"TOGO"

🏀 🏀 🏀 ENJOY 🏀 🏀🏀

Story overview

RHH: RHH: Welcome, fellow hoopers, to yet another episode of the RHH Basketball Podcast. I am very excited to welcome a member of our community, Carlos from Togo Scouting, who is here to talk about his project, Togo Software, a platform dedicated to basketball scouting and analytics. Carlos, welcome. It's very, very nice to have you here.

TOGO: Thank you very much. It's a pleasure to speak with you and see how your channel is growing. You're doing a great job.

RHH: Thank you. It's always nice to have people from our community sharing their stories, and we're very excited to present new projects that are of such interest. So, we'll dive right in. Would you mind telling us a bit about the idea behind Togo?

TOGO: The idea came about a bit by accident, to be honest. We are three friends who love basketball. We love watching games from unknown leagues to discover players who are under the radar. We started to see that some of the players we scouted would eventually arrive in the NBA or EuroLeague after several years. A few years ago, we decided that we couldn't lose this knowledge. We should save the knowledge we have about players in reports. At the beginning of this year, I started to study AI, and I saw what it could do. I thought, "Okay, if I spend 10 hours doing this manually, I can probably do it in 10 minutes with AI." So it saved me a lot of time. Of course, I still need to review everything, but I can save a lot of time. Then I thought, "If I can use this, why can't clubs use the same thing?" One of the things I realized is that maybe big teams have all the resources to do this, but smaller teams often don't. I've seen many cases where an assistant coach has to scout the opposition before a game, prepare the training session with the coach, and handle many other responsibilities. There is simply not enough time left to scout players. One thing we already know is that there is a cycle in the market where players move from one team to another, and when a player has had a very good season, there is a lot of interest in him. In the end, it's often the same pattern. We think our tool can help clubs save time and arrive in the market in a very good position.

RHH: Nice. And it's true that at smaller levels, at lower levels of basketball, where teams don't have the resources to have a massive staff, it is very useful for people to save time and energy and focus on where they want to spend it in the first place. So, would you like to tell us a bit about how your software works, the Game Intelligence Index, and some of the details?

TOGO: Yeah. What we do is, we already had a report created before working with AI, and this report has 44 skills covering the players, the game, and also mentality. We have created a Game Intelligence Index that analyzes how the player works, how the player thinks, and also how he performs when he's tired or in pressure situations. Apart from this, we analyze how his shot mechanics are, how he shoots two-pointers and three-pointers, offensive rebounds, defensive rebounds, and all these kinds of things. They are evaluated from one to five. Apart from this, we also take the context into account. The software can analyze all the players, and according to the level of the league, we have created tiers. Of course, if one club says, "I want a player who is very good, very fast, very good from three-point range, and a very good passer," I cannot propose Stephen Curry because he's going to say, "You're crazy." I don't have the software for that. For this reason, if a team is playing in a new league, I cannot offer them a player who is playing in the second division or something like that. So, we analyze everything within the context of the league and the tier in which the player is playing.

RHH: Okay. For example, you may find a player with skills that are higher in certain areas than another player who is in the EuroLeague, but this is because they are playing in different leagues and at different levels of basketball. This way, you're also able to identify players who are on the rise, who are playing under the radar for bigger clubs, and then you can present your findings to GMs and show them what your software can identify.

TOGO: Yeah. In fact, the purpose of this is especially to find under-the-radar players. It can analyze all kinds of players, but when we created it, we thought it would be particularly useful for these players. The thing is that we update the tiers. We are not going to analyze NBA players directly, but we analyze players who may eventually arrive in the NBA. So, we need to update the tiers once per year. We recreate all the skills, all the tiers, and all the reports according to whether the player has improved. If the player is playing in another minor league, in another tier, we keep him in that tier because we think that usually the salary will be the same. It's strange for a player to accept a reduction in salary.

TOGO: Yeah.

RHH: But when a player improves, we need to upgrade him. And when did you start your venture?

TOGO: We started with AI in June.

RHH: Okay, so it's very, very recent.

TOGO: Yeah, it's very recent. The thing is that we started before AI. When we were doing everything manually, we started about three years ago.

RHH: Okay. And can you also tell us, for the audience that isn't very technical with AI or particularly savvy with new technologies, how do you compare the tools that you use with the traditional human scouting approach? Is it a combination? Do you have to cross-check everything? How does it work for you?

TOGO: Yeah, it's necessary to combine the two. AI helps a lot and is a very good tool, but it cannot replace the rigor of a person. In a very short time, you will have the report on a player, but afterwards you need to review that everything is correct. That's a job that my team and I do. We review everything to make sure it's okay. If it is, there's nothing else to do. But if something isn't correct, we need to change some values or make adjustments. For example, when calculating the tier, we have a list and a ranking of the leagues, and we organize them into different tiers. But sometimes AI doesn't find a league because there is a small difference in the name. When it does a web search and cannot find the league, it may assign Tier 7. In this case, we need to correct it. Or maybe we see that it has analyzed five videos of a player and, in those videos, his shooting was very good, but that's not necessarily representative of the player. One of the things we do before the analysis is provide context for the AI. We ask it to look for the player's status, different classifications, information, and also news about the player. For example, one of the most difficult things for us is evaluating the mentality of players: whether he's a good team player, whether he's very professional, and things like that. This is the most difficult thing to evaluate from a video. You can't always find this information there. You can see how he reacts, whether he is provocative with other players, his trash-talking, and his on-court behavior. But you can't always determine everything from that. So, we also look for news. For example, if a player has been involved in illegal betting, we include that context in the profile.

