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There I didn't have it up front Nice to meet you. Yeah, there you are. Welcome everyone. This is Mike My name is Melissa Arma and Mike is a trader Mike. Why did you do the class? I think earlier in the year Really? Do you only do the class this year in 2016? Yeah. Yeah. No way.  Tell me a little bit about you. No, I'm not I So I should look at the camera Okay, well, yeah, I'm not a full-time trader. I Have a full-time job. I'm an engineer But you know, I started trading like last last year in July and And but I just do it as a hobby Well, it's a It's a consulting job.  So you you're probably there at least four days of the week in the room, right? Yeah, yeah, that's right. Yeah, so when you first started out, what were you doing before you took my gap? That's what were you doing? Like you said July. What were you doing in July? I? You know, I'm new to the market.  Overall, I mean just to read the charts to see if the stock is an off trend or a downtrend You could to get that right you know, you need to get that right in the first place and Yeah, and then just You know before I would read the charts as like You know, if it makes a well, I just Reaction, but you know looking at looking at it from a you know, whether you know It gaps or not and how much it gaps, you know, the quality of the gas You can see you can kind of get a clue as to where the institutional money is And tell me that when it's trading, but also in day trading, I just didn't know how to you know enter and and how to exit but You know, I mean that's that's helped a lot.  It just kind of helps you see the big picture You know instead of just It's it's just coming with experience. I guess I mean Because I've never did I think I would say for someone who's starting off in trading they should With I think I would highly recommend a trade with somebody who actually trade and if we know what they're doing because Because if you just try to do it by yourself, you just you don't really know I think that being treated with you You know your perspective and and contact And so you just learn so much faster, you know Um, that's great. Yeah, so I would say it just you just give overall direction, you know You just keep things in perspective and you can kind of kind of see um You know the market through Someone who knows what they're doing You know to you is because you took this Amazing call that I made in the market and you have a better price than me and not really jealous And I looked at it tonight to see what it closed down Of course, I'm I'm better today than I've ever been now with the close today when I looked at it when I got back tonight So obviously I didn't look at yours. What's the what was the difference between the bid and the asker? You're trained today Yeah, so, um, I bought it at three cents and now the the spread I think is I think it's between eight and 11 That's fantastic. And so I could I could definitely could fill that nine cents You know, but I'm Okay, so tell everybody what you did tell everyone it wasn't on my email list because I'm I'm whatever you want to know What exactly did you do and why? I've heard you talking about uh, that that spy train.  I think around 180 and the spies and then, um You know, first I I thought uh, I think 300 at three cents. Okay. And then um And I was like, you know That they're so cheap, you know So and the thing is is Like, um, you know, you couldn't I could lose, you know Three cents per contract, but I could make You know, god knows how much And so it's just so I just so a couple days later.  I bought, um, I only I got filled at three cents for for all of them. So I bought 500 in total And so that's about 1500 plus In 375 with commission. Okay, but the less than 2000 for the entire So your profit right now is two grand Yeah, yeah, okay. Yeah, so it's the difference between what you could sell it for forces What you paid is the profit that works because you did an option trade, right? Now what what is the benefit of doing an option versus taking a day trade using my method for someone like you? um In action, um, if you if you get full compression, right, then you have you have some Accessibility as a person day trading because you're in day trading If you get the direction wrong, you know Then you lose money that day when in swing trading Um, it's a little bit more forgiving. Um, you know, I wanted to get the overall direction, right? So You have you can hold on to it You're a good amount of money and then you're coming to new york and you're taking me to dinner Like, you know, because you have a better price of them than me I'm bliss now I mean, I could have bought more and cost average my price down and I thought about it But I spent so much money like because I took a big position I have 300 but I took it back in december and then I figured out what I would have had to buy To pull myself price down and I was like forget it. It's not worth and I'm gonna just write it out I knew it was good But when you took it and when I was talking about the market Did you have a hundred percent conviction in what I was saying because every day I'd be like bullish bullish and I'm like no one believed me in the room. Did you believe me at first? And then you like question it or did you there's something here like when did you actually say Was it before you took the trade or did you always believe what I said or you were like, wait a minute. This is crazy I mean, I we do wrong, but you know, you know the market it it moves kind of slow You know, so there were some sometimes, you know, when I was like, I'm just gonna work but But the thing is Overall, I believe here because um, you know me that you know what you're talking about So I know it's just um, it just makes sense because you know, we have the 180 I think it was um, about the bottom And it's just and also it's uh, I'm comfortable with the risk Yeah It was it was just a good trade, you know I mean We held the 180 on the five And you know, even if I'm wrong, you know, it's it's um, really like $1,500-$2,000 Right It's just a it's just a great trade. You have to if the risk to reward is that good you have to kick trade So now let we talked about this in the room. We said no piggy targets. Let's just say this thing rallies a dollar Okay, it rallies a dollar since let's just figure out 50 000 shares You basically have a 97 cents. You would be up 48 500 dollars.  Oh Like 50 50 000. Yeah Um, I guess Yeah, I mean, I would get off half. Yes. Okay. Very good. That's the answer I wanted to hear You know, if I think that the market's gonna keep going up, you know Hold it to like maybe to satisfy it back for december expiration. Yeah You know, but I mean, I'll just if I'm up 50 000, I'm getting rid of half. I would have to I was gonna ask you and you said the perfect answer because $25,000 that's a lot of money to make in the trade for the risk and you still would have you such a huge position You'd still have 250 contracts that if the rest of it rides and it could be worth A couple bucks that's still even more money and you have have booked and then if the rest flop off It doesn't even matter like that's that was a good thing because you have a strike price I think of what 240 or is that what it is? Yeah, yeah Yeah, definitely So like you said, you could you could get something out later Continuing to look at it and seeing when we hit up over the high It depends when we hit up over the high the sooner we hit up over the high The more those are gonna run faster Well, I'm so glad that example of someone that has done normal risk that you can afford And stayed with the trade not lost conviction and not killed it because of fear or something and not rich But look at the potential you have now in the trade So, I mean you really have done a great job with it You're you're you're one of the people that has taken my class and that's why I think it's great to showcase someone like you That's doing well that really quickly. Let's talk about your day trading So how is that going as far as like let's just talk about since since Well, really let's go back to earning season first quarter Like at the beginning of the year january february. It was your first earning season then after the class. How did you do? Um, I was just um, I wasn't really taking trades. I was just watching Really? Yeah, and then And then um, you know, I still Now I can do things more on my own.  But you know, but in terms of um day trading See, okay I have this problem.  I'm gonna get out too quick. Um, and then But overall from the direction, right? Yeah Um, I think that I'm just gonna come with with experience and once I you know game I wouldn't think too much about The loss, but I think I just focus more on the loss than the what I can You know just over a trade like reading the market, you know, um in the direction I'm I just need to stop, uh, you know thinking and if I believe that it's gonna work and I see the setup I should just take it, you know without thinking I think so what is holding you back even though you're seeing it You're seeing like 80 of them work What's holding you back is the fact that you still might lose. Is that what you're saying? Because I lost so much, um in the beginning of getting out, you know from july to november and no actually even Yeah, I have a lot of swing trade positions. Actually, I got ran over in um, january Okay, last year you mean Um, no actually January this month In terms of um swing trade, I still have long term swing trading positions on and they were all on the long side and so You know, I just I did and um, I think you know, that's how you got me psychologically But that's probably why I'm not, you know, because I But the thing is, I mean, I'm recovered. So yeah, yeah, yeah So, I mean, I think it'll it'll I just need to Just keep working at it. But in terms of um reading the market and I mean, I keep I keep a spreadsheet and um, I I would have made so much So you would have made back all of your losses and then um team thousands probably if you had done all the Even though the other day, um, we were watching I think that day stx or Yeah, and then Paul was watching wbc. Um, I took wbc But um, why I said earlier post actually ended up losing uh down Yeah, we both worked that st Was it stx? I don't even remember because I can't forget the chart Yeah, but that one, you know, right that one did move um a lot more but um wbc worked too But it was a little bit more choppier. Yeah But but that one see even that I better and I was like, how did I do that?  