Right. My name is T.S. Biology. I've been in this business for about 15, 20 years. Today we're going to talk about a little bit background about who we are. So the company that I represent is Cox Communications. I lead a group of user experience designers as well as research and analytics professionals. And what we want to talk through here today is what we're doing from a business of analytics and big data standpoint, but how does that affect user experience, alright? So we'll go through who we are, our philosophy, and give you some foundation material, and then we'll get into big data and how we really use it on a day-to-day basis. I got about half an hour, so we'll go through about 20 minutes of slide work here, and then we'll get into 10 minutes of questions. And I'll be available for a few more minutes after that, so you guys can contact me at that point, alright? So the way we approach design, right? So we are solving customer problems and using research and analytics while we are making sure that the experiences that we deliver either meet or exceed customer expectations. And we have different components through which we measure whether a particular experience is meeting or exceeding customer expectation. When I talk about experiences here, it's not about just UI design. It's about creating an experience which UI design is a component of, alright? So what you're seeing up there on the slide is the group that we have, we have about nine design professionals and we have about four research professionals. So roughly one is to two ratio, so that's what the group is comprised of. They come from a variety of different backgrounds, art school, industrial engineering, psychology, computational science, human-computer interaction, as well as we have data scientists that come from psych and stat background, alright? So the way we approach design, so we have physical design as well as digital design. So when I say physical design, think of it in terms of store spaces, think of it in terms of paper bill, the bill that you receive, think of it in terms of anything that's non-digital that you might be interacting as a customer inside of a workspace or a call center or in terms of something that comes to your home in terms of a set top box or something like that. So just to give you some background, I forgot I mentioned, Cox is a cable company, so we provide telephone, digital data products as well as TV communication products as well as internet home security and home automation products. What that means is, I don't know if there's anything in India that compares to something like that, if there is, I'm sorry, but essentially we provide all of these four different services bundled together and you get a discount on the bundle. So that's the business proposition there. So most of the designs that we provide range from physical to digital, but we are providing that from a discipline of thinking about data and the data that we acquire either through interviews or through interactions that customers have with our different products. And when we think through those things, I'm going to talk a little bit about how my group is structured and how we think about data and how we translate that into design principles. So from a design standpoint, it's very typical. If you're part of a design group, you have something like a UX strategy, prototyping, visual design, content strategy, depending on whether the emphasis on content strategy is if you're a digital group, if you're not, if you're a product design group, there's probably less emphasis on content strategy at that point. Our design process looks something like this. It's very iterative. You start at some point where you have an understanding of what concept that you're trying to build and you get into an understanding of what customers are expecting through either research or existing data and then we go into an understanding of what is it that we need to build. We go deep into a particular concept and then we eventually launch something and then we learn from that and then we go through this process all over again. Fundamentally, this is how most design groups work, so I'm not going to go into great details. The kind of deliverables that we go through, we have something called as blueprints. It's essentially different components of what a digital design could look like. Everything from topography to color to patterns that we're going to employ within the digital space. If it's a physical product, then we have CMF or other components that we need to consider. From a process standpoint, this is what we're doing. We think about the customer's journey through different stages, so everything from learning awareness all the way to engagement, purchase, use, and then finally serving and paying through our processes. We go through these journeys. We understand whether customers are meeting or expecting different things in each part of these journey and our designs are either surfacing components of that or we're trying to address fundamentally how we run our business from a business process standpoint. Let's look at research and analytics. This is a little bit interesting. The way we approach research and analytics, we think about it in terms of health. Health is how good of a product, how good or how well a particular product or service is doing in the marketplace, and then we think about it in terms of diagnostics. There could be a problem that comes in that says customers are having problems understanding our bill. That's a statement that comes in from some place, either through a call center or through some executive someplace, and then we go deeper into that, and then the last piece is the strategic. What we do here is we think about it in terms of if I have an investment of 100 bucks that I need to make, let's assume that capital is not unconstrained and most companies' capital is somewhat constrained, and we think about it in terms of where is the best way we could invest that $100. That $100 could be invested in new product, or it could be invested in improving an existing product, but you're also looking at it in terms of what are the returns based on that investment. We'll get into ideas of how we utilize big data and trying