AI + turfgrass science in the most high-tech World Cup yet

[AUDIO LOGO] JANE LINDHOLM: Hey there. You’re listening to Science Friday. I’m Jane Lindholm. I’m the host of a kids’ science show called But Why at Vermont Public. And this week, I’m filling in on Science Friday.

The 2026 World Cup is finally here. It’s already the largest tournament in World Cup history, with 48 teams battling it out. But FIFA and the tech giant Lenovo are also trying to make it the most high-tech tournament with the launch of Football AI Pro, which is designed to analyze over 2,000 different metrics to coaches, players, and analysts.

But can AI capture everything that happens on the field? And what does AI integration actually mean for the game? Here to discuss with us is Ryan O’Hanlon, staff writer at ESPN and author of Net Gains: Inside the Beautiful Game’s Analytics Revolution. Ryan, it’s nice to talk with you.

RYAN O’HANLON: Hey, Jane. Thanks for having me.

JANE LINDHOLM: Can you just tick off all– or some of at least, the new AI features that FIFA is rolling out for this World Cup?

RYAN O’HANLON: Yes, so they say most of the AI features are around refereeing and improving the refereeing process, so some 3D modeling, using what they’re saying player avatars, to be more accurate in terms of calling offside, also being able to determine whether the ball has gone out of bounds for a throw-in or a corner kick. There’s also a sensor in the ball. And then they also have the AI tool that you’ve talked about, which is delivering various metrics, which they’ve said will democratize the use of AI among all the teams at the World Cup.

JANE LINDHOLM: FIFA president Gianni Infantino said a couple of months ago, though, that quote, “We are ensuring that innovation benefits every player, every team, and every fan everywhere in the world.” So it sounds like they’re trying to make it sort infiltrate the whole game.

RYAN O’HANLON: Yeah, I think Gianni Infantino is the first. He’ll be the first person to jump on any trend that is happening in the world. And AI is the big thing that people seem to be excited about. So Gianni Infantino wants us all to think that AI is going to transform the World Cup for us, for the better. But if I had to venture, I think the result of all this AI talk for fans will less be an improved experience, and more be an annoyance with hearing the phrase “AI” over and over again.

JANE LINDHOLM: Oh no. So it’s not so much for the fans, in your interpretation at least.

RYAN O’HANLON: Yeah, I don’t think so. I think that there will probably be all kinds of new metrics that are thrown at us throughout the tournament. But I think those metrics will, as they tend to be very context-free, black box-produced– and also, as tends to be the case with a lot of soccer statistics you see on television, just not connected to winning and what actually predicts what wins games in any kind of real way, will be my guess. I’m happy to be proven wrong, though.

JANE LINDHOLM: Yeah mentioned that piece, democratizing the game, is a buzzword. Is there a benefit to having this spread out across all the teams in the World Cup? Whether or it’s for the fans, is there a benefit to the teams?

RYAN O’HANLON: Yeah, I think that’s a really good point. And I do think making analytical tools or data available to more teams is a good thing in general. But at the World Cup, you’re limited by who was born in your country or nationalized to play for your team or who your country colonized or has a military base in at some point. So you’re limited. There’s no scouting benefits to data in international soccer.

Well, the main benefit of data analysis in all sports is figuring out who’s actually good at the sport. So that doesn’t apply as much here. And so with the data for the games in particular, I think there’s a very real question about how actionable or useful any of that data will be because of, one, what is the data exactly?

Two, how able is anyone at any of these federations to quickly model this data in any real way, connected to being predictive? And then three, the World Cup, as much as we hate to admit it, it’s a very small sample size in an incredibly random sport. So extracting signal from noise, I think, with 2,000 data points would be very difficult as well.

JANE LINDHOLM: Can you talk a little bit more about that? Because the Football AI Pro has sort of been framed as this, like, “coach on the sidelines” that’s going to be really helpful in real time. Is that going to be as helpful as maybe what it’s being framed as?

