1 00:00:01,160 --> 00:00:04,600 Speaker 1: Since you're a subscriber to this Bloomberg podcast, we thought 2 00:00:04,640 --> 00:00:08,119 Speaker 1: you'd be interested in a new four episode sponsored podcast 3 00:00:08,240 --> 00:00:13,280 Speaker 1: called The ROI Rules of Ai, produced by IBM and 4 00:00:13,320 --> 00:00:17,400 Speaker 1: Bloomberg Media Studios. It explores how business leaders are thinking 5 00:00:17,440 --> 00:00:22,639 Speaker 1: about the return on investment of artificial intelligence projects. You 6 00:00:22,680 --> 00:00:27,080 Speaker 1: can subscribe wherever you listen to your favorite podcasts. Here's 7 00:00:27,200 --> 00:00:32,720 Speaker 1: a recent episode. Imagine you're the head football coach of 8 00:00:32,760 --> 00:00:37,880 Speaker 1: a major college football program. It's third down and five 9 00:00:38,000 --> 00:00:41,280 Speaker 1: yards to the goal line, with the game clock winding down. 10 00:00:42,080 --> 00:00:45,320 Speaker 1: There are one hundred thousand spectators in the stands and 11 00:00:45,479 --> 00:00:51,280 Speaker 1: millions more watching on TV. Your whole season, and potentially 12 00:00:51,360 --> 00:01:00,200 Speaker 1: your job, rests on what happens next. But in fact, 13 00:01:00,560 --> 00:01:04,280 Speaker 1: the game may well have been determined months before when 14 00:01:04,280 --> 00:01:08,000 Speaker 1: you recruited this roster of players. What if you could 15 00:01:08,000 --> 00:01:12,320 Speaker 1: have used AI to help determine which players to select. 16 00:01:13,319 --> 00:01:17,280 Speaker 1: That's the challenge a startup called Edge three dot AI 17 00:01:17,600 --> 00:01:18,720 Speaker 1: is trying to address. 18 00:01:19,440 --> 00:01:22,400 Speaker 2: We have called his amateur sports for a long time. 19 00:01:22,760 --> 00:01:26,920 Speaker 1: It's a business that's Kenya and Rashid, a co founder 20 00:01:26,959 --> 00:01:30,280 Speaker 1: and CEO of Edge three, a former co captain of 21 00:01:30,280 --> 00:01:33,520 Speaker 1: the Oklahoma Sooners, and a running back for the NFL's 22 00:01:33,560 --> 00:01:37,319 Speaker 1: New York Giants and Jets. Rashid has spent the past 23 00:01:37,360 --> 00:01:43,040 Speaker 1: two decades developing and commercializing emerging technologies for the sports industry. 24 00:01:43,840 --> 00:01:47,440 Speaker 1: For the past three years, he and his partners, who 25 00:01:47,480 --> 00:01:52,680 Speaker 1: include CBS college football analyst Brian Jones an NFL Hall 26 00:01:52,720 --> 00:01:56,040 Speaker 1: of Famer Warren Sap, have been using AI to build 27 00:01:56,080 --> 00:01:59,600 Speaker 1: a product that will help college football coaches find the 28 00:01:59,640 --> 00:02:03,480 Speaker 1: right place players and assist high school players in finding 29 00:02:03,520 --> 00:02:08,320 Speaker 1: the right college team. From IBM and Bloomberg Media Studios, 30 00:02:08,800 --> 00:02:12,840 Speaker 1: this is the ROI Rules of AI and I'm your 31 00:02:12,880 --> 00:02:18,120 Speaker 1: host Edward Adams. On this podcast, we're exploring how companies 32 00:02:18,160 --> 00:02:21,920 Speaker 1: of all sizes are using AI to remake their operations, 33 00:02:22,400 --> 00:02:27,840 Speaker 1: increasing their return on investment and that of their customers. Today, 34 00:02:27,919 --> 00:02:33,040 Speaker 1: we're investigating how to apply artificial intelligence to athletic