to drive some of those components. Within our research and analytics practice, we have about six different programs that we run. Designed research, pre-launch assessment, post-launch assessment. I'll start with design research. It's anything similar to ethnography or going into a customer's home trying to understand what is it that they do, what are they trying to achieve through the products that we provide, or if you're trying to get into a new area, what are the things that we are trying to achieve through that. Pre-launch assessment. This is pretty much risk associated with a launch of a particular product or service or a new component. Think of it in terms of if I launch this particular product or service, would customers interact with it, adopt it, and use it on an ongoing basis. Post-launch assessment is our typical large-scale survey. Once we launch something in the field, we go into the field, we try to understand how well a particular product or service is performing, and then we use that data back into understanding how we can change designs or how we can approach the service in a fundamentally different way. Modeling. Modeling, think of it in terms of mathematical models that come together to help understand value of user experience design. And when we think about modeling, we're going to get into a little bit more detail here in just a few more minutes. We use different statistical techniques, and I'll talk about those a little bit in detail. Cross-channel analytics platform, this is a platform that we have where we are able to merge together data from our call center, from our retail stores, from our website, from our mobile applications and mobile site, all the way into whatever customers are using in their homes, either through a modem or through a set-top box or whatever it might be. And then the last piece is 360 analysis. This is a better view of the different research methods that you could employ. So what this tells you is what people do, what people say that's essentially behavior versus perception, why and how to fix something, and how many and how much is essentially a quantification or a qualitative approach to the same thing. This is nothing new. Everything that I'm talking about here is not brand new. It's already been done someplace else. This is a representation from Christian Rohrer's work, if you're familiar with it. So with a 360 analysis, what we do is a complete view of the customer's interaction. So we get data from our ethnographic work, which is a pre-launch assessment or a usability testing. We could be getting data from analytics, and then we are getting data from surveys. So we bring all of these data pieces together and we try to understand what customers are doing, how they feel about it, and why they're doing what they're doing. And then we use that to employ, once again, changes to either design or different components of our business process or service. All right, so now let's get into the framework component. So when we measure our customer's reactions to our products and service, the bottom of the pyramid is usefulness. So that's essentially a measure of ease of use of a particular product or service. Usable, it's sorry, usefulness, whether a particular product is useful to the customer or not usable, it's the ease of use of measurement. We use a scale called SUS and usefulness we use a scale called CSS. In delight, it's essentially how pleasurable a particular product or service is, and we use a scale called BERT and that. And then with trust and loyalty, we essentially use NPS for loyalty and then we have a customized scale for trust. So we use all of these different components, and essentially what you get out of it is if it's a survey or something like that, you're able to essentially model how these things relate to a particular product or service that we have. And then when we report out all of these scores, this is how we typically report out. We say whether a particular product or service is meeting expectation, below expectation, significantly below expectation, or exceed expectation. So by normal curve, right, only 10% of the products or services are going to meet, sorry, be and exceed or way below categories. The rest are going to fall in between the two. We'll get into big data here. So that's a quote from Eric Schmidt from Google. I'm not going to read through it, but essentially there's a lot of data that's being created. And I'll go on a tangent here. A little less known story, the data that he presents there is not fairly accurate. So essentially what he says is it's about five exabytes of data that gets produced every two days. It's about seven exabytes of data that gets produced in every three days. So if you Google it, you'll find out the truth behind that. But essentially exabytes, in reference to how big that data is, think about it in terms of the state of California, the state of Washington, and the state of Utah. So essentially it's as big as those three states. If a single byte is a size of a grain of rice, you can essentially spread seven exabytes of data across all of these three states. That's how big it is. Depending on which company and what you guys do, your big data solution is going to be different. Your big data is going to look very different. For example, the company that I work for, we produce roughly, just from our website, we produce about 12 gigs worth of data every single day. So that's information that we're getting from our customers. And big data is essentially defined in different ways. And this is a fundamental view. You can look at it, if you Google hard enough, you can find 10 different Vs of big data that someone has explained what those Vs are. But essentially it's a variety of volume and velocity at which data comes through. So the explanation that I was giving about 12 gigs worth of data produced every single day, that's volume of that data. And if you start to look at the velocity at which that data comes in, that's what that component is. And different varieties of data. So what I explained is internet data coming from our website. You could have internet of things. So if you're in a home automation business, you probably have sensors that are connected to homes in