1 00:00:00,080 --> 00:00:04,720 Speaker 1: It's time to get inside the Giants on Giants dot Com. 2 00:00:04,760 --> 00:00:06,640 Speaker 1: Here we go, Here we go on the Giants. Let 3 00:00:06,680 --> 00:00:09,479 Speaker 1: him in there, Let's go. Part of the Giants Podcast Network. 4 00:00:09,920 --> 00:00:13,600 Speaker 1: Welcome to the Giants Huddle podcast, presented by Fordham University. 5 00:00:13,640 --> 00:00:16,520 Speaker 1: We're joined by Thy Siam. He is the Director of 6 00:00:16,520 --> 00:00:19,560 Speaker 1: Football Data and Innovation for the New York Giants, and 7 00:00:20,040 --> 00:00:23,520 Speaker 1: Ty explain what that title means. You basically sit at 8 00:00:23,520 --> 00:00:26,160 Speaker 1: the integration of all things technology and data and how 9 00:00:26,200 --> 00:00:29,480 Speaker 1: it relates to our football operations. Are scouting departments both 10 00:00:29,480 --> 00:00:33,280 Speaker 1: college and pro, are coaching staff, and then our medical 11 00:00:33,280 --> 00:00:35,680 Speaker 1: and sport performance staff. Let's talk a little bit about 12 00:00:35,720 --> 00:00:38,600 Speaker 1: your journey from a student at Cornell. Did you ever 13 00:00:38,720 --> 00:00:42,240 Speaker 1: envision that this was where you'd wind up? Never once did. 14 00:00:42,479 --> 00:00:44,760 Speaker 1: I went to Cornell to play football kind of for 15 00:00:44,760 --> 00:00:47,120 Speaker 1: the love of the game. Um and and that was 16 00:00:47,159 --> 00:00:48,600 Speaker 1: really going to be the end of the road for me. 17 00:00:48,680 --> 00:00:51,519 Speaker 1: Ended up going to grad school there and working for 18 00:00:51,600 --> 00:00:55,120 Speaker 1: Deloitte Consulting. Never dreamed that football would land back on 19 00:00:55,160 --> 00:00:56,840 Speaker 1: my lap, but just was kind of a fan, going 20 00:00:56,840 --> 00:01:00,600 Speaker 1: to games on Sundays and Saturday's for that matter. And uh, 21 00:01:00,680 --> 00:01:02,240 Speaker 1: and it was kind of a dream come true that 22 00:01:02,280 --> 00:01:04,280 Speaker 1: I never knew I had. How did it all open 23 00:01:04,360 --> 00:01:06,160 Speaker 1: up for you to become a part of the Giants 24 00:01:06,280 --> 00:01:09,320 Speaker 1: organization in two thousand and fifteen. Yeah, I was fortunate 25 00:01:09,360 --> 00:01:11,960 Speaker 1: to uh to meet a former colleague at the NFL 26 00:01:12,040 --> 00:01:14,560 Speaker 1: League office as an alum of Cornell who introduced me 27 00:01:15,160 --> 00:01:18,200 Speaker 1: to Kevin Abrams. His name was Buck Briggs and uh, 28 00:01:18,240 --> 00:01:20,679 Speaker 1: and that connection was made early in my career and 29 00:01:20,720 --> 00:01:24,280 Speaker 1: we just kind of made that conversations around data and 30 00:01:24,319 --> 00:01:26,400 Speaker 1: analytics and how it related to football, and it was 31 00:01:26,440 --> 00:01:29,480 Speaker 1: kind of very informal until the opportunity really opened up 32 00:01:29,480 --> 00:01:31,680 Speaker 1: in two thousand fifteen. So it's one of my great 33 00:01:31,720 --> 00:01:37,679 Speaker 1: pet peeves. Um the way people approach the word analytics. 