I mean holding them a little bit longer is an easy problem Or like take it get half out into the first place that you would don't lower the stop Keep the stop for the rest of the original place and ride the rest out You know what I mean or or trailed and and and then he would just trail it breaking It's just about a lot of it is mental. I mean we talked about this in the gap class You've got to get through past those points of things that happen in the past to you And everybody's vantage point like some people Their parameters of how much money they lost is so different from somebody else's for you. It might be Really horrendous to you, but if you talk to another person, it's like nothing to them or vice versa Do you know what I mean? So that's why it's all about the person whoever you are and how you deal with things But obviously you don't how to do it now. So what are you worried about? Sure, but yeah, I mean I I do know how to do it because You do Like 80% that's that's really high I know so let me tell you my option will that get you over this mental anxiety Plus knowing all the stuff you're doing and tracking the money you made since the class And the money you would have made if you did all the trades that you didn't do Would that do it for you if you make 50 grand or something crazy? I think that yeah, I think so. I think if I had Because I lost so much You know, I think if I had A cushion yeah, I think that would make it easier to push the bottom I can see myself getting over it Either it's with time Or a big trade like the spy trade you'll get over it because again, you know that you can do it It's a matter of convincing that you know that you can do it You either convince yourself, you know, you can do it as time goes on because the longer the time goes on Do you realize you can do it the more you just know that you can and nobody has to tell you that you just know it You just know it inside in your heart that I can do this thing. It doesn't matter if melissa Goes to wherever I know I can do it without her But the other thing is if you have the money there as a cushion That's like a safety net too I think you're gonna have a good year because it's still very very early in the year You got this great trade going on your upper ready Like you said you can sell it today and make three times the amount That would be a little cushion. It would be a little more cushion You have before an extra couple thousand dollars like the stx or wc or whatever the ones are Are the spy then it just it helps your conviction It helps your commitment that you that what I taught you works And then also that you can see it yourself in the way that I'm seeing it to do it. Yeah Yeah, yeah, like today on the hans That was a gap up. Yeah, and right when it opened, um, I just knew it was gonna work What about that? Oh, let me ask you that really quickly when I say I don't like anything and it doesn't meet the criteria Do you do something that's like a kamikaze or are like doesn't rate that good or do you do things on your own? What do you do? I do things on my own. So What I started doing recently is I started looking at the charts, um, like doing homework like after The market closes. Yeah, I'm trying to look at it like 30 minutes or nothing And then some things you can just see it in the chart and it's going to follow through and you know keep going down So I just look at those and if they set up then I just short those Oh, okay As a swing trade you mean or day trade? Why the day trade? Because even if it doesn't get um some things on the chart, it's just looks like it's gonna fall Yes, I know Yeah, so I would just look at those and um, yeah, so I Yeah, so there's nothing to do that. I would just look for something. I would just do something that was on my list Yeah, thank you so much for for talking to me today. This was fantastic You can do without me and you know what I mean Yeah, but you know, I want to say though that um See I started I study now on my own but Everything that that you um, you know teach It's um, it's not true Is why wait, what did you say? What did you say I cut off there? What did you say?   I think I was I would understand that the best thing that I've done in my training was um, You know trading with you You know trade with someone Yeah, because there's a lot of people that are you just can't really trust them.  It's just uh, you give this kind of vibe and it's very positive. I would say Well, I mean the brain I never take a trade thinking I'm gonna lose of course I said my says my wrist But like this fly trade is a good trade like look that trade is gonna work out and that's like look at it And when I took it and after I took it the market fell and then I stayed with the train And I could have killed it with a partial loss at like any point in January and then And then they flatline those options But it's just like when I take a trade doesn't mean that some trades don't work some trades don't work That's part of the business But it's the point that yes, I myself believe that it's going to work if I take the train And you believe it's going to work too because you're putting on money on the line Well, it's a hundred dollars or fifteen hundred dollars. It's like a waste if you don't think it's going to work Why would you even take it? You know, but I've been trading my system for years that I just really really believe it and I know that it works And and every time I talk to somebody new like talking to you today This helps my conviction. This helps my conviction.  It's like I don't even know you and I just I'm talking to you now and you're somebody like on the planet And you did the class a couple months ago, but it's the point that That you found mine and you did the class and now you're making money because you took my class I've helped you which is a good feeling that I honestly got I mean I'd love you to make a half a million dollars in that spy trade But I think if you're at 50 grand you gotta get out of half of it But I mean I would love you to make a million dollars and hold the whole thing But it's too risky to hold it past being up a lot of money. I mean really really still could make like a hundred grand I don't know. We'll see how we'll see what we head up over the high and we'll look at it But I know you're gonna make a lot of money on that trade and and that's what's so great And you would have kept losing probably for six more months until you figure something out or take another class Or maybe you would have quit because are you wouldn't have been able to keep going and you would have been hit hard And said I can't do this thing anymore. I was just one day. I was just watching video and then I was like, oh, I liked it Was it about gaps or was it about the market? Like Your webinar and then you know, I would watch I think that went on for like two to three months Okay, and then I found new week I think what it was that I lost so much money obviously actually for myself Really?  Yeah I try to figure it out by myself You know, which is fine.  Right. And so I already knew About the app before taking your class the class I was very Like I was really looking forward to it, you know, because I was like You know, I really could know what you're doing And uh, yeah, so I took the class it's so helpful I I just I learned, you know, so much like and um And I I took it Yeah, um the next two weeks I took it twice. You know, I didn't take the first day, but I took the second day. Okay. Yeah Then by then, you know, I think everything like I felt like I really got it.  You really haven't been trading for that many years So you took your head to the beginning Just too quick But a lot of people a lot of people do you're you're lucky that you did or you might not have been able to carry through Take the class and keep trading.  Yeah I think I could have wasted a lot of money taking like crappy stuff, you know classes where they teach that indicator and stuff Yeah You don't do that. Yeah, my charts are really clean I mean, I don't know if you have your charts just like mine or not Do you have your charts just like mine or do you have other stuff on there you use or I'm using It's just like you work. Okay. Good. Yeah. Yeah Yeah, I'm so glad I, um, I I found you because that's another thing Could I could I read these stories about people saying that, you know, they wasted so much money taking All these classes, but I don't have that experience, you know I'm the only class that I take in is your class And Yeah, you never took it.  