different places and all of that data is coming through. But if you're in the B2B space and if you have a warehouse, you have sensors collecting different kinds of information about whatever business that is, right? So all of that you can combine together and you need a platform essentially to help understand what is really going on in each one of these spaces. So when you think about a typical, sorry, progression of how big data works through your organization, right, you have majority of your work today and this is probably true to most companies that are fairly immature in their big data space. Majority of your time is spent in setting up of data. The next component you'll see is either reporting or some component thereof where people are taking data from different platforms and then reporting out this is what's going on. And very little time is spent on analysis and modeling. And as you mature, majority of your time should be spent on analysis and modeling as opposed to setup or reporting. I'll just say this from the way I work to me, reporting is dead. If you're still in the reporting space, you're antiquated, you're looking at things in the past. You need to be looking at real-time data, making real-time decisions. Obviously that statement holds true in certain kinds of businesses, not all kinds of businesses, right? So in our group, we're trying to get to the target state that I'm depicting here and we have a platform that helps us understand all of this information. So we have different kinds of information coming into a cloud platform and we provide Tableau as a front-end interface to most designers as well as product managers and then we use SAS as a platform for most of our data scientists. The idea here is if you think about where people are using big data and how they're using it and some of the immaturity that I talked about early on, most of the work is fundamentally basic algebra. If you have high school algebra, you should be able to answer, 100 people came into this particular portion of the site, 10 people bought something or 10 people went into payment and that's all they're looking for, right? That's where majority of the work is. But if you want to move on to modeling and analysis and you want your data scientists to move into that space where they can provide valuable information back into your design teams, then you're going to need some help organizationally to figure out how you can self-serve those customers or internal clients, how we want to look at it to get to those basic algebra questions. Otherwise, you're going to have an analytics professional who's either a data scientist or a... Sorry about that. Or someone who has programming background trying to get at data. So essentially, your data is inaccessible to most of your designers today. And what we created with this is a way to get that data accessible to our designers. So we'll look at what kinds of problems you're able to solve once you have access to that kind of data, right? So essentially, we think about this data as a customer's journey through different touch points. So I talked about call center, retail stores. We have something called as truck rolls. I don't think there's something similar here. I could be wrong. But essentially, what happens is, let's say your phone line or your data or your internet or your TV is not working. In the US, we send a truck into your home to figure out what's really going on, and we call that a truck roll. And that truck roll is essentially the most expensive component of the business from a service standpoint. If you think about calls, let's say it costs you about a dollar, your truck roll is going to cost you somewhere between five or six times that, right? So what this depicts is essentially how many people are coming to our website, of those people, how many end up calling us, and of those people, how many end up getting a problem which they cannot solve by themselves, and how many of them end up needing a truck roll at the end of the day, all right? Wow. Okay, I got five minutes. So we can surf through all of this data and we'll get to ideas of why and what is really happening, all right? The same data represented differently here is essentially what you have is everything in blue is a call, everything in orange is a Tier 2 call, everything in green is a truck roll, everything in violet is essentially a website visit. So what is happening is if you start thinking about number of interactions customers are having, customers take up to eight interactions before 97% of their issues are solved. So when you start thinking about it from our company standpoint, we think about it in terms of can we reduce it to four interactions or less, or can we get to first-called resolution or first resolution in the first step or in the first interaction, all right? When we think about modeling, I'm going to go quickly here, all we're doing is capturing data in different ways, representing in mathematical models and then we use some kind of prediction to understand whether if we do X or Y, can that be different in real life or in the field, all right? The most common model that most people are looking at is the weather, right? So a weather gives you a view of high and low and it gives you a view of what is the chances of it raining in Bangalore today, right? So when you think about what are the chances of rain, the precipitation changes is represented in terms of a percentage, right? Which is just simple probability. But the model that drives that probability is fairly complex. It takes into account historical precipitation chances the day before weather or climate or what was happening in the city or in that location and what had happened in the previous 100 years if that amount of data is available. So we are taking something very similar. So this is essentially fairly complex that they have boiled down into a high and a low which is a discrete model and a probabilistic model which is your chance for rain, right? So we take a very similar approach and we look at it in terms of so this is data for our TV product and not ours but our competitors and we're looking at an understanding of how does remote, how does usability, how does other things that we might