RYAN O’HANLON: Yeah, I think coaches have a very interesting place in soccer where they’re viewed as these all-powerful figures. But also, soccer coaches have the least amount of power of any coach in any sport, because the half starts, and then it ends. You’re allowed to make subs, but–

JANE LINDHOLM: They can yell from the sidelines, Ryan. They can show their displeasure with their faces.

RYAN O’HANLON: Yes, and I feel bad for whatever wing player is playing on the same side of the field as his coach’s bench. It’s always better to be on the other side where you just can act like you can’t hear what he’s saying. But I think I have a hard time seeing how any kind of data in, let’s say, a 30-minute span.

A half’s 45 minutes. Something happens over 30 minutes, I have a really hard time envisioning what AI is going to tell a coach that would allow the coach to essentially change his team’s formation– I guess that would be the main way that you could change up, that a coach wouldn’t already see. Or how would that information is not just random chance by the bounce of the ball versus a structural issue with the team? So if one attacker is dribbling past a defender, like, five different times, and the AI is like “weakness detected,” I think a coach has already seen that. So yeah, I have a hard time seeing how there will be real, actionable data, given just the structure of soccer in real time.

JANE LINDHOLM: Are there any areas where these new technologies and AI is actually changing or being beneficial to the game?

RYAN O’HANLON: Yeah, so I know I’ve probably sounded like a Luddite, nihilistic, “none of this matters” person. But I actually do believe that, data can be used to make better decisions in soccer. I do. The one thing that you’ve seen change– so soccer is just a very dynamic sport. There’s barely any rules, 22 players.

If teams wanted to, they could agree to stare at the ball for 45 minutes, and no one could do anything to stop it. The fans would be booing and the ref would be like, I can’t do anything, sorry, they’re just standing around. But there is an aspect of the sport– corner kicks, throw-ins, set pieces, that does start to resemble American sports a lot more, mainly because the game comes to a halt.

The players can discuss what they’re going to do. And the coach, if he wants to, he can draw up a pre-designed play. You have a corner kick.

You can tell the players where they’re supposed to run, who’s going to set a pick. And data analysis over time has found that this is a very underexploited area. Some teams have been very good at it without getting worse at other areas of the game.

If you look at Liverpool, who’s one of the smarter teams in the Premier League, they collaborated with Google DeepMind. And they created this app where you can show where your players are on the field for a corner kick versus the defense. And then the AI-based app will be like, no, actually the positioning of the players, this would lead to a goal slightly more often. So I think that is the one area, because it’s such an isolated part of the game that is prone for AI to potentially add even more value.

But what’s happened, both for good and ill, I would say– so set piece scoring, corner kicks, throw-ins, it’s at a higher rate than it’s ever been since we’ve been recording this data. But then open play goal scoring is at a lower rate than it’s ever been, because if you’re lining up a corner kick, and being very specific about the details and where you want the ball to go, it takes a lot of time to figure that out. And the clock doesn’t stop. So in the Premier League this season, the ball is in play less than it’s ever been since they’ve been recording the data. So the part of soccer that people tend to fall in love with– which is not set plays, it’s the creative on the fly thinking, there’s less of that than ever before.

JANE LINDHOLM: At what point does the AI, and all of the analytics and all of the ability to in all of these sports where we’re seeing analytics play such a big role these days, wind up tipping the balance away from a fan experience?

RYAN O’HANLON: Yeah, I think if fans are going to be able to see an offside decision within the margin of 1 centimeter being correct, they’re not going to care if all the other aspects of soccer are gone. I’m just kidding. But I think that’s a great question. It’s something that’s happened in a lot of the other major sports. Baseball is run by all people that went to Ivy League schools. The data analysis is way beyond anything you would see in public.

And they realized that it made the sport worse because it was all home runs and strikeouts. The ball was never in play. So there is a definite– like, it’s the leagues and governing bodies responsibility to make sure the sport is fun. And it’s the teams’ responsibilities to try to find out how to win. And you have to try to figure out a way to make those things balance.

Before the age of data analysis, this wasn’t as much of an issue, I don’t think. Now it is. Soccer is way behind all the other sports in terms of how objective analysis is being employed.

But the set pieces did catch on. And it was enough of a story in the Premier League– and the team that won the league, Arsenal, set the record for corner kick goals in a season. They played a very conservative style. It became enough of a story that I think it’s like a very real thing that people are aware of.