34 00:01:38,520 --> 00:01:41,319 Speaker 1: And there's something to be said for old school, but 35 00:01:41,880 --> 00:01:44,800 Speaker 1: analytics have been going on since they kept a batting 36 00:01:44,840 --> 00:01:47,680 Speaker 1: average in Major League Baseball and a manager would put 37 00:01:47,680 --> 00:01:51,559 Speaker 1: his line up together that's based on analytics. Who hits 38 00:01:51,560 --> 00:01:54,560 Speaker 1: for power, hits third or fourth. So why is it 39 00:01:54,600 --> 00:01:57,640 Speaker 1: that analytics has become a dirty word in sports? Yeah, 40 00:01:57,640 --> 00:02:00,200 Speaker 1: that's a great question. And uh and really just such 41 00:02:00,240 --> 00:02:02,600 Speaker 1: a loaded term. It's a buzzword. It's used in so 42 00:02:02,640 --> 00:02:04,640 Speaker 1: many facets that I think it's really hard to kind 43 00:02:04,640 --> 00:02:06,480 Speaker 1: of get your head around what it is. And a 44 00:02:06,520 --> 00:02:08,240 Speaker 1: lot of the work we did in analytics in my 45 00:02:08,280 --> 00:02:11,720 Speaker 1: early days here was just around access to information and 46 00:02:11,800 --> 00:02:15,040 Speaker 1: leveraging information to make decisions, which to your point, has 47 00:02:15,080 --> 00:02:18,959 Speaker 1: been going on for years in all sports and all industries. Um. 48 00:02:19,280 --> 00:02:23,120 Speaker 1: It's around process efficiency and process improvement and making sure 49 00:02:23,160 --> 00:02:25,079 Speaker 1: that people are kind of going about their day to 50 00:02:25,160 --> 00:02:27,440 Speaker 1: day work to be as efficient as possible being the 51 00:02:27,440 --> 00:02:30,720 Speaker 1: subject matter experts that they are. UM. And then ultimately, yeah, 52 00:02:30,800 --> 00:02:33,560 Speaker 1: like it's a piece of to the puzzle to to 53 00:02:34,000 --> 00:02:37,200 Speaker 1: use good pieces of data to help add insight to 54 00:02:37,280 --> 00:02:40,240 Speaker 1: kind of be guardrails on decision making uh and support 55 00:02:40,320 --> 00:02:42,799 Speaker 1: that process uh and and all the things that we do. 56 00:02:43,160 --> 00:02:45,120 Speaker 1: Tom Landry when he was a player coach for the 57 00:02:45,160 --> 00:02:49,600 Speaker 1: Giants at a science background, and he used film study 58 00:02:49,760 --> 00:02:53,639 Speaker 1: and then tendencies and analytics to create the Umbrella defense 59 00:02:53,760 --> 00:02:57,600 Speaker 1: to stop Jim Brown. So that's really an integral part 60 00:02:57,639 --> 00:03:00,440 Speaker 1: of this sport, isn't It is understanding the data and 61 00:03:00,440 --> 00:03:04,200 Speaker 1: then how to apply it. It's just become more modernized, absolutely, 62 00:03:04,240 --> 00:03:06,120 Speaker 1: and I think it's just been so robust, right, Like 63 00:03:06,160 --> 00:03:08,160 Speaker 1: we get a lot of information and a lot of 64 00:03:08,200 --> 00:03:11,680 Speaker 1: different data sources UM that we have access to. UM 65 00:03:11,680 --> 00:03:13,360 Speaker 1: and some of the best data sources that we have 66 00:03:13,400 --> 00:03:16,639 Speaker 1: access to our our end users, the inputs that they 67 00:03:16,639 --> 00:03:19,600 Speaker 1: put into our systems and processes. UM, and it's really 68 00:03:19,600 --> 00:03:21,760 Speaker 1: just kind of aggregating that and positioning in a way 69 00:03:21,760 --> 00:03:24,280 Speaker 1: that can help people. Giant season tickets are on sale 70 00:03:24,280 --> 00:03:27,360 Speaker 1: now for the