be doing in the marketplace as well as the reliability of that service starts to affect satisfaction. So when I talked about modeling earlier, I said if I have $100, where should I be investing? So what this helps you understand is should I be investing it in the remote? If I invested in the remote, what are the chances of NPS or the satisfaction improving? If I have to invest in usability and now you start to see where design comes in so it could be a design of remote that you're changing or it could be a design of the service that you're changing which could be part of your usability factor or it could be just pure network changes that you're making which helps you understand the reliability of that particular service and you can further start going into either the set top box reliability or a network reliability and you can further break it down into depending on how the network is laid out further things into the network on where you can utilize that investment. So the idea here is once again just like in weather we'd be able to get to a discrete value or you could get to a probabilistic value of what are the chances of success or what are the chances of NPS or NPS is Net Promoter Score which helps you understand loyalty or satisfaction improving based on the investment that you make in different components. So here's another example of the same thing. So the biggest difference here is there's an education component that was added on. So here what is happening is a customer gets an installation they get education about how the system works and how the remote works and we utilize that information and the success and the satisfaction associated with each one of those steps in the overall scheme of this service and how customers perceive the product to be and ultimately the company to be and we use that in a way where we're starting to go the investment that we need to make for next year will have to make a little bit more on let's say a different kind of remote depending on the demographics or a different kind of education depending on what kind of systems that we're putting in or in the reliability and in the shorter term we then look at how we can solve usability if you have a system that you can update on an ongoing basis. So that's how we are starting to utilize big data in the workplace today and this is probably fairly unique in that very few people are doing this kind of modeling work where you can start to predict issues or system investments that we need to be making and with that I'll take maybe one or two questions I can't see sorry go ahead ask your question I got lights in my eyes so I can't see who that is raising your hand go ahead I mean where do you find resources for such kind of work I mean we have been struggling to find resources for this which kind I mean talent no which kind design or research or analytics which one of those largely on the big data largely on the big data so most of the people that I found I can tell you that I went into schools talked about this found talent that was interested in it groomed them got them to do this on an ongoing basis in my company so that's a short answer to that you don't get any ready resources come on how many of you were ready and came into this what are company you're working for and where valuable assets to that company on day one so alright any other any more questions one more one more yes one example of so the example that I showed you right so that's based on set up boxes right so if you know what's at our box it's essentially as box that connects into your TV that gives you all the different channels what we have done is we have found where we lack in terms of what we're doing compared to our competitors and we're going to make an investment based on where we lack compared to our competitors and one of those components is remotes for elderly and education so that's something that we're going to make investment next year so that's relatively small example of how you're using it go ahead you talked about big data maturity right and you talked about the actual situations where we are giving more importance to the settings rather than we give more importance to the analysis so how do you move from giving more time and effort in doing the settings to analysis because if you don't do the settings correctly you won't get an analysis of proper data reflection right yeah great question ultimately what you got to realize is this is not something you're going to do on an individual basis this is an organizational movement you and your entire organization need to move in this direction for this to be successful this is not going to be a heroic effort of one or a group of five individuals right and as you as you understand that the kind of allies that you need to make that kind of a transformation is what's going to really be telling and it's long lasting and sustaining at the end of the day alright thanks


Let's take a look at how a baseball game is actually played You'll recall that the player who stands in the middle of the infield is the pitcher and at the start of every baseball game The pitcher will stand on the mound with the ball He will push off the rubber and he will throw the ball home towards home plate When the pitcher throws the ball, this is called a pitch and this is where everything in baseball starts At this point the batter will have only a fraction of a second to make a decision Should I swing or not? If the batter does swing either he will hit the ball or he won't hit the ball If the batter does not swing the pitch will either be called a ball or it will be called a strike and That is what this video is going to be about balls and strikes We'll come back to this flow chart a few times. So hopefully it'll help you keep everything straight When the batter does hit the ball, there are a lot of different things that can happen But in this video, we're just going to focus on these bottom three scenarios So here we have our batter at home plate Sorry about the white background. I tried to reverse the colors But if you make this batter white in the background black, he starts to look like the devil So in order to avoid frightening the younger demographic will stick with the black on white