So I read a lot and so But I do it by myself So I was like, if I'm gonna take somebody's class, I'm gonna take it Great. I'm so glad You know very intelligent people It's like it's like a mystery until you figure it out But I think the one good thing I did is that I honed in on just this one thing Which was the gaps But I'm telling you that is That's how I call the market like because I was reading the bearish gaps in the market Not seeing them to be weak enough to break it and then I was reading the bullish gaps So that's how I was reading it. So ultimately whatever you choose to do Learning the gaps can help you with everything because it is about reading what the institutions are doing and that's what happens at the gaps Yeah, and the thing that really helped me was um, also when um, I also took your trends class Yeah, that's right. You did you did. Yeah and then um This is what you said and I asked what you said, um find a follow If it's once you know it, you know, it sounds intuitive, but unless you actually Someone says it, you don't know it, you know, and this is what you Have made everything like come together. You said it's just such a simple statement.  You know, and and so see that's just a simple thing But no one knows it because they don't you know if they just see it as a gap You know, they don't see yeah, they're living in a plastic this and I'm looking at like everything. Yeah. Yeah Um, so that's helped me tremendously, you know, just seeing the picture. You're just just just context You know because before I mean, um, just the uh Just the one minute chart, right? Can't read the market like that because you have to look at it. You have to step back. Yes Yeah, so that's pretty yes. So you put everything in context, you know, so It just makes perfect sense It's all um kind of You know logical, you know, thank you Yeah, you're a good teacher, you know So yeah, I just I don't know I'm I do I believe in god, you know, and so I just think that You know, god didn't want me to fail so You know, I I always find me and take my class are meant to find me because I literally just started the business I don't know the videos on youtube like when I started it, you know back at the end of 2012 and No one know who I was was and a lot of people don't know who I am now I mean, I have more of a following now that I ever did But I mean I didn't even get the website done and now the website really doesn't even say everything that I do Enough about the market. It's more about me and that has to be redone again I mean, there's so many things and you say how is people finding me that People that find me are meant to find me because like you said, there's so much to choose out there How do you know to go to this person and that person? You want to go to a bigger company than mine because it's really just me and now I've hired paul But it's the point that I'm just one person That's just doing it But what I know is like amazing but it's because I I did a lot of work and figured it out myself and and I just never thought I'd be teaching people I mean, I just never in my life thought I'd be talking or teaching someone like you to make a difference So I do believe like fate or whatever it is and I feel like that the people and that's why I really want people to make it I want people to make it and I want to help them and I want them to make money And you're doing that is above and beyond You know the price of the class or anything else. I've taught you something you can use to learn For the rest of your life Definitely But we're gonna do this again because you were so great and I want an update Of where you're at with everything.  I think it'll be good for you. Do you know what I mean? A big love of studying The other ones like I came out with this options letter like I've been studying them. There'll be other ones I'll make other crazy calls. I was you know what I mean? It's about seeing it far out and I was I was I was able to see this far out I've never anticipated we'd fall like we did when I took it myself in december But I'll let because I saw the money in there and the money didn't leave Even though we dropped it really didn't leave. Do you know what I'm saying? Yeah Yes, just like you said about the netflix Yeah, and the google is to say that chart study that chart. There's something there in that one too Okay, and we could talk about that in the room this week in fact remind me I'll talk about the google very similar very similar to the thing in the netflix And and and you just remember you said that we could talk about it in the room this week Okay, I'd like to meet you someday Okay. All right. Okay. Have a good night


This video is brought to you by Incogny. Go to the link in the description to get 60% off an annual plan. There's been a question lingering in the back of my head for the past few months. It's not exactly a novel question. In fact, it's one that I've asked myself on and off for years. It's one that a lot of music fans have asked and a lot of the music press have asked. That question is, what is the greatest song ever made? In my decades listening to and writing about music, my answer to this has fluctuated as much as my tastes. At various times in my life, I have boldly proclaimed like a Rolling Stone, Scarborough Fair Canticle, Under Pressure, and a half dozen other songs as the definitive greatest song ever made. These days my answer tends to gravitate toward Curtis Mayfield's Move On Up, but ask me again in a few years and I'm sure that will change. The question of what the greatest song is is a moving target. Every year thousands of new songs are released and every year thousands of old songs find new life in an ever-changing culture. So rather than try to answer this question outright, I've decided to come at it from another angle. Over the past few weeks, I roped in my trusty assistant Matt and sent him digging through every music publication we could find that has asked what the greatest song is. The result is a collection of 27 different songs declared the single greatest by 32 different organizations or blogs. By looking at this data, I'm hoping that we can come to a better understanding of what we as a culture value in a song, and just maybe we'll be able to add a bit of clarity to that eternal, unanswerable question. Let's take a closer look. Before we get our hands dirty with this dataset, I want to note a couple of things. The easiest way to find this data was through the internet. This potentially cut off older publications if they hadn't been scanned and almost certainly leaves dozens of lists behind. The oldest list we pulled was NME's 1976 list, Top Singles of All Time, while the newest are a number of lists released this very year and a few content aggregate sites that are sort of always updating. Also, we are a pair of English speakers in Canada with nearly passable French, so most of the sources we had access to were English language and all of them were either European or North American. That alone puts a huge bias on this dataset, but that Western bias is also a reflection of broader trends within the history of popular music. And finally, not all these lists are explicitly labeled as the greatest song. Some are most iconic or top single, but for our purposes, I think we can all just agree that they're pretty much saying the same thing. So with these caveats in mind, let's do a little tour of the list. Three songs topped on at least three different lists. Bohemian Rhapsody and Lyco Rolling Stone each appeared three times, while Smells Like Teen Spirit topped them all with four different appearances. So if you go by the numbers, the answer to what the greatest song is might be Smells Like Teen Spirit. None of these songs seemed particularly surprising to me. While they're all quite different aesthetically, each of them is an enormous cultural touchstone. Both Lyco Rolling Stone and Smells Like Teen Spirit were landmark recordings in their day, drawing attention and controversy, and leading to drastic shifts in the music industry. Both were also written and performed by artists who would be dubbed the voice of their generation. Bohemian Rhapsody, on the other hand, is a bit of an otter case. It was celebrated in its day and cracked the Billboard Top 10, but it really blew up when the cult classic Wayne's World used it for the iconic headbanging sequence. Since then, the song's cultural impact has continued to grow as new generations take it on. And the slow burn influence of Bohemian Rhapsody is reflected in the publications that have called it the greatest song. All three of the lists that had Bo-Rap at the top have come out in the last two years. I don't think many people would historically argue that Bohemian Rhapsody wasn't a good or important song, but the place it holds in the collective consciousness right now is a lot more of a modern phenomenon. That's probably due to things like the Bohemian Rhapsody biopic and a reflection that happens as songs age through the filter of time. As a lot of these older artists have reached the twilight of their career, or in the case of Freddie Mercury, passed tragically, we as a culture have taken closer looks at some of their works. It's also a reflection of a changing political culture. As LGBT plus rights have advanced, Freddie Mercury has become a modern queer icon, so audiences have viewed his work in a new light. By the same measure, Aretha Franklin's feminist anthem Respect has been resurfacing in the discourse following the Me Too and Black Lives Matter movements. In the 2021 edition of Rolling Stones' 500 Greatest Songs of All Time, Respect took the number one spot, booting like a Rolling Stone down to number four. Respect is one of a number of protest songs proclaimed the greatest. It's joined by tunes ranging from the melancholic utopia of Imagine to the raging storm of Anarchy in the UK. And I think that this speaks to something that we all want to see in music. We really do want to believe