season. In addition to ticket savings, membership 71 00:03:27,400 --> 00:03:31,120 Speaker 1: benefits include access to exclusive events, experiences, pre sales, and more. 72 00:03:31,160 --> 00:03:32,720 Speaker 1: You can lock in your seat starting at just one 73 00:03:32,800 --> 00:03:37,280 Speaker 1: hundred bucks called NYG is a Giants dot com slash 74 00:03:37,280 --> 00:03:41,200 Speaker 1: tickets for more information. Talk about the role that your 75 00:03:41,240 --> 00:03:43,960 Speaker 1: department has as far as integrating it, as far as 76 00:03:44,000 --> 00:03:48,480 Speaker 1: the coaching staff is concerned, and possibly game day decision making. Yep. 77 00:03:48,680 --> 00:03:51,760 Speaker 1: Dave's has been very open minded and progressive in the 78 00:03:51,800 --> 00:03:53,360 Speaker 1: way he kind of treats us stuff, you know, some 79 00:03:53,400 --> 00:03:55,880 Speaker 1: of the early conversations he had in the building or 80 00:03:55,920 --> 00:03:59,040 Speaker 1: with myself and our group in the data analytics space 81 00:03:59,520 --> 00:04:02,160 Speaker 1: UM and UH and and I think our staff in 82 00:04:02,240 --> 00:04:05,240 Speaker 1: general is very open minded to it. UM. They've they've 83 00:04:05,240 --> 00:04:07,440 Speaker 1: come from backgrounds where this has been a key part 84 00:04:07,480 --> 00:04:11,080 Speaker 1: of their game preparation process. UM. So It will start 85 00:04:11,120 --> 00:04:13,360 Speaker 1: early in the week in terms of what kinds of 86 00:04:13,400 --> 00:04:16,279 Speaker 1: tendencies can we glean inside on and our upcoming opponents. 87 00:04:16,640 --> 00:04:18,400 Speaker 1: It will kind of factor through the week as our 88 00:04:18,440 --> 00:04:21,680 Speaker 1: coaches are finding things with their eyes and they're coaching 89 00:04:21,720 --> 00:04:24,080 Speaker 1: intuition UM, and it will be a part of the 90 00:04:24,080 --> 00:04:27,279 Speaker 1: game management process in terms of how do we leverage 91 00:04:27,279 --> 00:04:29,800 Speaker 1: that information to kind of put ourselves in the best 92 00:04:29,800 --> 00:04:32,279 Speaker 1: positions to win games on Sunday. And then there's always 93 00:04:32,320 --> 00:04:35,839 Speaker 1: the variables, right I mean that even analytics can't come 94 00:04:35,839 --> 00:04:39,520 Speaker 1: into touch with if a team, uh is good running 95 00:04:39,560 --> 00:04:42,359 Speaker 1: the ball in short yardage, but you're down to offensive 96 00:04:42,360 --> 00:04:45,119 Speaker 1: linemen in the game and it the field is a mess. 97 00:04:45,880 --> 00:04:48,360 Speaker 1: Those are kind of things that you take into account, 98 00:04:48,440 --> 00:04:51,159 Speaker 1: right Yeah. I think the best end users and analytics 99 00:04:51,240 --> 00:04:53,160 Speaker 1: tend to be the people that can take all those 100 00:04:53,200 --> 00:04:56,760 Speaker 1: factors that go into what we call a model UM 101 00:04:56,800 --> 00:05:00,080 Speaker 1: and take that output, understand what what things factored in 102 00:05:00,120 --> 00:05:01,880 Speaker 1: to it, and be able to move on the fly 103 00:05:02,000 --> 00:05:04,200 Speaker 1: and understand how that changes as the game goes on. 104 00:05:04,560 --> 00:05:06,960 Speaker 1: For the layman that are watching and that aren't they 105 00:05:07,000 --> 