Anyway, imagine that home plate is here and we are looking at the batter as if we are the pitcher Baseball does not have a clock. So we need some way of keeping play Moving forward and this is basically the main concept behind balls and strikes So once our batter steps up to home plate an area called the strike zone is created And this extends from right underneath the batter's knee cap up to the midpoint between his belt and his shoulders So about where his team's name would be written on his uniform Vertically the strike zone is everything above home plate, which makes it 17 inches wide Because home plate has a depth if we were to look at it from above Then the strike zone is right at the front edge of home plate the edges closest to the pitcher When the batter does not swing if the pitch passes through the strike zone It will be called a strike if the pitch does not pass through the strike zone It will be called a ball And you might wonder what if the pitch is right on the line This would also be a strike if any part of the ball no matter how small it is Passes through the strike zone. It is a strike now with the ball moving so fast It might be difficult to tell where the ball was And so this is the job of the home plate umpire to determine whether the pitch is a ball or strike And this is why like in this photo you will usually see the umpire crouch down behind the catcher So he can get as good of a view as possible as to where the pitch is So when the pitch comes in the umpire will literally say out loud either ball or strike So that everybody knows what his call has been for that pitch and usually for a strike You might even see him point out to the side make some kind of hand motion to signal that it was a strike So the only way that a pitch can be a ball is if the batter does not swing at it And it does not go through the strike zone There are a few ways that a pitch can be a strike The first one we just saw if the batters does not swing and the pitch goes through the strike zone The umpire will call it a strike The second way to get a strike is if the batter swings at the pitch and misses and The third way is if the batter does hit the ball, but it goes foul So remember that everything outside of the foul lines that run down the first and third baseline Is considered to be foul territory. So if the ball is hit into foul ground or foul territory This is called a foul ball and it will count as a strike Let's jump back to our flow chart, which appears to have grown since the last time we saw it And we'll see here what we just looked at Not swinging at a pitch can result in a pitch inside the strike zone Which would be called a strike by the umpire or it can result in a pitch that was outside the strike zone Which the umpire would call a ball If you swing at the pitch and miss it, this is a strike as well And finally if you do hit the ball and it goes into foul territory rather than fair territory This is also a strike So you might have noticed here the four out of five of our branches have resulted either in a ball or a strike And so balls and strikes, I guess you could say will happen a lot You'll probably see over 200 pitches in every baseball game And the vast majority of them will either be just called balls or strikes Rather than pitches that are hit into fair territory or result in something else I said earlier that balls and strikes exist to keep the game moving forward So let's take a look at how that works. This is with something called the count Oh, sorry not that count There we go The count refers to the number of balls and strikes that a batter has seen during his at bat And the way that we say this is the number of balls and then the number of strikes So if you watch a baseball game on tv and especially if you listen to one on the radio You will hear the announcer constantly saying something like there are two balls and one strike Or the count is two and one And if you are watching on tv usually in the top corner of the screen, it will display the count numerically two balls Dash one strike. So where does this end? Or I guess you could say how high can the count go? Can you have a count of 10 balls and eight strikes? Well, the count will continue until the end of the at bat Which will be the result of a strikeout a walk the batter hitting the ball Or well, there's a bunch of different ways other than this But as far as balls and strikes go, let's look at these first two strikeouts and walks A strikeout happens when the batter receives three strikes in his at bat This will be called an out Which is another key element to keeping a game of baseball moving forward that we'll look at more in the next few videos A strikeout or any out is what the pitcher is trying to get and this is what the batter is trying to avoid So the last thing to say about a strikeout is that the third strike must come either on a called strike Or a swing and a miss which is also called a swinging strike This is another way to say that you cannot strike out on a foul ball If you have two strikes on you and you swing and foul the pitch off It would essentially mean nothing and you would just get another pitch Even if you foul off 10 pitches in a row or 100 pitches in a row Or theoretically you could stand at home plate and foul off pitches for the next week. You still would not be out Although like everything else in baseball there is an exception to this and this is if you are attempting to bunt A bunt is when a player does not swing at the ball But instead he holds the bat out and just tries to tap the ball forward a few feet So here is a batter who is trying to bunt You can see that he's moved his hand up on the bat, which will make it easier To bunt the ball So if he had two strikes on him here and he was To bunt the ball foul then this would be a strikeout But only because he was trying to bunt As for a walk this means that the batter has had four balls thrown to him Which means that he basically gets to become a base runner without even having to do anything He just had to stand at home plate and resist the urge to swing Although I wouldn't recommend this strategy because usually pitchers are pretty good at throwing strikes So if you're not going to swing more often than