art can change the world, and that affects the way that we evaluate songs. One protest song that did truly contribute to world change topped multiple lists. Billie Holiday's Strange Fruit, a song that sometimes gets credit for kicking off the civil rights movement, was declared number one by Time Magazine in 1999 and by Time Out in 2015. Strange Fruit, getting the nod from a prestigious organization like Time, is a sign of an organization that puts more weight on the historical impact of songs. But plenty of lists also choose songs that have musical influence or virtuosic playing. One song to top two lists, perhaps unsurprisingly, was Led Zeppelin's Stairway to Heaven. What might be a bit more surprising about that is that both of these list tops are far more recent. Stairway currently sits at the top of the fan ranking site, Ranker, which might reflect the power of Zeppelin's enduring fan base. And the other topper was from what I think is a French song ranking blog. Both of these show that even as the world is reckoning with Zeppelin's complicated legacy, the band's rock god persona persists. The last song to have multiple list tops was Joy Division's Love Will Tear Us Apart, which saw one of the widest spreads between its tops, copying a 2002 NME list and a 2014 Music Express list. That song hits on one of the most common topics found throughout the lists, love, and especially heartbreak. Far and away, the largest proportion of the songs that topped lists are About Love. We've got everything from Elvis's Suspicious Minds, to heard it through the grapevine, all the way to the weekend's Blinding Lights. It's no secret that humans love talking about love, and the abstract emotionality of music as a form lends itself so well to love songs. There's such a rich history of artists pouring their heartbreak into song, and that simple universal human experience can clearly spawn greatness. Even to this day, so many hit songs are about love and heartbreak, so don't be surprised if you see a Taylor Swift song top one of these lists in a few years. The remaining songs in the lists run the gamut in lyrical content, from the abstraction of David Bowie's Life on Mars, to feel-good dance songs like Johnny B. Good and the Twist, to the surreal paranoia of Michael Jackson's Billie Jean. The oldest songs that sat on the top of lists were Strange Fruit, and Judy Garland's 1939 Over the Rainbow. Over the Rainbow also holds the distinction of being performed by the youngest artist. Garland was just 17 years old when she recorded Over the Rainbow, a full two years younger than our next youngest in Chubby Checker. On the whole, nearly every song represented in this dataset was sung by somebody who was young. In the entire list, only five were recorded by people older than 30, and the only song performed by an artist over 35 was Leonard Cohen's Hallelujah. This skewed age is a reflection of the popular music industry of the 20th and 21st century. Pop music has always been a young person's game, with labels eager to sign talent that will appeal to teen markets, and the grueling schedule of touring making it harder to keep up as artists age. This is also just a reflection of a culture that puts undue value on youth, and chews out most artists as soon as their backs start to ache. This youthful skew ties in with another huge bias present in these lists. More than half of all these songs are rock. The next most represented in the list are Soul and Pop, with a handful of other genres getting spotlight. There's a number of genres not present at all, including dance music, classical, country, and even rap is barely mentioned. Despite the fact that hip-hop is half-century old, and has been the dominant music for over 20 years, only one song appearing on the list could be considered hip-hop, Beyoncé's Crazy in Love. These biases are a reflection of a music press that was birthed out of the 60s rock era. There definitely were publications writing about music before, but this sort of culture is born out of music magazines like Rolling Stone and Cream, and those magazines have a long legacy of rock bias. These biases are slowly changing, but it takes time for things to catch up. Most songs need to gestate and accrue a certain level of prestige before they're topped on these lists. Almost all the songs in our set were written and recorded decades before the list publication, but there are a few notable exceptions. Mr. Brightside topped an XFM listener poll just six years after its release, and Unfinished Sympathy topped a similar poll by BBC seven years after its release. It's notable that both of these songs are from listener polls that pulled from a wider audience. This could suggest that broad listeners are less biased toward the old stuff and quicker to recognize greatness than an established music press, but it could also just be recency bias. Really, with a sample size this small, it can be hard to draw meaningful conclusions. But there are a few objective data points that we can pull from these songs. Nearly all of them are in 4-4 time, most of them are in a major scale, most range between 3-5 minutes, with the shortest being yesterday at a hair over 2 minutes, and the longest being Stairway to Heaven's 8 minutes. But there's not really much meaning to be found in these numbers. There are some trends that do tell us important information, though. Nearly every one of the songs on this list was a commercial success. Most of the artists named have sold millions of records worldwide, with four of the five best-selling artists in music history making appearances. The Beatles, who have been certified for nearly 300 million sales worldwide, are one of the only artists to appear on the list with two different songs. They're joined in that by Aretha Franklin, who has two votes for respect, and one for, I say, a little prayer. And this reality brings up a certain chicken or egg situation. Are these artists great because they have sold? Or do these artists sell because they're great? In my mind, I think it's a bit of both. I do truly believe that great art taps into something universal in the human spirit that people latch onto. So it's not surprising to me that a lot of great art is popular. But I also think that our perceptions of greatness are deeply, deeply impacted by the media we consume, by the stories we read, by the documentation of these artists' lives. Just knowing more about these artists, I think, makes a lot of people feel closer to them and feel like their work is greater. And that closeness is reflected in national identity, too. Almost all of the artists named here are either from the UK or the US, with two notable exceptions. Both The Weeknd and Leonard Cohen share my home in the strange cold lands of Canada. I'm sure if you looked at more lists from other countries, more local artists would top with great songs. Because music is fundamentally subjective at its core, and that means what is considered great music will always be a reflection of the culture of whoever is making that declaration. There is no such thing as an objectively great song. Honestly, having dug through all this data, I don't feel any closer to a definitive answer as to what makes a song great or what the greatest song is. But at the same time, just looking through this has been a delightful experience that has let me find weird connections between songs that I love and has encouraged me to see songs that I might not have valued as highly through a new light. And really, I think that's the reason why these lists exist. They're not there to give you definitive truths. They're there to give you a fun and interesting way to interact with the art that you love. The entire point of these declarations is to have you disagree with them, to have you argue them out with your friends and come to your own conclusions. By getting into discussions about the art that we love, we learn more about ourselves and we learn more about the society that we live in. And really, that's the whole point of art. So I don't think there's an easy answer to what makes a song great. And I think the question of what is the greatest song is completely unanswerable. But I hope that this has at least piqued your interest and inspired you to start questioning what your criterion for a great song would be. And if you want to get heated in the comments and talk about the art that we love, I'd love to hear what your list looks like. I don't know about you, but with each passing year, it feels like my inbox has filled with more and more spam. Every other week, I find myself having to clear out junk, getting around filters, and obnoxious offers from things that I've never signed up for. This problem exists because of the industry of data brokers, companies that get their hands on your personal information and sell it to interested parties. Everything from emails and license plate numbers to financial information, and even political beliefs, can be up for sale by these data brokers. And this data can be used for scary things. People use this information for identity theft, mail and wire fraud, and even sell data to companies targeting vulnerable and disadvantaged groups. If that pisses you off as much as it pisses me off, you should check out Incogni. Incogni is a service that reaches out to data brokers on your behalf and sends them removal requests until they comply. You can get started with that today if you go to incogni.com slash polyphonic. If you check out that link, you'll get 60% off an annual plan, and you can start fighting back against data brokers. And signing up with that link is also just a great way of supporting my channel. Thank you so much for watching.