00:05:10,240 Speaker 1: hear the word analytics, Can you give us an example 106 00:05:10,400 --> 00:05:13,080 Speaker 1: of some of the things that you will put together 107 00:05:13,200 --> 00:05:16,440 Speaker 1: during the course of a week for instance, that will 108 00:05:16,480 --> 00:05:19,520 Speaker 1: be used as far as game planning and then in 109 00:05:19,640 --> 00:05:22,000 Speaker 1: game decisions. Yeah, I mean a lot of it factors 110 00:05:22,040 --> 00:05:23,960 Speaker 1: around what a coach is gonna end up doing. So 111 00:05:24,080 --> 00:05:28,200 Speaker 1: just run past breakdowns on a number of different situations. So, um, 112 00:05:28,320 --> 00:05:30,279 Speaker 1: you know, we work closely with our coaching staff to 113 00:05:30,360 --> 00:05:33,960 Speaker 1: understand kind of how they slice and dice the call sheet, UM, 114 00:05:34,040 --> 00:05:36,919 Speaker 1: and and and try to put uh the information in 115 00:05:36,920 --> 00:05:39,400 Speaker 1: a way that's easy for them to interpret, easy for 116 00:05:39,440 --> 00:05:42,480 Speaker 1: them to react to on what to expect that an 117 00:05:42,480 --> 00:05:45,480 Speaker 1: opposing offense and opposing defense is going to do. And 118 00:05:45,520 --> 00:05:48,400 Speaker 1: then when you when you take that information, UM, I 119 00:05:48,440 --> 00:05:52,000 Speaker 1: would assume that it really is extremely valuable when you're 120 00:05:52,000 --> 00:05:56,560 Speaker 1: doing self scout, especially on the fly. So whereas back 121 00:05:56,600 --> 00:06:00,600 Speaker 1: in the day before there was as much resources, you 122 00:06:00,680 --> 00:06:02,480 Speaker 1: kind of had to wait for your bye week and 123 00:06:02,520 --> 00:06:04,960 Speaker 1: you try to self scout on the fly, but you 124 00:06:05,040 --> 00:06:07,760 Speaker 1: really needed to take a deep breath. Now your department 125 00:06:07,839 --> 00:06:11,279 Speaker 1: facilitates that on a weekly basis. Correct every week, you know, 126 00:06:11,320 --> 00:06:13,279 Speaker 1: we're kind of keeping a pulse on what what's the 127 00:06:13,279 --> 00:06:15,200 Speaker 1: opponent going to find about us? If we have a 128 00:06:15,240 --> 00:06:17,880 Speaker 1: tendency where is it and how can we get ahead 129 00:06:17,920 --> 00:06:20,560 Speaker 1: of that or use it to our advantage? Um, depending 130 00:06:20,600 --> 00:06:23,880 Speaker 1: on what those makes the show. Talk about the innovation 131 00:06:24,040 --> 00:06:26,520 Speaker 1: part of your title and what that means to a 132 00:06:26,520 --> 00:06:29,039 Speaker 1: football fan. Yeah, I think keeping a pulse on all 133 00:06:29,080 --> 00:06:32,320 Speaker 1: the latest and greatest technologies and ways to use data 134 00:06:32,920 --> 00:06:35,440 Speaker 1: as as it applies to football, keeping a pulse on 135 00:06:35,480 --> 00:06:39,520 Speaker 1: that and finding ways to adopt those practices from other sports, 136 00:06:39,960 --> 00:06:44,159 Speaker 1: other industries, um. And making sure that we're putting ourselves 137 00:06:44,200 --> 00:06:46,400 Speaker 1: in the best position to win, and that as we 138 00:06:46,480 --> 00:06:49,000 Speaker 1: understand that things are ready for Hey, this might be 139 00:06:49,040 --> 00:06:50,920 Speaker 1: interesting for a coach to look at on a regular 140 00:06:50,960 --> 00:06:53,120 Speaker 1: basis or a scout to look at on a regular basis. 