not you'll get a strikeout Than a walk. Okay. So now that we know that three strikes is a strikeout and four balls is a walk Let's go back to the count at the beginning of every at bat the count is Zero and zero or we would say there is no count on the batter If the first pitch is a ball then the count would move to one and oh If it is a strike whether it's a called strike a swinging strike or a foul ball The count would be oh and one The third option of course is that the batter will hit the ball into fair territory And at that point the at bat would be over If he does not hit the ball into fair territory Depending on whether the first pitch was a ball or strike the cow could either move to two and oh To oh and two or to one and one one ball in one strike or again the batter could hit the ball So I think you can see where this is going the batter can end the at bat by hitting any pitch into fair territory Or he can continue taking balls and strikes until it reaches three balls and two strikes Which is what we refer to as a full count Why is this called a full count? Well The next pitch if it is a ball the batter will walk if the next pitch is a strike It will be a strikeout A foul ball again a foul ball that the batter swung at and not bunted Will not end the at bat and this is why or at least one of the reasons why as you may have heard that a baseball game could potentially last forever Or finally of course the batter could hit the ball into fair territory In other words once you reach a full count, there is a pretty good chance Well 75 chance in fact that the next pitch will end the at bat So again, let's go back to our flow chart Everything in baseball starts with the pitch Either the batter will swing or he will not swing if he does not swing Either the umpire will call a strike if the ball was in the strike zone or he will call a ball if it is not If the batter does swing and he misses it It is a strike if he swings and he hits the ball into foul territory This is also a strike the balls and the strikes are added up in the count Which is zero zero at the beginning of every at bat and can work its way up to a full count of three balls and two strikes Four balls and you walk, but one two three strikes and you are out So that's a lot of info and while it probably still seems really complicated, especially if you're brand new to baseball I promise that after watching two or three games balls and strikes will become second nature to you


What's the word y'all welcome back to the playoff recap? We are here to talk about basketball.  I had nothing to say I just I'm just not gonna force it, but today on the other hand we had to yes I said to games of playoff basketball because that first thing we counted as a scrimmage and I have nothing to say about it Okay, let's talk about the Clippers, you know cuz over the past year. I Have been the guy. I've been one of the guys to give the Clippers the benefit of the doubt I've been one of the guys to defend the Clippers on on multiple conversations with friends on my podcast this and that It's over bro. I'm done giving them the benefit of the doubt next time We are giving them the benefit of the doubt boy Y'all better show me a lot because if you remember before the playoffs I came on to the show and I said I can't imagine The Clippers Losing the last two games of the season one of them being against okay See who are at that point we're like the worst team of all time. They were doing it, right? They know what they're doing their tank and they're successful, you know And they're all right They lost the game against them and I forgot there was one more game at the end of the season that they lost against a team That wasn't the play-in and the title comes to the podium like no, we're not trying to mess with the seating We just want our guys to be healthy and rested for the playoffs when in reality They were trying to see themselves to get the more favorable matchup and avoid the Lakers but here they are against that favorable matchup losing two games at home Losing two games at home, and I'm done. I am done Saying that they could do this they could do this and again the series is not over But I think I said the statistic that they showed at the end of this I think it was 96 point yada percent of the time if a team goes up to oh They win the series and I bet that doesn't even account for a lower seed doing it and taking home court advantage convincingly and then people on my tour at a timeline like yeah It's a big deal that the Clippers are down to oh, but the last time Kawai was down to oh He came back and won a series against the Milwaukee Bucks that happened a few years ago If you don't remember when he was with the Raptors they went on to win the championship You know the story but it's so much different It is so much more different because he was down to oh as the lower seed So he lost two games in a row whoop they do he just had to take you know He had to take one away I guess two away from them This is completely different. They had home court advantage and fumbled twice This is insane, bro, and I cannot and I'm maybe the minority here. I cannot pinpoint What about this team needs to be fixed or things that I want to see differently for them to end up winning You know cuz cuz Tyron Lou didn't make a few changes today One of the few changes was actually a successful one He played Terrence man today Terrence man practically got zero minutes in the first game He came in Terrence man is a positive defender. He hits some shots I would say he was a net positive in this overall game So he tried to come in and make some changes, but with that Like Sergei Baca didn't play. I can't look at Lucanard making 18 million and not He's getting DMPs in a playing get a playoff game making 18 This man is what the third fourth highest playing paid player on your entire team He's getting DMPs right now and Saying I don't like I said, I don't know what it is like typically we come in here like oh I want to see this and that like remember when we talked about the Lakers losing game one I was like Marcus all has to play by the boom by the band Marcus all plays and they play significantly better than they win I'm not saying I'm I'm gonna coach it