RHH: Okay, these kinds of things. In fact, it's a proper profile for each player.

TOGO: Yeah. That's the most difficult part. It's the most difficult, and sometimes we fail, as everybody does, because it's very difficult. Last month, we needed to change one of the profiles in a report we had created. But this is difficult to know, to be honest. It's something that we look for in order to provide the context, because at the end of the day, it's very important. You need to analyze everything, but you also need the context. And even with this context, we don't always get everything right, so we always need to review it.

RHH: And so far, in your talks with GMs, with clubs, and with scouts, are they willing to check your approach? I mean, you are in a country with a very rich basketball culture, and the ACB is the best local championship. Are they willing to try new things? What is your perception so far?

TOGO: To be honest, it's a very hard market because clubs still don't feel that they have the problem that we understand they have. They are accustomed to watching videos, videos, and more videos. I think nobody recognizes that there simply isn't enough time to watch as many videos as they need to. They have more information than ever. Scouting is not an information problem currently because they have very good tools that provide a lot of videos and a lot of information. But they don't have enough time to process all this information. I think that's the problem. Clubs always do things the same way. They work in the same way other clubs work, or they work directly with agencies. They don't have the perception that they have this problem that I have identified. I think younger general managers are more receptive to this idea than GMs who have always worked in a different way. For them, it's more difficult to change their mentality.

RHH: Yeah. And I think European basketball in general still works in a more traditional way, especially compared to the NBA, where they have the staff and the resources. It's still quite different. But if you had to project five years down the road, looking at the landscape of scouting and how AI will be integrated into it, what do you see in terms of player evaluation and building rosters? Is there a tendency that you can already see, or something that you don't necessarily want to guess but can identify as a trend?

TOGO: For sure, because at the end of the day, America is the one leading the way.

RHH: Yeah.

TOGO: And they are already working with these kinds of things. Not with our platform, because to be honest, we arrived late to that market. They already have their own software, very technical and complex software. NBA franchises already have departments with developers who are creating these kinds of systems. The NBA is amazing. You can see that they have tablets. The assistant coaches have tablets, and during timeouts, AI can already provide a report of the game in real time, saying, "This play works better than this one," or showing that the defense is giving up a lot of points when a particular play is used. These kinds of things are already automated, and it's amazing to see in the US.

RHH: So, you can see that eventually coming to Europe as well.

TOGO: Yeah, I'm sure it will arrive.

RHH: I'm not sure when.

TOGO: Okay. But I'm sure it will arrive because you can see that every time there are more skills, more tools, and more information, and humans don't have the availability to process as much information as quickly. It's not about replacing people; it's about helping them make better and faster decisions.

RHH: Okay. Is there anything else that you want to point out about Togo that we haven't touched upon? Something that we might have missed?

TOGO: No, I think this is a good summary. If somebody is interested, they can request a free demo, and we would be glad to provide one. They can see how our software works and how they can use it. The good thing is that we can do the scouting really fast, but we also have an AI agent where you can type something like, "I want a player with these skills, who did this, who is free," or whatever criteria you want. You can provide all the information, and the agent will provide the five players who best match what you have requested.

RHH: Okay. And we will definitely put all the links on the video and in the piece that we will have on our website for this. I want to thank you very much for taking the time to speak to us today. It was very interesting and intriguing. This is our first web story for our podcast. We wish you the best of luck, and we encourage everybody who is interested to go and have a look at Togo. Hopefully, we will hear from you again. Thank you very much for being here today.

TOGO: Okay, you're very welcome, and I hope that your channel will grow because you're doing a very interesting job.

RHH: Thank you. And thank you, everybody. Make sure to check our website, check the piece that will be uploaded soon, and stay tuned for more. See you soon.

RHH: Welcome, fellow hoopers, to yet another episode of the RHH Basketball Podcast. I am very excited to welcome a member of our community, Carlos from Togo Scouting, who is here to talk about his project, Togo Software, a platform dedicated to basketball scouting and analytics. Carlos, welcome. It's very, very nice to have you here.

TOGO: Thank you very much. It's a pleasure to speak with you and see how your channel is growing. You're doing a great job.

     Today's community story comes from Spain and it is basically a glance into the future of basketball scouting and how AI and analytics are transforming the game! We interviewed the founder of TOGO, Carlos who explained to us their innovative idea and how it became a tangible project just some months ago (June 2026). 

With Carlos we discuss the inception of his project, what prompted the 3 friends who love the game to proceed with this, challenges and of course the evolution of basketball.

We urge our community to have a look at this new innovative project, check out the DEMO of the software and give us feedback!

Below is the link to the RHH Podcast interview that you will of course find on our channel in you-tube!

2025 All rights reserved