intelligence 35 00:02:33,480 --> 00:02:41,919 Speaker 1: remaking top collegiate football programs nationwide. Like a lot of industries, 36 00:02:42,120 --> 00:02:46,080 Speaker 1: college football is being disrupted, but rather than being challenged 37 00:02:46,080 --> 00:02:49,640 Speaker 1: by a competitor, the disruption is coming from within, with 38 00:02:49,760 --> 00:02:53,560 Speaker 1: both student athletes and some schools pushing back against the 39 00:02:53,600 --> 00:02:57,919 Speaker 1: status quo. In twenty twenty one, the US Supreme Court 40 00:02:58,000 --> 00:03:02,320 Speaker 1: ruled in favor of students, finding that the NCAA violated 41 00:03:02,360 --> 00:03:08,040 Speaker 1: antitrust laws because it prohibited compensating college athletes. That same year, 42 00:03:08,480 --> 00:03:11,880 Speaker 1: the NCAA dropped the requirement that players had to sit 43 00:03:11,960 --> 00:03:16,880 Speaker 1: out a season if they transfer schools. So suddenly players 44 00:03:16,960 --> 00:03:20,519 Speaker 1: were unrestricted free agents and could be paid by groups 45 00:03:20,520 --> 00:03:26,200 Speaker 1: of alumni, supporters or advertisers. The NCAA has even proposed 46 00:03:26,400 --> 00:03:29,680 Speaker 1: that top schools should be able to pay athletes directly. 47 00:03:30,560 --> 00:03:32,880 Speaker 1: With some of the best players now jumping from one 48 00:03:32,880 --> 00:03:36,080 Speaker 1: school to another in search of more compensation and more 49 00:03:36,120 --> 00:03:40,520 Speaker 1: playing time, Rashid says that increasingly the scholarships that used 50 00:03:40,560 --> 00:03:43,280 Speaker 1: to go to high school recruits are now being given 51 00:03:43,320 --> 00:03:46,320 Speaker 1: to more experienced transfers that have a better chance of 52 00:03:46,360 --> 00:03:51,200 Speaker 1: making an immediate impact on teams. With fewer scholarships available, 53 00:03:51,560 --> 00:03:54,720 Speaker 1: high school recruits are left to their own devices to 54 00:03:54,760 --> 00:03:58,839 Speaker 1: find a college program that best values their talent and abilities. 55 00:04:00,160 --> 00:04:02,240 Speaker 2: Never in the probably the last fifty years, have we 56 00:04:02,280 --> 00:04:06,040 Speaker 2: seen such a paradigm shift in this business model and industry. 57 00:04:06,360 --> 00:04:08,480 Speaker 2: You have both sides trying to react to it in 58 00:04:08,520 --> 00:04:11,280 Speaker 2: real time, and so what Edge three is doing is 59 00:04:11,320 --> 00:04:14,880 Speaker 2: providing efficiencies on both sides to help them adapt to 60 00:04:14,920 --> 00:04:16,880 Speaker 2: this new way of recruiting. 61 00:04:17,279 --> 00:04:21,240 Speaker 1: And the business of college football. Recruiting is big business. 62 00:04:21,760 --> 00:04:25,000 Speaker 1: The average college spends one point four million dollars a 63 00:04:25,080 --> 00:04:28,880 Speaker 1: year on recruiting, and costs have shot up fifty one 64 00:04:28,960 --> 00:04:36,080 Speaker 1: percent since twenty twenty one, according to Client estimates. Today, 65 00:04:36,520 --> 00:04:40,159 Speaker 1: lots of companies rate high school players, but they're comparing 66 00:04:40,200 --> 00:04:44,080 Speaker 1: them to each other. What EDGE three does is quickly 67 00:04:44,120 --> 00:04:49,479 Speaker 1: compare them to current and prior college players, using new 68 00:04:49,520 --> 00:04:53,520 Speaker 1: predictive models to determine their odds of success playing at 69 00:04:53,560 --> 00:04:55,200 Speaker 1: each program. 