What's going on and welcome to the solo shot. We have a 13 game Slate Deadlocks at 705. My name is Tom Vecchio. This is one of the many shows on the FanDuel podcast network. You can find that anywhere whether it's iTunes, Soundclad, Stitcher, Google Play. Make sure to give that a like, follow or subscribe. That is greatly appreciated and you can follow me on Twitter at DFS underscore Tom. Before we happen to things, listen up baseball fans. The MOB is putting on a wonderful kind of event with the Field of Dreams game this Thursday between the New York Yankees and the Chicago White Sox at his August 12th. FanDuel is giving fans a chance to get in on the action with a $5 Field of Dingers promotion. All you have to do is opt in and place a minimum bet of $25 on a three leg parlay, same game parlay or more for the 2021 Field of Dreams game. You'll receive a $5 bonus in the site credit for each home run hit in that game by both teams. Relive the magic of the Field of Dreams by heading over to FanDuel today. Must be $21 plus and present in Colorado, Iowa, Illinois, Indiana, Michigan, New Jersey, Pennsylvania, Tennessee, Virginia, or West Virginia based on student bonus is issued as a non-double site credit that expires in seven days max bonus $35 term to apply game from call 1-800-522-4700 in Colorado, call 1-800-betts-off in Iowa, call 1-800-9 with it in Indiana, call 1-800-270-7171 in Fort Confidential Health in Michigan, call 1-800-gamber in New Jersey, Pennsylvania, Illinois, Virginia, or call Tennessee Red Line at 1-800-889-9979 in Tennessee, or visit 1-800-gamber.net in West Virginia. All right, hopping into today's 13 game MLB Slate locks at $705, obviously a significantly larger slate than what we had yesterday. Also, on tonight's slate, as we had yesterday, we are dealing with plenty of rain. So starting off, again, this is always via Kevin Roth on Twitter meteorologists doing great work in the DFS industry. We could be having some rain in St. Louis at Pittsburgh. A little bit of rain, neither should impact play too heavily. The Dodgers visiting Philadelphia, also a bit of rain, not expected to be too much, but we'll get an update at 4 p.m. on the Q&A show, which you can find right here on the Fangle YouTube Twitch and Facebook page. Detroit at Baltimore should be rain, a little bit consistently leading up to game, could be a late start. We'll get an update on that. Oakland at Cleveland, not a ton of rain, but the storms in the area will be very slow. Moving in the storm could present a bit of trouble with winds blowing out towards Washington at the New York Mets. Plenty of rain possible this, depending on the timing of how soon it gets there. Tampa Bay at Boston could see things at the tail end, just with the storm moving up the East Coast. Cincinnati at Atlanta also could see a little bit of rain, but should not be an issue. And then the New York Yankees visiting the Kansas City Royals should be rain before first pitch, but ultimately not too much of an issue. As of now, again, we'll circle back on all of this at 4 p.m. because there's a number of games that could be impacted by things. Now, leading off tonight's slate, we have three, I want to say, clear aces on the mound. Max Scherzer, Sean Manaya and Aaron Dola, followed by Sonny Gray. Now, we can say that some of these pitchers all have their positives and negatives. Leading off, we're going to be going with the best pitcher on tonight's slate. And ultimately, that's Max Scherzer coming in with a phenomenal 34.5% strikeout rate this season. 6.4% walk rate is absolutely unbelievable. See a 2.98 Sierra and a 3.43X fit. All phenomenal numbers from Scherzer. He is allowing 1.45 homeruns per nine, but ultimately we're not going to be too worried about that because we know his strikeout ceiling is absolutely immense. Now, this isn't to say the lineup he's going against in the Phillies isn't without danger. We've seen them very strong over the past couple of weeks, but we know his strikeout upside is arguably unmatched on this slate. All things considered. So at $10,600 going up against the Philadelphia Phillies, Max Scherzer is clearly the best pitcher on tonight's slate. Now, we also could be looking to someone like Sean Manaya, but that game could be impacted by weather. And frankly, he doesn't carry that high of a strikeout rate in comparison to Max Scherzer. Again, Scherzer is at 34.5%. Manaya is at 26.9%. And there are only $600 difference. So there's really no reason you'd be going to Manaya over Scherzer in really any capacity. Now, Aaron Nola is just a bit cheaper compared to Max Scherzer. Nola coming in at $9,900, but the matchup for him is no doubt a tough one going up against the Dodgers. But he also could say the same thing for Sonny Gray, who we know has a good strikeout upside and he's $9,200, but he's on the road going up against an obese dangerous Atlanta Braves team. So this leads us to Logan Gilbert at $8,900 as my second favorite pitching option on tonight's slate. A young pitcher for Seattle only has 67.1 innings pitched this season, which is his first year in the majors, but has a very solid 28.2% strikeout rate coming with a 6.4% walk rate. He's allowing a 43.4% fly ball rate, which we'd like to see a little bit lower, but he does combine that with a strong 55.9% medium contact rate, add in a 3.58 Sierra and a 3.87 XP, and we are looking at solid numbers overall from Logan Gilbert. Despite all those fly balls, he's only allowing 0.94 home runs per nine. Now, more importantly, he's going up against the Texas Rangers, and we see Logan Gilbert at home for Seattle. So obviously a great pitchers park there. Going up against the Texas Rangers, obviously a very depleted offense wasn't that strong. To begin with, they come on a league average or so, 23.9% strikeout rate versus right-handed pitching, which is the 15th in the league. We look to their WRC Plus, and they come into the 78 WRC Plus with their current roster that is 29th in the league. Absolutely not an offense. You need to be worried about combine that with the fact that they have a 140 team ISO versus righties with their current roster that is 27th in the league. So a Texas Rangers offense that wasn't great to begin with is even worse over the past few weeks. And now we see Logan Gilbert at $8,900, presenting a great point per dollar value, along with a solid 28% strikeout rate at home, again in Seattle, which is a great pitchers park. Logan Gilbert really shaping up to be one of my favorite pitchers on tonight's slide. Now ultimately, I'll still side with Scherzer as a better overall option. We do see Scherzer going much deeper into the games. We do see Logan Gilbert limited in terms of his pitch count and not going as deep into the games at times. So we want to be taking him about a half a step or full step behind Scherzer, who we know is the more consistent option. Again, you are paying $10.6 to get to Scherzer. Logan Gilbert is $8.9, obviously making roster construction that much easier tonight. Now, I assume plenty of people will have plenty of questions about a number of other pitchers throughout the slate. And throughout the day, I can handle those at the 4pm show here on the Fandle YouTube, Twitch and Facebook page. Plenty of different options to go to on, of course, a 13 game slate. But Eduardo Rodriguez for the Boston Red Sox is a pitcher I want to focus in on today. Now, I know the middle portion of the season for him was very rough. We saw him start off the season strong. He went through a big downturn in terms of his production and he's since picked it back up. He still comes in with a very strong 28.9% strikeout rate, 7% walk rate. The 1.20 home runs per nine obviously isn't great, but he is mainly a ground ball and medium contact pitcher that 42.9% ground ball rate, a 54.7% medium contact rate, a 3.49 Sierra and a 3.30 exit, which of course are both great. He's going up against the Tampa Bay Rays. And yes, this is a positive park shift for the Rays because they are in Boston tonight. But Tampa Bay still comes in with a 25.3% strikeout rate versus lefties, which is the fifth worst in the league with their current roster now. They do generate a lot of walks. They do have a bit of power in that lineup and they do come in with a slightly above league average 101 WRC plus versus lefties, but ultimately they're still striking out a lot. And the strikeout upside for Eduardo Rodriguez is there considering he's only $8,000. He also makes another solid point per dollar play at pitching. Now we look to some of his start, Eduardo Rodriguez, some of his starts since the All-Star break or since the start of July and outside of this one start against the Yankees where he literally only pitched one inning left with a shoulder or back issue. We don't want to be looking at that. He posted a 47.6% strikeout rate in his most recent start against Detroit. He posted a 38.1% strikeout rate against Toronto, a 38.1% strikeout rate against the Yankees and a 28.6% strikeout rate against Oakland at the beginning of July. So he has been very, very solid since the beginning of July, of course, for moving this one game where he only pitched one inning against the Yankees. Very solid numbers from Eduardo Rodriguez overall and ultimately the match of him against Tampa Bay is shaping up to be one where he could really reach another ceiling game when it comes to his strikeouts. So Max Scherzer absolutely fantastic as always on tonight's late. Logan Gilbert at $8,900 at home, integrate pitchers park against a very, very weak Texas Rangers line. If we want to be looking at Logan Gilbert as one of the most, I would say consistent and safest options for his salary that we have on tonight's late. And then dropping down a little bit further, Eduardo Rodriguez. Now, this isn't to say I'm not considering other pitchers on tonight's late, but those are the three main ones that I'm going to be focusing in on. Now, when it comes to stacks on tonight's late, there are obviously a number of different ways to go about things. As of now, we see six teams with implied run totals sitting over five, the Yankees, the White Sox, the Orioles and the Tigers, they're going head to head. That game could present a spot for a bit of a game stack, the athletics and then the Mets. Those are the 16 as of now that are sitting with implied run totals sitting over five. Now, of course, we'll want to drop down and take some teams in the 4.7 4.8 range just to differentiate our lineups a bit. Starting off, we want to be looking at the Oakland athletics going up against Tristan Mackenzie. Again, we see the athletics with a 5.20 implied run total tonight, which is very solid.  