141 00:06:53,360 --> 00:06:56,360 Speaker 1: That we're trying to be the liaison to introduce those 142 00:06:56,400 --> 00:06:59,440 Speaker 1: things into our processes. How much is Germaine from other 143 00:06:59,480 --> 00:07:03,159 Speaker 1: sports that use analytics to what you do and what 144 00:07:03,279 --> 00:07:05,600 Speaker 1: you try to incorporate. I think it's quite a bit 145 00:07:05,640 --> 00:07:08,839 Speaker 1: of fun. A part of the off season processes is 146 00:07:08,880 --> 00:07:12,000 Speaker 1: working with our counterparts across other other leagues and other 147 00:07:12,040 --> 00:07:15,160 Speaker 1: sports and just trying to understand like what have they done, like, 148 00:07:15,200 --> 00:07:18,000 Speaker 1: where have they failed? Where have they done really well? 149 00:07:18,360 --> 00:07:20,480 Speaker 1: And trying to say like Hey, that's a starting point 150 00:07:20,520 --> 00:07:22,440 Speaker 1: for us. Like if they spent a lot of time 151 00:07:22,480 --> 00:07:24,920 Speaker 1: on something that didn't reap a lot of benefits, and 152 00:07:24,960 --> 00:07:26,920 Speaker 1: maybe that's something we shouldn't spend a lot of time on. 153 00:07:27,080 --> 00:07:29,480 Speaker 1: Or conversely, like if they've had a lot of success 154 00:07:29,520 --> 00:07:32,520 Speaker 1: doing something that maybe there's something applicable in our environment 155 00:07:32,520 --> 00:07:34,920 Speaker 1: that we can take that and pull it in. When 156 00:07:34,920 --> 00:07:38,280 Speaker 1: you're when you're putting your team together, first of all, 157 00:07:38,280 --> 00:07:41,160 Speaker 1: explaining to the audience what your team looks like as 158 00:07:41,160 --> 00:07:43,240 Speaker 1: far as the amount of people and what a day 159 00:07:43,240 --> 00:07:47,000 Speaker 1: to day operation is. Like, let's start with off season 160 00:07:47,120 --> 00:07:51,040 Speaker 1: day to day operation. Offseason day to day operation, UM 161 00:07:51,600 --> 00:07:53,840 Speaker 1: is pretty variant. It kind of depends on you know, 162 00:07:53,880 --> 00:07:56,680 Speaker 1: some people are dedicated to scouting, some people are dedicated 163 00:07:56,720 --> 00:08:01,080 Speaker 1: to coaching, some people UM kind of falling between. But UM, 164 00:08:01,480 --> 00:08:04,080 Speaker 1: it's really putting our best foot forward to kind of 165 00:08:04,120 --> 00:08:06,920 Speaker 1: prepare the bigger initiatives that we have going on to 166 00:08:06,960 --> 00:08:10,760 Speaker 1: bigger research projects that have like a longer term milestone plan, 167 00:08:11,320 --> 00:08:13,760 Speaker 1: UM and and and and making sure that we're making 168 00:08:13,760 --> 00:08:15,840 Speaker 1: progress on those things so that when the time comes 169 00:08:15,880 --> 00:08:18,520 Speaker 1: to use that as a data point in a decision, 170 00:08:18,800 --> 00:08:20,960 Speaker 1: that it's ready to go. Um and that that that 171 00:08:21,040 --> 00:08:23,160 Speaker 1: people can look at those things. Don't miss your chance 172 00:08:23,200 --> 00:08:26,720 Speaker 1: to experience a premier hospitality experience watching Giants games, world 173 00:08:26,760 --> 00:08:30,440 Speaker 1: class concerts in two as a Giant Sweet