70 00:04:55,520 --> 00:05:00,040 Speaker 2: AI allows you to create new recruiting models that don't exist. 71 00:04:59,839 --> 00:05:04,520 Speaker 1: To After crunching the data on more than fifteen thousand 72 00:05:04,600 --> 00:05:10,160 Speaker 1: college players, EDGE three has found some surprising results. For instance, 73 00:05:10,520 --> 00:05:13,760 Speaker 1: it's the conventional wisdom in high school sports that the 74 00:05:13,800 --> 00:05:17,839 Speaker 1: best players should play only one sport, both to maximize 75 00:05:17,880 --> 00:05:21,120 Speaker 1: their focus and to avoid injury in the secondary sport. 76 00:05:22,040 --> 00:05:24,359 Speaker 1: But the data says that's wrong. 77 00:05:25,160 --> 00:05:28,440 Speaker 2: What we found is that most of the successful athletes 78 00:05:28,600 --> 00:05:31,000 Speaker 2: at the next level, let's say at a quarterback position, 79 00:05:31,080 --> 00:05:32,120 Speaker 2: are two sport athletes. 80 00:05:33,120 --> 00:05:37,559 Speaker 1: Take Kansas City quarterback Patrick Mahomes, the three times Super 81 00:05:37,560 --> 00:05:41,080 Speaker 1: Bowl champ. He's well known for his ability to throw 82 00:05:41,200 --> 00:05:45,279 Speaker 1: sidearm while scrambling away from tackles. It's what coaches call 83 00:05:45,560 --> 00:05:48,680 Speaker 1: a quarterback's arm angles. Gotchrill. 84 00:05:48,680 --> 00:05:51,520 Speaker 2: Mahoone's dad was a baseball player, and so he grew 85 00:05:51,600 --> 00:05:54,599 Speaker 2: up playing baseball, and so he developed those arm angles 86 00:05:54,640 --> 00:05:55,600 Speaker 2: from playing baseball. 87 00:05:56,920 --> 00:05:59,599 Speaker 1: Edge three can predict the odds a high school player 88 00:05:59,600 --> 00:06:02,480 Speaker 1: will train ansfer from a certain program. 89 00:06:02,680 --> 00:06:05,200 Speaker 2: There are certain kids that come out of certain programs 90 00:06:05,200 --> 00:06:07,880 Speaker 2: in high school that have a higher risk of transferring 91 00:06:07,960 --> 00:06:11,120 Speaker 2: if they go to certain geographical areas. As a coach, 92 00:06:11,200 --> 00:06:14,760 Speaker 2: I start weighing those probabilities when I'm deciding on where 93 00:06:14,800 --> 00:06:16,560 Speaker 2: to give this money and this scholarship. 94 00:06:16,600 --> 00:06:20,880 Speaker 1: To EDGE three isn't just aggregating a high school player's 95 00:06:20,960 --> 00:06:22,080 Speaker 1: on field stats. 96 00:06:22,839 --> 00:06:26,679 Speaker 2: We're also looking at social data. We're looking at digital 97 00:06:26,760 --> 00:06:30,599 Speaker 2: mentions and sentiments based on each individual athlete to start 98 00:06:30,640 --> 00:06:33,240 Speaker 2: to give you an overall value of what he is 99 00:06:33,279 --> 00:06:35,360 Speaker 2: to the actual program. 100 00:06:35,720 --> 00:06:39,960 Speaker 1: Ultimately, EDGE three calculates the dollar value of a player 101 00:06:40,200 --> 00:06:43,880 Speaker 1: to a college team. How do you go about predicting 102 00:06:44,080 --> 00:06:48,120 Speaker 1: what a high school player ought to be paid in college. 103 00:06:48,400 --> 00:06:51,320 Speaker 1: It seems like it would be almost impossible to figure 104 00:06:51,320 --> 00:06:51,760 Speaker 1: that out. 105 00:06:52,640 --> 00:06:54,839 Speaker 2: Well, they figured out in the NFL all the time 106 00:06:55,279 --> 00:06:57,520 Speaker 2: using the same type of data points. 