Again, this is one of the games that could be impacted by weather, so we'll certainly have to circle back on this on the 4pm Q&A. But for Tristan Mackenzie, allowing 2.61 home runs per nine to righties, a 13.3% walk rate to righties is absolutely terrible. He's allowing 1.11 home runs per 9 to lefties and a 16.6% walk rate to lefties. He has a 5.29x fit against lefties and a 4.74x fit against righties. None of these are good numbers. He allows a 55.6% fly ball rate to righties and a 46.3% fly ball rate to lefties. All of this is very, very troubling, especially in a spot where we could be, if this game does play, if we do see some extra wind blowing out in Cleveland. So, yes, the Oakland Athletics are a team we want to be targeting tonight. Looking over the top, they have plenty of power, whether it be Seth Brown, the 251 iso in this split. Matt Olson, the 242 iso in this split. Sean Murphy, 200 iso, Jed Lowery, 174, and even Mark Hanna at 170. So, the Athletics present plenty of options when it comes to stacking tonight. And ultimately, they are relatively affordable to get into your lineups. You know, outside of Matt Olson, who's above $4,000, sitting at $4,300, the newly acquired Starling Marte at $39, after those two, it's relatively affordable to roster multiple Athletics or a full Athletic stack, whether it's Hanna at $33, Matt Chapman even at $3,200, Jed Lowery at $3,000. You name it, there are multiple different ways to go about stacking the Athletics tonight. You can even drop down further. And if Sean Murphy makes the lineup over Jan Gohms, we get some real value at $2,400. So, the Athletics are certainly a team I'm targeting tonight for multiple reasons. One, they offer everything we want when it comes to stacking. You can decide to pay up for the top. You can drop down to mid-range and take some value. And ultimately, they have a great match up against Tristan Mackenzie. So, yes, the strikeouts are always going to be there for Tristan Mackenzie, but too many walks and too many home runs are a dangerous combination to be playing with. So, Mackenzie is a pitcher that I'm going to be looking to stack against tonight. Another pitcher I want to be stacking against tonight is Drew Smiley from the Atlanta Braves, a pitcher that's also giving up too many home runs this season, sitting at 1.78 overall. He has a low 20.4 percent strikeout rate, an average to slightly bad walk rate sitting at 8.4 percent. He has a 42.6 percent fly ball rate, a 36.9 percent hard contact rate, a 4.68 Sierra, and a 4.80 X fit. We look to some of his individual splits versus righties and lefties. He's actually struggling a bit more against lefty hitters despite being a left-handed pitcher, allowing 2.10 home runs per nine to lefties and 1.66 versus righties. So, ultimately, it doesn't really matter who we attack him with. We do see plenty of power on the side of the Cincinnati Reds. We'll get there in a minute. And his fly ball rate is generally the same versus both lefties and righties, 45.8 percent against lefties and 41.5 percent against righties. He's at home in Atlanta, which is a solid hitters park. It's not amazing. It's not terrible. It's slightly better than league average, but we still want to be looking to the Reds with all of their power. And the Reds come in with a 4.77 applied run total slightly below the top, which means that there's a chance they could be going slightly under the radar, which, of course, is great for tournaments. We'll circle back on all of this when we get to the 4 p.m. show. But Kyle Farmer leading the way with a 254 ISO for the Reds, obviously great to see. Nick Castellanos with a 236 ISO in this split. We can even look to Eugenio Suarez at 172. Joey Vado obviously has a smaller sample size because he's spent so much time on the IL. But of course, a player we can certainly add to the Reds stack overall. Jesse Winker, a phenomenal hitter this year, does not have a whole lot of power versus lefties specifically. He's actually down at .081. But if they were to bring in some righties from the Braves bullpen, obviously things would flip in Winker's favor. And of course, then we get some potential upside for Joey Vado as well. So the Reds with a 4.77 implied run total just below the top tier of teams tonight is another team that I am really, really focusing in on stacking. Because as we've seen specifically over the past few days of the weekend, when the home runs get going for the Reds, they are one of the teams that you absolutely want to be having as stacks in your player and team allocation just because the home run upside for them is absolutely immense. It seems like the Reds and the Braves are these teams when the home runs get going. We are really in a spot to see plenty of scoring. Now, this isn't to say that I don't like the Yankees on tonight's slate. I don't like the White Sox on tonight's slate after all the runs that those two teams put up last night. I'm fully on board with stacking those two teams. I think they're absolutely phenomenal. Again, I'll give more details on the 4 p.m. show. But also looking to the Detroit Tigers side with their 5.25 implied run total right now that's tied for the third highest on the slate. They're in Baltimore, which is of course a great hitters part. They're taking on Keegan Akin for the Baltimore Orioles. Now, Akin is another young pitcher doesn't have the largest sample size this year or last year, only coming with a total of 77.1 innings pitched between the last two seasons in the majors. But he has a low 19.7% strikeout rate, 8.4% walk rate giving up a 39.8% fly ball rate. None of this is terrible. None of this is amazing, but he's giving up too many home runs overall. And yes, the Tigers, a team that we should be looking to for some potential scoring tonight. Yes, the Tigers might not be the best team in the league, but they certainly have plenty of power. And more importantly, they're facing a very weak pitcher in a very hitter friendly part. So, looking to Eric Haas with his 402 iso versus lefties is absolutely great tonight. Jonathan Scope at 263. Even Robbie Grossman at a 226 iso is someone you can be considering. You want to take a shot with Miguel Cabrera. That's certainly an option as well. Akil Badu is not a player I'm necessarily targeting at the start tonight for the Tigers because the lefty-lefty match is so difficult for him. But ultimately, if I'm going to be targeting the Tigers tonight, I'm not going to be too worried about either A, Keegan-Akin, or B if he gets run out of the game because the Tigers put up a whole lot of runs. I'm not going to be worried about the Orioles bullpen. So, Akil Badu is a player that I want in some Detroit stacks. He's just not the player that I'm starting the stacks with.  So, all of those players are certainly in play tonight. And yes, they do have a 5.25 implied run total. So, the Tigers could be a chalky team on a 13 game slate just because their match begins with Keegan-Akin. And ultimately, the Orioles bullpen is just going to be so good. So, the Athletics tonight, the Tigers tonight, and the Cincinnati Reds tonight are three of the teams that I'm focusing on a little bit heavier than compared to some of the others. Again, I still want exposure to the Yankees and the White Sacks. And even the Orioles on the other side of the Tigers because the Orioles are going up against Casey Meis, a young pitcher for the former number one overall pick from the Tigers who's still giving up too many homeruns this season. And a pitcher we can certainly look to attack. So, we are looking at a slate where we should be seeing plenty of offense, that there are plenty of teams in great spots going up against bad pitchers which should present plenty of upside for stacking. Now, when it comes to the final three things on tonight's slate, an extra pitcher, an extra stack, and then a homerun call. Of course, we can recap all of this on the 4 p.m. show. We'll give one homerun call now. I'll give one homerun call later. Starting off with the pitching option, or the another pitching option to consider saying would be Alex Wood, $8,600 at home for the San Francisco Giants. Now, two of these most recent starts have not looked great for him. Giving up four earned runs at Arizona on the team he's facing tonight and then four earned runs against Houston. Yes, he's facing the same Arizona team he did in this most recent start, but still Alex Wood, a good overall pitcher, not bringing in the highest strikeout rate. Ultimately, that's not necessarily why we want to be targeting. He comes in $8,600. I think he makes a solid point per dollar play. I think he's going to be a nice pivot away from Logan Gilbert since they are at a very similar salary. So, yes, we can be going to Alex Wood with his 25.1% strikeout rate, which is certainly solid, his 3.77 Sierra and 3.68. Exit all solid numbers from him overall. Yes, one bad game against Arizona is not the greatest, but overall Arizona is still a weaker lineup. And I think we can be looking to Alex Wood as a solid at tournament pivot away from Logan Gilbert who should just be much chalkier going up against the Texas Rangers at an only $300 difference. So, overall, we are looking to be in a good spot for pitching. Multiple options at every different price point allows some natural pivots, allows you to certainly change things when it comes to your roster construction in the hopes of being different, which is always good to see. Now, when it comes to another team, we'll be stacking on tonight's plate. Again, like I said, you can go to both the Orioles and the Tigers. I think that they're both firmly in play liking that as a bit of a game stack. The athletics, the Reds are to the main teams. I'm targeting along with the Tigers. And again, the Tigers make a lot of sense just because ultimately they offer a bit of salary relief, which we'll need if we want to pay up for pitching or be pay up for potentially expensive Red stack. So, I'm also on board with that. And then I also think that you can be looking to go to the Seattle Mariners tonight, attacking Kobe Allard, a pitcher that we truly don't need to be afraid of going to both Logan Gilbert and a stack from the Mariners tonight is something that we should be considering. Kobe Allard is allowing 1.65 homeruns per nine overall this season. A 21% striker rate is absolutely nothing we need to be too afraid of. He's not walking a ton of haters, which is actually, I guess, good to see for him with a 5.2% walk rate, but ultimately not a pitcher when you be truly worried about a 39.9% fly ball rate is something that is, you know, right on the edge of presenting plenty of upside for the Mariners hitters. So, I'll dive into the Mariners a bit more on at the 4pm show, you know, targeting, whether it's Mitch Hanniger, even Kyle Seger in a lefty-lefty matchup for Seattle is solid. Mariners aren't that expensive overall. You want to add in some Thai friends, Abraham Toro, who's been hot for the Mariners as of late, all certainly viable. And ultimately, I don't think the Mariners with their run total singing at 4.68 should be too popular tonight, and they are heavy home favorites alongside Logan Gilbert, who is pitching. So, plenty of options on tonight's plate. We have plenty of chalky options. We have some aces on the mound with pitchers in the mid-tier, basically everything that we want. The clear opposite of what we had on a small, what turns out to be three-game slate last night after the Brewers and the Cubs were postponed. So, certainly looking at Alex Wood tonight, I think it's going to be a good rebound spot for him going up against Arizona, like in Seattle as a bit of a secondary stack tonight. And then the first home run call on tonight's slate is going to be Nick Castellanos for the Cincinnati Reds, again, going up against Drew Smiley, allowing a 41.5% fly ball rate this season to right-handed hitters. 