partner, limited 174 00:08:30,480 --> 00:08:33,080 Speaker 1: full season locations are available or places a deposit for 175 00:08:33,080 --> 00:08:37,520 Speaker 1: individual games called n y is a Giants dot com 176 00:08:37,559 --> 00:08:41,839 Speaker 1: slash suites for more information. So what's your schedule like 177 00:08:42,400 --> 00:08:46,920 Speaker 1: and sort of an average work day training camp starts, 178 00:08:46,920 --> 00:08:49,720 Speaker 1: we're getting closer to the regular season. What's the grind 179 00:08:49,800 --> 00:08:54,920 Speaker 1: like as far as basic stuff that the audience can understand? Yeah, 180 00:08:54,960 --> 00:08:56,880 Speaker 1: I mean it's a lot of it, just rolling our 181 00:08:56,920 --> 00:08:59,400 Speaker 1: sleeves up and with a new coaching staff, especially just 182 00:08:59,520 --> 00:09:02,679 Speaker 1: understand ending like the vantage point that they're looking at 183 00:09:02,720 --> 00:09:05,160 Speaker 1: opponents in and just trying to understand are there are 184 00:09:05,200 --> 00:09:08,920 Speaker 1: ways that we can make something simpler for them, automated process, 185 00:09:09,559 --> 00:09:11,839 Speaker 1: get access to information to them quicker. And then as 186 00:09:11,840 --> 00:09:13,719 Speaker 1: we do those things, we get to observe a lot 187 00:09:13,760 --> 00:09:17,360 Speaker 1: of the ways they're integrating data already. Uh that allows 188 00:09:17,440 --> 00:09:20,440 Speaker 1: us also to make suggestions in terms of, you know, 189 00:09:20,559 --> 00:09:22,760 Speaker 1: what data do we have that can help them prepare 190 00:09:22,800 --> 00:09:25,920 Speaker 1: for those games. But a lot of it, especially for 191 00:09:25,960 --> 00:09:28,120 Speaker 1: the first three weeks. The first three opponents that we 192 00:09:28,160 --> 00:09:30,880 Speaker 1: have is really trying to do a breakdown of what 193 00:09:30,920 --> 00:09:33,560 Speaker 1: were the tendencies that they exposed in the one season, 194 00:09:33,880 --> 00:09:37,200 Speaker 1: Which ones of those are fair for us to expect 195 00:09:37,400 --> 00:09:41,359 Speaker 1: to carry over in the two season from a personnel standpoint, 196 00:09:41,400 --> 00:09:44,120 Speaker 1: in a statistical tendency standpoint, you know, kind of help 197 00:09:44,200 --> 00:09:48,240 Speaker 1: incorporate that into their process. How do you, um, how 198 00:09:48,280 --> 00:09:50,720 Speaker 1: do you change on the fly as the season is 199 00:09:50,720 --> 00:09:53,360 Speaker 1: going on and you realize, okay, here are certain things. 200 00:09:53,720 --> 00:09:55,760 Speaker 1: How do you make those adjustments on the fly to 201 00:09:55,840 --> 00:09:58,840 Speaker 1: stay best informed? Yeah, I think like a lot of 202 00:09:58,840 --> 00:10:01,600 Speaker 1: it just from a lead stand point, there's some continuity 203 00:10:01,600 --> 00:10:03,520 Speaker 1: in the way things happen, so we just try to 204 00:10:03,559 --> 00:10:06,560 Speaker 1: get our best understanding based on what's happened historically. And 205 00:10:06,600 --> 00:10:08,800 Speaker 1: so if you can kind of understand, like how has 206 00:10:08,840 --> 00:10:12,719 Speaker 1: that changed play calling generally historically, then you can make 207 00:10:12,760 --> 00:10:14,920 Speaker 1: better decisions about