107 00:07:02,160 --> 00:07:06,320 Speaker 1: After Edge three uses AI to aggregate mountains of player 108 00:07:06,400 --> 00:07:10,520 Speaker 1: data from both structured and unstructured sources. 109 00:07:10,080 --> 00:07:12,840 Speaker 2: We then are using AI to run predictive models against 110 00:07:12,880 --> 00:07:14,800 Speaker 2: it to notice patterns against baselines. 111 00:07:15,440 --> 00:07:19,240 Speaker 1: The software also uses conversational AI to allow high school 112 00:07:19,240 --> 00:07:22,800 Speaker 1: players to ask the database about the best schools to attend. 113 00:07:23,680 --> 00:07:27,560 Speaker 1: Schools can input their own data into the system. Limiting 114 00:07:27,640 --> 00:07:30,840 Speaker 1: data access between competing parties is part of what's known 115 00:07:30,880 --> 00:07:33,280 Speaker 1: as data governance and it's crucial. 116 00:07:33,840 --> 00:07:36,040 Speaker 2: I don't think a coach would trust Kenya a Rashid. 117 00:07:36,080 --> 00:07:38,160 Speaker 2: What is data? And the first question we're going to 118 00:07:38,240 --> 00:07:40,680 Speaker 2: get from teams is if I give you any part 119 00:07:40,720 --> 00:07:43,240 Speaker 2: of my data, how do I know it's safe. The 120 00:07:43,280 --> 00:07:46,560 Speaker 2: biggest reason why this partnership with IBM was so important 121 00:07:46,680 --> 00:07:49,520 Speaker 2: because there's a lot of data companies out here, but 122 00:07:50,640 --> 00:07:53,560 Speaker 2: IBM has been around for years. The reward of working 123 00:07:53,560 --> 00:07:57,400 Speaker 2: with IBM is they have enough resources that we can 124 00:07:57,520 --> 00:08:00,000 Speaker 2: find the right people with the right products and services 125 00:08:00,040 --> 00:08:01,720 Speaker 2: that can help us at the stage that we're at. 126 00:08:02,800 --> 00:08:06,080 Speaker 1: Working with a company of IBM's breadth and experience is 127 00:08:06,200 --> 00:08:08,960 Speaker 1: enabling Edge three to go to market faster than it 128 00:08:09,000 --> 00:08:10,080 Speaker 1: could do on its own. 129 00:08:11,160 --> 00:08:13,440 Speaker 2: The time that it would take us to get these 130 00:08:13,480 --> 00:08:16,960 Speaker 2: pieces together and actually just even put them in predictive 131 00:08:17,040 --> 00:08:21,120 Speaker 2: models would be astronomical for a startup in our position. 132 00:08:21,560 --> 00:08:24,560 Speaker 2: So we needed an IBM to help us accelerate these 133 00:08:24,600 --> 00:08:27,280 Speaker 2: things and really tell us things that we didn't know. 134 00:08:27,640 --> 00:08:29,360 Speaker 2: We didn't know how to go get the data, and 135 00:08:29,400 --> 00:08:31,120 Speaker 2: we knew it was there, we didn't know how to 136 00:08:31,160 --> 00:08:32,960 Speaker 2: pull it in, we didn't know how to configure it. 137 00:08:33,360 --> 00:08:35,760 Speaker 2: And so really the guidance and some of the consultants 138 00:08:35,760 --> 00:08:38,600 Speaker 2: around IBM have been able to help us kind of 139 00:08:38,679 --> 00:08:40,520 Speaker 2: understand how we need to formulate that. 140 00:08:41,160 --> 00:08:45,040 Speaker 1: The sales pitch to schools boils down to helping reduce 141 00:08:45,120 --> 00:08:50,000 Speaker 1: the constraints that they and all businesses face, reduce expenses, 142 00:08:50,600 --> 00:08:51,840 Speaker 1: increase productivity. 