kind of maybe non contract analysis aspect about profit except you’re like the most and I do have to ask a question. I mean, I don’t want to give it away because some people aren’t aren’t aren’t getting to see it again. But are some people in the profit X ranking higher then public perception? Let’s say that right now as I’m going through kind of like a top 20 There’s some people in here who’ve had who’ve been sponsored mostly, you know, kind of kicked to the curb by the NBA, Twitter, like, so good. If you could kind of explain how that ranking goes as well too. And kind of your favorite things about the software outside of the financial financial Yeah. Yeah,

Josh Ebrahim 50:00
so a couple of my favorite models, my I think my favorite model is the career outlook model that that gives you a lot of different insights, it gives you two year projections on the performance and financial financials of the player, it has a has an AI powered, free agency market tier of, you know, kind of where the player is sitting at, from a from a career perspective, all NBA MVP candidate all star, you know, impact starter, and so forth. And then there’s also a really cool tool on it that called the age impact that basically shows you the year by year performance growth, from a, from an age perspective, is he getting better each year, and there’s a lot of different use cases for that with, you know, the contract year for some players that, you know, play really well play really well at during their contract year. And so that’s really where I tried to capture those insights and try to show shed some more light on that. There’s also performing, you know, performance projections on that career outlook model. So that’s, that’s really been a cool model that I’ve really enjoyed looking at. I think the team fit model is another one where, you know, Spencer Dinwiddie, for example, who, you know, was was a really good player in Brooklyn and and, and was making an impact on that roster and ended up going to Washington and potentially could have been mismanaged Miss utilize the roster dynamic, could have prevented him from kind of reaching that full capability, he was also coming off of an ACL injury, so trying to work his way back in, but if you look at the team fit model, you know, it shows and it updates dynamically with the annal, while analyzing the the current roster and those changes that are being made, it really just kind of shows you where that optimal fit is. And, and if you look at it now, you know, it shows that the Mavericks currently are the, you know, most optimal team fit, you know, in a lot of different performance attributes of the team. So that’s, that’s also one of my, one of my favorite models, and I think the the player development, the potential model, where, you know, you’re able to see individuals skill sets of different players. And, and really show the performance growth of each of those, those different skill sets and project, you know, what they could do and where they can get better in the next two years. So and then obviously, with with the, with the, the overall rankings. You know, I think that that is also coming from that’s also coming from, you know, I think one of them that I was actually talking about with someone was Russell Westbrook, where he does have a high ranking right now, but, you know,

Warren Shaw 53:15
I’m glad you said it.

Josh Ebrahim 53:18
Yeah, absolutely. And I think that’s, that’s, you know, that’s a prime example. Because, you know, we are not, you know, we are factoring in the entire player’s career, not just, you know, the real time contract value updates in real time, but there’s there’s timeframes where it kind of generates those insights based off of so if you look at Russell Westbrook, he, you know, he had a he had a probably one of his best years last year towards the end of the season where he went on a pretty historic run and and now that you’re looking at his his ranking this year, you know, it’s it’s still high Absolutely. But I think it’s, it’s, it’s accounting for its accounting for a lot more of his his previous career career history, then then more so on on kind of what he’s doing. Now, if you look at his, if you look at his trajectory, you’re starting to see that that slight decline, you’re starting to see that slight decline that I think most people would anticipate, but when you really look at it, his numbers haven’t really dropped off. It’s more so just kind of the the fit of, of how, you know, the dynamic of the Lakers and kind of the the injuries that have played a part and at least that’s my opinion. Um, so Josh,

Cal Lee 54:50
I, just to kind of have you fixed a little bit on this. Would your model factor in the Current roster that like we’re saying here is we’re profiling, Russell Westbrook. And we’re saying team fit projection. What about team fit as is right now with the people that he’s surrounded by? Because usually the conversation is is the team that LeBron James is surrounded by, right? Like so we’re focusing specifically like you’re using Russell Westbrook as your client, and you have the metrics in place to really kind of center and hone in on whether or not Russell Westbrook would have been a solid fit for the Los Angeles Lakers. You know, I’m not saying that you would have been able to see this because obviously, you’d have to put it through your model in order to to be able to really gather that type of data information. But do you have it set up in that kind of way, where you can actually look at the players that is surrounding that individual? And seeing whether his skill set is going to elevate being next to those guys on that roster? Or would it have been better that he be somewhere else?