1.66 home runs per 9 to righties this year, numbers that we absolutely want to be taking advantage of. And Nick Castellanos, of course, a great power hitter this season, coming in with a 2.36 ISO versus lefties, obviously something that he's shown in plenty of years past. He has a 22.7% home run fly ball ratio versus lefties and a 47.1% hard contact rate versus left-handed pitchers. So, the home run upside for not only Castellanos, but plenty of the other Reds players is something we absolutely want to be capturing within our lineups and within a Red stack tonight. So, Nick Castellanos is my first home run call on tonight's slate. We'll go for the second one on the 4pm show today on the Fingal, YouTube, Twitch, and Facebook page. I will take all of your questions there and we will run through the updates, not only for the starting lineups, some extra pitchers, some extra stacks, but more importantly, the weather on tonight's slate because we have, was it four, five, six games that could be impacted by weather, something we actually want to focus in on, don't want to get left with some dead players in our lineups. Alright, so that does it for today's podcast. It's always going to be found on iTunes, Samclad, state your Google play. Make sure to give it a like, follow, or subscribe. You can follow me on Twitter at DFS underscore Tom. Until next time, good luck in your contests.


Prince Charles III will be crowned King today. In a solemn Christian ceremony, steeped in 1,000 years of history and tradition, but adapted to reflect 21st century Britain, Saint Edward's crown, a solid gold, sacred symbol of the monarch's authority, used only once, and the arena will be placed on Charles's head. Charles 74 has been King since the death of his mother, Queen Elizabeth II, in September last year, after seven decades as her apparent. The coronation is the first of a King since 1937, only the second to be televised, and the first in colour and streamed online. The ceremony will also reflect him as the supreme governor of the Church of England. I am willing. I, Charles, do solemnly and sincerely, in the presence of God, profess, testify, and declare that I am a faithful Protestant, that I will according to the true intent of the enactments which secure the Protestant succession to the throne, uphold and maintain the said enactments to the best of my powers according to law. Meanwhile, singers, lineup, Ricci and Kitty Perry and US politician John Kerry were among the international guests arriving at London's Westminster Abbey on Saturday ahead of the crowning of Britain's King Charles III. Also present to watch the coronation are British actors in Emma Thompson and her husband Greg Wise. Charles 74 and his wife Camilla will be crowned in a glittering but solemn religious ceremony, with traditions dating back some 1,000 years. It will be followed by a procession resplendent with pomp and pageantry. Hello, hope you enjoyed the news. Please do subscribe to our YouTube channel and don't forget to hit the notification button so you get notified about fresh news updates.


Well, Colchester's win at the weekend was their first in seven matches. They take on a Bradford City side tonight, who are looking for a fourth away win of the season, having lost the last two games and have won the previous two. Back to goal, well played, Morrison. And here he is again. This is good football from Colchester and Sotheby. Very end product from Sears on the road since victory of the NK Dons back in November. Bradford City in a chant here. And that's a good save from Walker. The make of this corner opportunity, Bradford. And the header is in. Could it see it? James Hansen with a bullet of a header. Meeting Dolan's corner. Fifty minutes, Bradford City leads. Deflection on the cross. And a chance for two. And Walker down to his right to deny McLean. Dixon doesn't have too long on the ball. Squared across McLean, this for two. And he's missed it. He scored four goals in the last seven games, Colchester. They're a goal down here. And made that two. From the tightest of angles. Bennett has slammed it in. So really poor defending from Colchester. And they've been punished. Beating Walker in his near post. Masses free kick. Touchdown. And is this to be Colchester's moment? No, McLaughlin holds on. It's all over. For Parkinson's man, we'll go back to Yorkshire with all three points in the bag. Two nil winners.


So does a designer need to have some special qualities to be a good collaborator? I am so glad you asked. I like to highlight 10 principles that can help you build high-performance teams. In fact, these 10 principles are part of your course assignment for this fortnight, so you will be applying them while you work. For now, we'll just run through them to get a basic sense. So let's say you have a project with a specific design goal or outcome and you have managed to put together an appropriate team with the required skills, a team of, say, let's five members. We're going to look at our 10 principles now. We might call them best practices or we could refer them as rules of thumb. Today, collaborations and interactions have moved online. Team members can see each other's work and are expected to respond with rich interactions, critical inquiry and clear communication as part of their online collaboration. So the first principle is using online collaborative tools. There are several popular online collaboration tools available. These include Slack, IBM Lotus Connections, Front, Quip or the Pulse. Are these very expensive? Some are proprietary. Others, like Slack, are based on free and open source software and cost nothing at all. The choice depends on what you need to use it for. You can look up articles on the net that compare different choices, decide on the features you need and select one that is offered by a trusted provider. The second principle directs members to begin by sharing their individual strengths. They identify who will need help, of what sort and from whom and on what aspects of the task. Here is an easy way to find out individual strengths and challenges. Examine this matrix. While filling in four quadrants, the team members will discover what one likes to do and does well, what one does not like to do but does well, what each person likes to do but does not do well and what each person does not like to do and does not do well. That seems to cover all the possible preferences. Yes, jot down at least five things in each quadrant. After each member fills in the quadrants, compare them and list the strengths and challenges of each member of the team. It becomes very clear which member loves doing something and does it well. But more importantly, tasks a person does not like to do or does not do well are also very evident. If I may add, we need to grapple with this question. How will we as individuals and as a team hold ourselves accountable for deadlines, shared results and overall quality? The third principle is speak the language of commitment. Have a thorough discussion about the meaning of teamwork. Teams often fail when members don't pull their weight when they are not accountable and don't really collaborate at all. This is what Lee Colin, a leadership consultant says. Accountability means answering or accounting for your actions and results. Accountability is like rain. Everyone knows they need it but no one wants to get wet. It's easy to talk about how they need to be more accountable. But it can be uncomfortable when we apply it to ourselves. Yet we get more accountability from our teams by being accountable to them. It's a two-way process. Accountability starts at the beginning of the process. If we wait until the end, then we will just be putting out fires. Leaders and team members should be able to agree on the answers to a basic question. How will I know if I have met expectations? And let's remember that human communication is often not very precise. But when we collaborate, we need to be crystal clear and have measurable improvements and define milestones we want to achieve in order to succeed. Accountable leaders help their teams by communicating 4Ws. Oh, what are these? What, why, who and when. What actions needs to be taken? Why is this action important? You must link the action to the bigger picture so that the person understands. Who is responsible? This must be clear so that there is no passing of the buck. When must be the task completed? Be specific about when you want results. Saying next month or by second quarter is too vague. The fourth principle is set the rules. Have members agree on norms or a contract which defines each person's role. Have specific remedies for situations in which members do not live up to the agreements. For those who seem incapable of teamwork but whom you cannot do without, you might have to make special arrangements to accommodate them. But this should be the exception, not the norm. The fifth principle is prepare yourself to fall apart. Yes, that's right. It is essential that the team members feel safe to take risks and communicate openly. And yet things can and often do go wrong. Teams may start off feeling inspired and unified but later discordant personalities emerge, agreements get broken and suddenly everything is turned upside down. Prepare your team members for this process. And if productivity is going down, help them become aware of this. Reserve time in each team member schedule for people to sort out any differences and to regroup and reassess how things are. Let setbacks not become a reason to give up but to learn from mistakes made. Remember how sports team win games and at times lose badly? Should they? Should you? Should we give up then? Of course not. But there are times when a collaboration breaks down irretrievably.  Of course Neena. In dire situations that may be the only option left. Any way your question brings me to my next principle. The sixth principle directs us to see conflict as opportunity. No one likes conflict but this is the exact point when team members learn the ways of conflict resolution. They are going to need it to work together in the future. We must all learn the language of constructive feedback and the golden rule of good listening. Are you really listening or just waiting to air your own response? Often one can avoid difficulties later by having team members practice these methods at the beginning of a project. Ever see red? It's called being defensive. And turns out it is the single greatest inhibitor to true collaborations. Jim Temp, an expert in building collaborative workplace environments, advises us on getting out the red zone and cultivating a green zone attitude. Just follow the link to the next tab to see the video.