143 00:08:52,559 --> 00:08:54,400 Speaker 2: I can go to a coach and say I know 144 00:08:54,440 --> 00:08:57,080 Speaker 2: how much time and effort I can save you, and 145 00:08:57,120 --> 00:08:59,120 Speaker 2: I can equate that to dollars because I know what 146 00:08:59,120 --> 00:09:02,480 Speaker 2: you're spending in recruit and no coach wants to spend 147 00:09:02,520 --> 00:09:05,200 Speaker 2: more money and waste more time. 148 00:09:06,080 --> 00:09:10,720 Speaker 1: While Edge Three's product has a targeted market, its experience 149 00:09:10,760 --> 00:09:14,880 Speaker 1: with IBM holds lessons for other companies AI. 150 00:09:14,720 --> 00:09:17,760 Speaker 3: Is a technology that can be applied to every size 151 00:09:17,760 --> 00:09:20,160 Speaker 3: of company, even if you are a startup. You can 152 00:09:20,240 --> 00:09:24,120 Speaker 3: make a difference in the market. You can disrupt what's 153 00:09:24,160 --> 00:09:26,360 Speaker 3: already in there using AI. 154 00:09:26,920 --> 00:09:32,480 Speaker 1: That's Marcella Viro, vice president of Data and AI at IBM. 155 00:09:32,679 --> 00:09:36,360 Speaker 1: While where Sheid has worked in sports marketing, he's new 156 00:09:36,480 --> 00:09:37,920 Speaker 1: to artificial intelligence. 157 00:09:38,960 --> 00:09:41,360 Speaker 3: First of all, they know a lot about their business, 158 00:09:41,600 --> 00:09:45,960 Speaker 3: but they are not technology experts, so they relied in 159 00:09:46,040 --> 00:09:51,439 Speaker 3: our partnership to build a successful, unique solution using AI. 160 00:09:52,320 --> 00:09:55,880 Speaker 3: They were aware the data is available from different sources 161 00:09:55,960 --> 00:09:58,959 Speaker 3: all the time, but they had to find the tool 162 00:09:59,040 --> 00:10:02,400 Speaker 3: that would help them to manage that data and to 163 00:10:02,480 --> 00:10:06,719 Speaker 3: trust that data. Governance is related to your brand, to 164 00:10:06,760 --> 00:10:10,400 Speaker 3: your reputation. This is fundamental to any size of company. 165 00:10:10,600 --> 00:10:13,679 Speaker 3: It's important for a company not only to start a business, 166 00:10:13,720 --> 00:10:15,600 Speaker 3: but to stay in the business. 167 00:10:16,360 --> 00:10:20,480 Speaker 1: For Rashid, the parties bringing different strengths to the table 168 00:10:20,880 --> 00:10:23,120 Speaker 1: is key to building a successful product. 169 00:10:23,640 --> 00:10:25,720 Speaker 2: This is a bunch of athletes who have gotten together 170 00:10:25,760 --> 00:10:29,240 Speaker 2: with a technology company and said, let's go build something 171 00:10:29,880 --> 00:10:33,120 Speaker 2: that works. And that's what this partnership with IBM represents. 172 00:10:34,800 --> 00:10:38,520 Speaker 1: Edge three dot AI is scheduled to become available to 173 00:10:38,559 --> 00:10:43,600 Speaker 1: both schools and players in August. We wish Rashid and 174 00:10:43,679 --> 00:10:48,160 Speaker 1: his team all the best. This has been The ROI 175 00:10:48,440 --> 00:10:54,000 Speaker 1: Rules of AI, a podcast from IBM and Bloomberg Media Studios. 176 00:10:54,320 --> 00:10:57,080 Speaker 1: If you like what you're hear, subscribe and leave us 177 00:10:57,120 --> 00:11:00,320 Speaker 1: a review. I'm Edward Adams. Thanks for instin