Josh Ebrahim 56:07
Yeah, I mean, we, we’ve, we’ve actually talked about so currently, the team fit model just takes into account a cumulative cumulative analysis of everyone that’s on that roster right now. But it does focus on it’s centered around each of the models on those profiles are centered around that particular player. We don’t have in depth we don’t have in depth insights into you know, kind of the dynamic between those types of players on that roster. But we do have a AI player synergy model that generates you know, the best the best suited players that match up with rut what Russell Westbrook’s playing style and so, we I think those two models kind of complement each other where it gives you the breakdown from from a team perspective that generates all the all the players on that roster and matches them up with the player that best suits Russell Westbrook. So yeah, I think I think to answer your question, it’s, it’s a, there’s a lot, the team fit model does a cumulative composite score of all of the individual players and matches it up with Russell Westbrook, and then you have the player synergy model that will kind of give you that breakdown of, of which players are best suited to play with the style of of what Westbrook offers to the Lakers.

Cal Lee 57:49
Man Josh, I don’t know what to tell you, man. Like, it’s, it’s, it’s unreal, how far we’ve we’ve come. And to see that you’ve been able, you and your team have been able to take the take the take data, take numbers. And we could, you know, are you until we’re blue in the face about what’s driving what’s motivating it, but you take numbers and you implement it in this culture that we have right now in basketball, and it’s an explosion of newfound information and to see that what you’ve built, what you and your team built with profit X is absolutely phenomenal. I myself and I’m sure you know, my man Shaw, you know, we are totally geeked over the idea that there is just this amass abundance of information yet to even be a filter. Thank you,

Josh Ebrahim 58:52
thank you, I really appreciate that. It’s been a it’s been a long road. But uh, you know, it’s, it’s exciting, it’s exciting to to, you know, make this accessible and it was built with love and and we’re gonna continue to innovate and and venture into pretty much every sport so it’s a it’s a really exciting time at pro FedEx and we’re gonna continue to make this the best product on the market

Cal Lee 59:36
Mr. Shaw, what an excellent, excellent way for us to re introduce and invigorate our listeners with our series branded just a phenomenal conversation to really be had about, you know where the NBA is going.

Warren Shaw 59:52
Well I think that’s a great great pitch there and that leads me into as you’re talking about the dollars and cents man in the baseline needs to become like an investor of some sort. All right, Josh, if you’re listening, give us a chance. We may want to get jumping in and getting some shares on this because I think this thing is gonna blow up. As you listen to him talk, there is obviously the clear fit of how agents and teams can utilize this to help predict and build their team, so to speak. But he also mentioned that there is something that from the fan perspective, you can utilize it if you’re a journalist, you can utilize it, if you’re a fantasy play or bedding, all of those aspects give Prophet X an opportunity to have a massive amount of tentacles, I think within the sports landscape. And that’s why again, yeah, I think we want we’d want to get in on this if possible, you know, on on all levels. One of the things too, though, and I’d really encourage if our if our listeners were paying attention, while he was being real humble Josh is a super, super nice guy and super humble. He actually gave us some insight about the maps trade, literally talking about the Spencer did when he fit there. So if the Dallas Mavericks now are again, they made a tray that all of us kind of question that they thought they traded Porzingis for maybe some pennies on the dollar, well, it would appear that the Prophet X software might have identified that a guy like Dinwiddie in Davos for tans would be a better fit alongside Luca. And that is definitely playing itself out now since that, so he couldn’t say it point blank, but I was paying attention. And I thought that was a really, really cool and interesting tidbit there that shows the software is already working. I think