a year But like there are some things you can look at and be like that's what you need to change That is the biggest thing and I don't know what it is this man Kawhi Leonard Balling absolutely balling especially in that first half what he had 30 going into the half And he he was like exerting all this energy on the off the side of the ball But like they have so many good defenders right Marcus Moore senior Paul George Patrick Beverly Nicholas Petu Rajon Ron I guess maybe not Rondo so much nowadays These are all guys that are good of good defenders that you should be able to put on Luca to not stop Luca because it's Luca we're gonna talk about the greatness of Luca in a minute But to slow down Luca so you don't have your guy that already gave you 30 Also have to kill it on the defensive side of the ball, but they couldn't do it So Kawhi had to draw 41 and then he also had to guard Luca Donzitz and here's a spoiler alert Kawhi Leonard is not a heavy minutes guy anymore It's just a fact that with this whole quad thing that happened three years ago four years ago And he's still resting still low managing He is one of those dudes that you should not play 40 minutes because he hits this thing He's gonna hit a wall where he's just not as effective because he just can't do it anymore his botically his body has been Going through the everything, you know So him playing 40 minutes of him giving you 41 points and also trying to guard Luca is insane And they just can't do it. You know, they just can't do it. I just oh my god. I'm done I'm just done defending this team. Show me come back in this series. I Won't I'm not saying nothing else positive until you come back in this series because if you don't oh my god The Clippers are looking back just two years ago Clippers fans I know first of all shout out to you for actually watching this video Because this could be a definitely a day where you turn off social media and you just you get away from it I know it's hard right now Two years ago you had one of the most fun teams in the league you had an 8c wasn't 18 8c 70 That was down the biggest the biggest What is the word? They were losing by the most points in a single playoff game is what I'm trying to say and they came back and won Shay Gildes Alexander Galanari Lou Williams that team was Amazing that team was fun and you throw it all away Plus the future of your team to get Paul George and Kawai to construct this not a no super team It's not a super team, but it was like a Constructed team that was built to win a championship Sam Preston him got all those picks Got a future store and Shay Gildes Alexander and y'all might not get out of the first round After last you're not being able to get out of the second round Two years ago your fun a team with Kawai a team of Paul George a team with Patrick Beverly And and now we're John Rondo this should be a fun team to watch and it is the exact opposite Even in the regular season where things were looking good. I've come on this show and say yeah, they're winning games But visually it's not fun to watch even though statistically they have the best offense in a league They have one of the best defenses in the league. It just wasn't pleasing to the eye And now it's even worse because you're not winning It's insane. Let's talk about the Dallas Mavericks because well, I know this is a 4-5 matchup But it's not at the same time the Dallas Mavericks Talent-wise don't really match up against the Clippers and now that I'm saying this maybe that's not even true Maybe all little talent on the Clippers is extremely overrated We just see them and like oh this player this player this play these are all great players when they rally Maybe they aren't but anyway back to my original thought. They just aren't a team that many people picked to even Get out of five That's dead now. Maybe losing six. I don't know many people that picked the Dallas Mavericks to win this series even though They have do I want do they have the best player in this series? I don't know it doesn't matter even though they have a Generational type talent at the helm who showed us last year that in the playoffs this man can up his play even more from being like What fourth fifth and MVP playing this this man Luca Donchich And I don't know how many words can explain how amazing this man is as a team as a team They shot 50% from the free throw line I cannot like if they would have lost this game because the Clippers Had his little run towards the end if they would have lost this game able to point it directly directly to the free throw shooting They shot 58% from the field Which is more than a free throw 53% from the three which is close to their free throw percentage and 54% from the free throw line Insane Tim Hardaway, Jr. It was way more than a roster or a salary-filling guy when the poor zingers tray went down You know I'm saying like they were talking about this on the broadcast I think at the end of it They were like oh, I know the next regret this and I'm like I don't think they do not send it You know I'm saying the next the next is doing quite okay right now. They don't really they're not looking at all man We shouldn't have traded away Tim Hardaway, Jr. They're doing completely. Okay, you know But Tim Hardaway, Jr. Be in that guy because everybody knew that Tim Hardaway, Jr. Can hope everybody knew and like I said in the last Episode I love a guy that's hot going into the playoffs and he continued that street today Everybody knew he can hoop the the main thing for Tim Hardaway, Jr. Has always been his consistency. He can go four games average of 20 Then you'll have five games average of 12 and bad efficiency, but in the playoffs so far He has been stellar poor zingers had a better game than the first even though they are a few times because the Clippers went Ultra small in the end of this game and then the Mavericks stuck to their guns They played poor zingers.  