how changes are going to occur in 208 00:10:14,960 --> 00:10:17,760 Speaker 1: effect this season in order to get your job done. 209 00:10:18,120 --> 00:10:20,080 Speaker 1: How many people do you have with you working on 210 00:10:20,120 --> 00:10:23,840 Speaker 1: your team directly related to the data processes? We have 211 00:10:23,920 --> 00:10:27,160 Speaker 1: eight eight people on staff? Eight people on staff, So 212 00:10:27,679 --> 00:10:29,920 Speaker 1: are you almost like the head coach as far as 213 00:10:30,080 --> 00:10:33,280 Speaker 1: having your meeting with your staff and saying, because someone 214 00:10:33,320 --> 00:10:35,200 Speaker 1: may come up with an idea, someone might be out 215 00:10:35,240 --> 00:10:38,560 Speaker 1: dinner they heard something talking with somebody, kind of take 216 00:10:38,640 --> 00:10:40,440 Speaker 1: it and vet it just like a coach would with 217 00:10:40,480 --> 00:10:44,320 Speaker 1: a play idea. Yeah, there's definitely like a filter mechanism there. 218 00:10:44,320 --> 00:10:46,080 Speaker 1: But we've got a lot of really talented people in 219 00:10:46,120 --> 00:10:47,960 Speaker 1: our group that I'm very proud of the way they've 220 00:10:48,000 --> 00:10:50,880 Speaker 1: kind of grown and blossomed as a staff members and 221 00:10:50,880 --> 00:10:52,720 Speaker 1: and and and a lot of the things they handle. 222 00:10:52,760 --> 00:10:55,360 Speaker 1: They do a great job communicating. But but a lot 223 00:10:55,400 --> 00:10:57,640 Speaker 1: of times they have full autonomy to be working directly 224 00:10:57,679 --> 00:11:00,680 Speaker 1: with our coaches and our scouts and our staff um 225 00:11:00,720 --> 00:11:03,000 Speaker 1: trying to answer the key questions that they have and 226 00:11:03,040 --> 00:11:05,600 Speaker 1: be an immediate resource that those people can go to 227 00:11:05,720 --> 00:11:08,800 Speaker 1: and and lean on and leverage. All Right, Obviously, you're 228 00:11:08,840 --> 00:11:11,520 Speaker 1: part of a team and you're part of an organization, 229 00:11:11,559 --> 00:11:13,640 Speaker 1: and every Sunday your goal is to win a game. 230 00:11:14,160 --> 00:11:18,520 Speaker 1: But everybody has their own satisfaction points, whether it's the 231 00:11:18,600 --> 00:11:20,559 Speaker 1: O C making the right call of the d C 232 00:11:20,760 --> 00:11:22,720 Speaker 1: at the right moment that won a game, of player 233 00:11:22,800 --> 00:11:26,480 Speaker 1: makes a play for your department. Is there a moment 234 00:11:26,600 --> 00:11:30,040 Speaker 1: sometimes in a game where you just and maybe it's 235 00:11:30,040 --> 00:11:32,400 Speaker 1: something that decides the game or helps decide the game, 236 00:11:32,400 --> 00:11:36,079 Speaker 1: where you're just like, we nailed this, they used it, 237 00:11:36,520 --> 00:11:39,560 Speaker 1: and way to go. Team. Yeah, that's I mean, I 238 00:11:39,600 --> 00:11:42,120 Speaker 1: think the important thing you said there is team And 239 00:11:42,120 --> 00:11:43,960 Speaker 1: I think we view this as a team effort. And 240 00:11:44,040 --> 00:11:46,600 Speaker 1: all the pieces, whether they get used on Sunday or not, 241 00:11:46,960 --> 00:11:49,880 Speaker 1: all the pieces that we're filtering to the surface throughout 242 00:11:49,920 --> 00:11:52,040 Speaker 1: the game