But given that it happened in the Premier League, if it happens at the World Cup, I think it could become an even bigger story. And then it could be a thing that the soccer world will be unable to ignore. And we’ll have to make some kind of changes to prevent this from continuing.

JANE LINDHOLM: Well, speaking of the beauty of the sport, you just wrote a very detailed article where you predicted the winner of the World Cup and the winner of almost every single game, and by how much. And you did it all by hand. Why?

RYAN O’HANLON: You should ask my editors.

[LAUGHTER]

No, I’m kidding, I’ve done it the past couple World Cups. Part of me kind of wanted to do it as a bit because now anyone can simulate the World Cup and be like, I simulated the World Cup using AI 100,000 times. Here’s what it said.

I think in soccer, or the World Cup, we just underestimate how random it is, and how often, one of the teams that we thought was a favorite loses early on. But if you go game by game and you predict everything, you end up with all of the favorites advancing. So I had to get it in my head, I don’t want this to try to have the maximum expected value for someone betting on the World Cup. But I wanted it to try to match up to what we normally see– the number of favorites that tend to lose in the World Cup.

But when I did that, I kind of saw– it’s interesting. Spain and Argentina, if they win their groups, it seems like they’re not going to play any of the best teams until the semifinals. So whether or not I think Spain and Argentina are the two most talented or the two most, quote unquote, “in-form” teams, it seems like they might actually have relatively easy paths to get far in the World Cup. So it did reveal that bit of information to me.

JANE LINDHOLM: And just so that we know who to yell at in the end, who did you pick as the winner? You got to tell everyone.

RYAN O’HANLON: Yeah, I picked Spain over Argentina.

JANE LINDHOLM: OK, well, where should we send the hate mail?

[CHUCKLES]

RYAN O’HANLON: Editors@espn.com.

[CHUCKLES]

JANE LINDHOLM: Ryan O’Hanlon is a staff writer at ESPN and the author of Net Gains: Inside the Beautiful Game’s Analytics Revolution. Ryan, what a pleasure to talk with you. Thanks.

RYAN O’HANLON: Thanks so much.

JANE LINDHOLM: Coming up after half time, inside the mission to grow the perfect turf for the World Cup.

[AUDIO LOGO]

Over the next few weeks, more than 100 matches will be played in 16 different stadiums across North America. The stadiums are in different climates at different elevations. Some are outdoors, some are indoors.

But they all need to have one thing in common– perfectly uniform grass. It’s been a project years in the making, and my next guest has been at the Center of it. Dr. Jackie Lyn Guevara is a turfgrass management expert at Michigan State University. Jack, welcome to Science Friday.

JACKIE LYN GUEVARA: Hi, Jane. I’m glad to be here.

JANE LINDHOLM: I’m really glad to talk with you. Are you a soccer fan, in addition to your turfgrass expertise?

JACKIE LYN GUEVARA: Well, I’m not a die-hard fan. A lot of people would say, oh, she’s not really into soccer. But I’m the person that gets so distracted.

Whenever there is a game, I’ll look at the cover, the density of the grass. Is the lighting, is the sun shining the right way on the grass? Are the players trying to avoid a certain part of the field? So those are the things that my head is just running a mile a minute.

JANE LINDHOLM: So let’s get into it. And maybe you can explain why you actually need such not only perfect grass, but perfectly uniform grass, throughout all of these stadiums. How does the grass affect the game.

JACKIE LYN GUEVARA: So that’s a great question, because for FIFA– just imagine this, the Holy Grail. Everyone looks at the grass. Having the right aesthetic is very important no matter what the grass is. And then the second is every player.

And there are multi-million, multi-billion dollar players that will play on it. So we need to give them the same feel for different grasses. Think about golf. Golf is also a natural grass. We pay attention a lot on the putting green.

And one thing that is really common between soccer and golf is how much the ball is in contact with that grass all throughout. So that’s why FIFA is really paying much attention in the grass. It’s just having that ball roll, having that consistency, the bounce is similar to a putting green when you’re doing your [? pot. ?] It’s like, oh, we need to be really consistent and have a good roll in it. Yes.