Cal Lee 1:01:20
that was the reason why it was important for us to bring up that part of the the subject is not to highlight anybody being right, but to highlight the importance of being right. It’s like, you know, what we’re talking about here is, this is a Dallas Mavericks team show that if they still had the same roster that they had constructed, when the season started, I don’t think that they’re anywhere near what they look like now, right? And what they look like now is a much more competitive basketball team, that it seems like they’re buying in and they want to be a horse in the race in, you know, in the Western Conference Now, whether or not it translates to the idea that they can, you know, run, you know, you know, shot for shot against the Memphis Grizzlies or the Phoenix Suns or whatever, I don’t know. But wouldn’t you say that based off of what we’re seeing here, this model that Prophet X kind of helped establish, also kind of gives a better idea for the executives in an organization like the Dallas Mavericks to say, we need players similar to this as we’re watching the trajectory of a guy like Luca Dockage, in order for us to better assess whether or not the talent is fitting to maximize the potential of what he’s bringing to the table.

Warren Shaw 1:02:38
Yeah, I think that to me, while I love the contract stuff in that being able to be something that that it can do and help teams assess when it comes to free agency and things of that nature, I still think probably for me, it’s it is identifying potential fit alongside players, especially if you are trying to build around a certain guy, okay, what what compound, what players compliment that style, what players compliment that specific player, so to sort of so forth and so forth. And looking at the trajectory of it as well, too. So that’s why I say what again, what I said in the beginning here, this thing has the ability to have a very, very long standing reach, it has adaptability, and as well too, and let me credit him one more time as well. I am 100% thankful for his overall honesty, he didn’t come here and try to sell us a bill a bill of goods if you will, or beliefs or whatever it is, whatever the terminology is, when it came to like first and second year guys, he’s like, hey, you know what, three years in is when this thing can actually probably be most predictive and most accurate for you. But just getting in like a Chet Holmgren coming in now going into draft like he’s not going to be able to suffer is not gonna be able to predict anything because there’s just not data there. So he’s not gonna lie about what it can and cannot do. And that’s why I think again, it’s like it’s so important to deal with people like that and and see what the gentleman like himself who has a certain level of integrity and ironically again, nothing against agents but that agency world lacks integrity and time so maybe that’s why he wasn’t the best fit for it ultimately and he’s kind of on the path that he’ll he’ll he really needs to be on. Well, he

Cal Lee 1:04:07
definitely had his Jerry Maguire moment I didn’t want to bring that up but I was like man, I’m telling the Jerry Maguire story right about now which any gave

Warren Shaw 1:04:15
us an idea for a new segment. I love it man story time with the baseline.

Cal Lee 1:04:19
Exactly. We definitely know who we were first this is gonna wind up being because but yeah, again, I would encourage people if you have an interest in learning more about Pro Fit X, be sure to go to Twitter AT Pro Fit x ai so PR o fit x ai and you can also catch them on Instagram as well to the same tag name, Pro Fit x ai and you know once again man we’d like to thank our man, Josh, Ebrahim, CEO and founder of Prophet X for copping on board and really providing us with the background around an insight of this model on this platform that he has constructed, as my main show has alluded to, this ain’t going anywhere, anytime soon. I just think that this is just the cream is rising for and like everybody wants a little bit of this wants to taste to this because this is some serious good stuff. And I would encourage people definitely go to their Twitter or their Instagram, go to their website and check it out. I think those who are interested in how numbers can work for not just the NBA, but also you as a person who follows the NBA, you really really, really interested to see how this model is a benefit. So once again, we’d like to thank you and yours for hopping on board. And thanks for sticking with us and being down with this first first episode of branded for the baseline. Kelly Warren show. We appreciate you guys. You know we do, we’ll catch up with you.

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