preparation week, I think are a part of 243 00:11:52,040 --> 00:11:54,760 Speaker 1: the puzzle. And I think that's a special part about 244 00:11:54,800 --> 00:11:57,640 Speaker 1: Sunday is it's a cumultive effort from a number of 245 00:11:57,679 --> 00:12:00,800 Speaker 1: different angles to to put our best product for uh, 246 00:12:01,080 --> 00:12:03,880 Speaker 1: for for the fans, for for the Giants, and and 247 00:12:03,880 --> 00:12:07,079 Speaker 1: and hopefully win a game. Um that sometimes there's those 248 00:12:07,080 --> 00:12:09,520 Speaker 1: individual moments where it came to service, but sometimes it's 249 00:12:09,559 --> 00:12:13,160 Speaker 1: just as effectively something that didn't happen that that data 250 00:12:13,240 --> 00:12:16,320 Speaker 1: was able to support as well. So, UM, there's winds 251 00:12:16,360 --> 00:12:18,839 Speaker 1: on both sides of it. UM. Certainly more fun when 252 00:12:18,880 --> 00:12:21,880 Speaker 1: it's like helps that for down decision or something like that. 253 00:12:22,320 --> 00:12:23,960 Speaker 1: But UM, but at the end of the day, we 254 00:12:24,040 --> 00:12:26,800 Speaker 1: do viewed as a team effort. UH, what winner lose? 255 00:12:26,920 --> 00:12:30,000 Speaker 1: The final question um, can you talk about sort of 256 00:12:30,000 --> 00:12:32,080 Speaker 1: the influence that Joe Shane has had on you in 257 00:12:32,200 --> 00:12:35,200 Speaker 1: his brief time here as he's reshaping what the New 258 00:12:35,280 --> 00:12:38,800 Speaker 1: York Giants look like. Yeah, Joe has been a great 259 00:12:38,880 --> 00:12:40,640 Speaker 1: leader in his first couple of months here. Has been 260 00:12:40,679 --> 00:12:42,839 Speaker 1: a lot of fun to learn and uh, he was 261 00:12:42,920 --> 00:12:46,320 Speaker 1: kind of at the forefront of a data and technology 262 00:12:46,360 --> 00:12:50,080 Speaker 1: revolution down in Miami and Buffalo alike. So, um, I 263 00:12:50,120 --> 00:12:52,800 Speaker 1: know what those groups started with and and and how 264 00:12:52,840 --> 00:12:55,319 Speaker 1: they evolved and that you know, the their well respected 265 00:12:55,320 --> 00:12:58,120 Speaker 1: counterparts around the NFL as a whole, and he was 266 00:12:58,160 --> 00:13:00,920 Speaker 1: integral and making sure that that grew. So you know, 267 00:13:01,000 --> 00:13:03,400 Speaker 1: he came in immediately with a number of great ideas, 268 00:13:03,840 --> 00:13:05,640 Speaker 1: um and and and has given us a lot of 269 00:13:05,720 --> 00:13:08,079 Speaker 1: autonomy to help kind of drive the initiatives that we're 270 00:13:08,120 --> 00:13:09,880 Speaker 1: working on. So it's been a lot of fun and 271 00:13:09,920 --> 00:13:12,320 Speaker 1: I know will continue to grow with that. We appreciate 272 00:13:12,360 --> 00:13:15,440 Speaker 1: you sharing the experience with the Giants fans out there, 273 00:13:15,480 --> 00:13:18,000 Speaker 1: and thank you so much and enjoy the season. I 274 00:13:18,000 --> 00:13:20,240 Speaker 1: know it's gonna be a lot of fun this year. Likewise, Bob, 275 00:13:20,280 --> 00:13:22,400 Speaker 1: thanks so much for having me. Folks, thanks for joining 276 00:13:22,480 --> 00:13:25,440 Speaker 1: us for this edition of the Giants Huddle podcast presented 277 00:13:25,480 --> 00:13:26,080 Speaker 1: by Fordham