JANE LINDHOLM: Can do that? You can make it feel the same for all the players?

JACKIE LYN GUEVARA: Yeah, so we try. That’s the research. We try to do that as much as we can.

So FIFA has this FIFA specification. They have FIFA standards. First is the grass should be natural. And not a lot of people are aware of that.

So having a natural grass is very important. And then what we did was just make a recipe or guidelines for different sod farmers and field managers across North America. So what we do is, we tested different kind of grasses, different mixtures, and see if it, at the end, they will have the same parameters– for example, surface hardness or how much traction should be on the grass.

At University of Tennessee, they created what we call a fLEX machine. Basically, it’s a machine with a 3D printed foot in it. It has a lot of sensors. You can use different cleats on it.

Then from there, it can make a divot on the surface. And it will give us different parameters like surface traction, displacement. So we have the same consistent data all throughout.

JANE LINDHOLM: You mentioned, there are different grasses for different climates. But how do you decide what grass to use?

JACKIE LYN GUEVARA: So that’s a great question, how do we decide which grass to use? So there are different aspects to this. If it’s outdoors and if it’s in a cool season area, we use a Kentucky bluegrass and perennial ryegrass mix. And that recipe, I’m really proud of, because that’s my PhD dissertation.

[CHUCKLES]

But for outdoor warm season, we’re using Bermuda grass. So those are the grasses. But things might change when it’s indoors. All indoor stadiums will have cool season grass because of the reason I told you before. It uses less sunlight.

So all indoor stadiums will use that. But one thing that people didn’t really realize– Mexico City. Because when you think Mexico City, is it hot or cold?

JANE LINDHOLM: Yeah, hot, you think.

JACKIE LYN GUEVARA: Hot, you think.

JANE LINDHOLM: Mexico City is really high.

JACKIE LYN GUEVARA: So yes, Mexico City, high. It used to have a different grass before. And we did an extension, University of Tennessee and Michigan State, that we need to provide proof that we can put a cool season grass in Mexico City, so it’s also consistent with other stadiums, because it used a grass called Kikuyu grass.

They think it’s a warm season grass, but it is endemic to a mountainous area in Africa. That’s what they were using. They weren’t using Bermuda grass because Bermuda couldn’t survive because of the warm season grass.

And then they didn’t really think about maybe, we can use a cool season grass, Kentucky bluegrass and perennial ryegrass. So we went down there three years ago in 2023. We grew like a test sod for them. They tested it in the stadium. So now, what you’ll see during the opening event is that new grass– Kentucky bluegrass, perennial ryegrass mix.

JANE LINDHOLM: That is so cool. And they’re playing at the Estadio Azteca?

JACKIE LYN GUEVARA: Yeah.

JANE LINDHOLM: Yeah, I’ve been to that stadium. It’s amazing.

JACKIE LYN GUEVARA: It is amazing. Seeing the stars when I was there, I was starstruck by the whole thing of it. I was just looking at the grass looking at the stadium. It’s a lot of– I know, yes.

JANE LINDHOLM: Depending on where you sit in that stadium, you might have to have binoculars just to see the players too. It is an enormous stadium. It is so cool there.

JACKIE LYN GUEVARA: It is.

JANE LINDHOLM: How will you actually know if you and the other team members and all of the sod farmers have done your jobs well?

JACKIE LYN GUEVARA: This is like our joke in our lab. If we don’t hear anything from anyone about the turf, that’s the good news, yes. Because when you hear it, you know something went wrong.

But now it’s just in the background. People were having fun. Players are playing hard and we’re happy with that.

JANE LINDHOLM: Dr. Jackie Lyn Guevara is an assistant professor in turfgrass management at Michigan State University. Jack, thank you for joining me. Now I’m going to watch the games and just pay attention to the grass.

JACKIE LYN GUEVARA: Thank you.

JANE LINDHOLM: This episode was produced by Rasha Aridi. And a happy World Cup to you all. I’m Jane Lindholm. Catch you next time.

[THEME MUSIC]

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