He's like nah, I'm gonna sit here at 20 feet out. I mean, I guess it don't matter at the end of the day But there's definitely one play on the low post or per zingers had and Rhonda on them the man didn't put the ball in the floor to like maybe back Rhonda down He just tried to turn around a shoe right over him and completely completely completely missed people like man I don't I don't see the Dallas Mavericks shooting 50% from three again Dora Finney Smith ain't gonna hit that many threes. You're right. He probably won't But then you're Tim Arthur with junior hitting his threes and of Luca has been an up-and-down three-point shooter his whole career If he's making five of 13, it's unstoppable. It really just is Who else who else? Really cally stein and his 15 minutes was really big for the team This is the definition of a front team to watch. It just really is so shout out to the Dallas Mavericks taking his lead And then they going back home It's hard to say anything other than hey the Dallas Mavericks win this series But it's the NBA and anything can happen so sad to them at least it was fun It was a fun game overall to watch that I spent ten minutes talking about that I surely did let's get to game number two before we end today's episode because the Lakers bounce back I was ready to name this video um The city of LA city of winners It's just something corny if both of the LA teams won But one of them then first of all the NBA is really just messed up by starting these games 30 minutes apart from each other So like as much as I wanted to deep dive into the Clippers game or I guess the Mavericks game or deep dive into this Lakers victory I couldn't because I was trying to dual screen it and listen to commentary on one But switches to the other one a commercial came on but this is what I took away from the Lakers win Anthony Davis came to play we knew he wasn't going to put up 12 a game in this whole series and he came to play He showed he played show this fire drew a ton of fouls He drew a ton of fouls, but like people are always say kidding. You look at the look at the free throw this Barrage, but it wasn't it was one and I know Devon Booker shot ten free throws in the last Minute and a half um, but like when you when you talk to me about a team getting more calls than the other Put together a video and show me this this was not a foul or this was a foul because I was watching this game When Anthony Davis was fouled he was fouled, you know what I'm saying? He worked hard for those 21 free throws and they needed that LeBron James obviously had a better game than game number one But he ain't he ain't playing with that same aggression as he has in this entire career And maybe that goes to what he said before the playoffs even started I'll never be at a hundred percent because he's not driving to the lane whatsoever They didn't really need it today LeBron hits again another game where he had one of the most crazy Threes to ice it or put it away just LeBron type things Drummond good game from Drummond It wasn't one of those games where you look at the stat line and be like oh he had 12 and 12 where he was As today was a game where he had 15 and 12 and it felt like he had a positive 15 and 12 in this game especially early into it and like I mentioned earlier. We got the Marcus all Minutes the Marcus all minutes were great. He was flabby. He was everywhere They were leaving them open and he capitalized. There was one late in the fourth quarter Where he got the ball on the wing open for three He took like four seconds winding that shot up and he made it, you know, they were guarding him out there And he made that shot. Um, what what else came here KCP? He looks at the basket in the first quarter and he'll miss his first two shots And he'll stop looking at the basket LeBron got to get into his ear because MVP KCP is a real thing So we need him. I'm saying we they need him to shoot better But the real MVP other than of course the top two guys we didn't assure they're playing Dramatically better in game number two than game number one, but I hated this game Mostly because CP couldn't play he finished with 22 minutes and he didn't play down a stretch now luckily for the two I mean, maybe not luckily they still lost. Cameron Payne is a backup has been Tremendous for them But when it mattered the most when it was the last couple minutes of the game You can desperately tell that you needed Chris Paul out there. You just didn't Cameron Payne is cool. Devon Booker is a good playmaker But they needed that veteran because you have to remember without Chris Paul on his team This is with the second youngest team in the playoffs, you know, I'm saying so if Chris Paul is not on the court You're running out players that have never played playoff minutes before and you saw that in the last couple minutes Man, they couldn't get a bucket. They turned them ball over a few times and a couple just bad shots Chris Paul would have Nope, I got this. Let me get to my spot in this little mid-range area I'm gonna make a few, you know shift the momentum a little bit Especially since we at home, but they didn't have that I don't know what the status is gonna be for my boy for game number three But it's just even in the minutes. He did play. I'm like, I was just thinking to myself Just don't play him, you know, let him rest.  So I'd rather I'd rather have camera pain play right now Well, what a what a time we live in it. That is a real sentence DeAndre Aden followed up his first diamond a game with another one But obviously the Lakers also brought in their firepower with the big man It was it was a good game again I didn't like it because Chris Paul didn't wasn't able to play and if Chris Paul is playing They I think they I think they win this game. Michael bridge is not a good game. J crowd are not a good game I don't expect them to continue to shoot this poorly But it is what it is man. It is what it is the other game that happened to scrimmage. I turned it off after the first couple minutes Then Blaine Leonis, which I had no interest after the first couple minutes We were at the studio The not the studio the set I think because when I say studio people think like music studio not music studio We were at the set and this game came on we start watching it And we were like y'all gonna go get some food. So we went to go get food Looking at the box score here. Here's my analysis strictly based off the box score Kyrie James Harden Kevin Arant Joe Harris Blake Griffin are all all very very good at basketball. So Yeah