Alright guys, what's up JohnnyQ here. For those who don't know, MrBeast commented on one of my TikTok videos and he said, Hi, and I'm like, how you doing Jimmy? I'm JohnnyQ. Hey, Jays. And I was like, yo, I should make another TikTok with a heart shaped painting and I'm like, boom, let's get it. So, let's get it. Hi MrBeast, how are you doing today on this lovely afternoon? I think it's afternoon, right?   Hope you don't mind MrBeast, Mr. Jimmy. I don't know what you want to be called, but hope you like this piece. And let the hate comments roll in. Alright, let's get this. I'm going to put some black up in here. Also, when someone like a huge YouTuber comments on your stuff, I would recommend take as much advantage as you can and make all the content you can. Because that's awesome, right? Like, if David Dobrik, if David Dobrik commented on one of my videos, I'd be like, I'm going to make all the content that I can. Why not? About that comment, like, yo, it's about, it's called being smart. Alright guys, let's get this. MrBeast, here you go my friend. Oh, final result. MrBeast. Oh, yes sir. There you go my friend. Haya. Boom. MrBeast. There it is guys. I like that piece.


Welcome everybody thank you for inviting me to give this presentation. So what you see in the top left is the symbol of SEOS, the Committee on Earth Observation Satellites, which is essentially the way the public funded space agencies in the world collaborate through SEOS. And so these metadata standards have been developed under SEOS and endorsed by SEOS. So I'm going to show you a time series of satellite data in Morton Bay where you see Stratbroke Island and Morton Island. And you see data over about 20 or 30 years where you see the send banks moving, you see a bit of clouds, you see some kind of differences in the water, but on the land in general you didn't see any difference. And this is because all these satellite data have been processed to analysis ready data which means all the atmospheric effects have been removed, the geometric correction has been applied and a lot of other corrections have been applied in order to make the data comparable so that you can use one algorithm for the data for all the data, all the images instead of having to process each image. There was just an example, I'll give you a few more examples as I go on. So the Quartek Reflectance Product Family Statement, BFS's Product Family Statement, which is an official term from SEOS, was done by quite a lot of people from Australia, geoscience Australia and SRO, but also the Joint Research Centre of European Communion, Brockmont Consulting working on a lot of European Space Agency projects. American colleagues, Kent State, universities in Berlin, NASA folks, Belgium, Vito, Netherlands, Water Insights and Estonia, Tietcuzza and Italy, so you can see this was a very international led initiative. So analysis ready data from satellite data. So satellite data have always had the promise of providing long continuous time series which you can analyse for vegetation or for agriculture or for aquaculture or for coral reef bleaching or for many many other applications. However the data from satellites is measured at the top of atmosphere. In order to make an under, sorry at the top of atmosphere, so the satellites are 800 kilometers above us, they go around 30,000 kilometers per hour, so they circle the earth in 100 minutes and they make a tremendous amount of measurements, but under different light conditions, different solar angles, different skylight conditions, there can be haze, there can be dust, there can be smoke in the atmosphere or can be a very clear atmosphere, there can be sun glint on the water surface, you name it there are a lot of effects which you all would like to remove so that the data is all becomes comparable from day to day, over the years so that you can do long term trend analysis and change detection and that's why you need to go from top of atmosphere satellite data to bottom of atmosphere fully corrected data which is called analysis ready data and then you can better capture the where and when things happen and what happens and that can help you answer the question of why, why did it happen and what to do about it and if you did something about it did it help so this supply chain for earth observation is quite complex and there's a lot of specialized preprocessing and the data sets are large, the Lancet archive for Australia which is one image every 16 days for each location in Australia over about 35 years now is petabytes of data if you have to preprocess all of that data each time you want to use it that is a completely impossible task so what you want to do is preprocess the data and then make that available either by the cloud or by some other method so that people can select the data and process it further to for their information requirement and if you have analysis ready data then the big data aspect of this information can be exploited so analysis ready data is a step before you analyze the data for a particular use be it commercial use or a management use or an agricultural use or recreational use etc and this tries to show that if you have analysis ready data and you can process it all centrally to analysis ready data and then multiple users can use that data as they wish this is implemented in a digital earth Australia in Australia so analysis ready data has now been defined properly it's generated from raw data and processed so that it can be used without the need for further process in the context of water quality it's systematically radiometrically, atmospherically, geometrically and spatially corrected full archive earth observation data sets of either normalized water living radians or reflectance and effectively when we see color we see reflectance the satellites are just much better at it than we are interpretation ready data represents derived products so you use the analysis ready data then you apply algorithms to go to a water quality for instance which I'll show in a minute and some of these water quality constituents concentrations we can do nowadays is the total amount of algae or the cyanobacteria color dissolved organic method of tenants in the water transparency turbidity etc this is an example of interpretation ready data made using analysis ready data and this is Lake Hume and an algal bloom on the 27th of February in 2020 this is 10 meter resolution data you can say an enormous amount of patents in the water different concentrations of algae and where it's bright green it's effectively a cyanobacterial bloom going on in the lake this kind of spatial information is check can change how we manage our water bodies because the Lake Hume management authorities sample at one or two locations and as you can see here they're sampling if it's in the northeast they will actually shut the lake for recreation and fisheries etc because it's high cyanobacterial content if they sample in the south they'll say the water is fine for recreational purposes but this is the true story which is much more complex just as an example so one of the reasons for having to do this and having to establish these global metadata standards is that at a certain moment multiple providers of earth observation data were for instance there was an example in some lakes in Africa which were in a high demand to get information of those lakes different providers were providing different forms of earth observation data from the same satellite but reaching different conclusions now if you don't know how they process the data you can't compare the results so it's one of the main reasons for saying we must have global acceptable metadata standards because we must avoid confusion with the end users so this is done to access the very large datasets but also to make sure that the end users get consistent information which is really really important so I'll now go a little bit into the framework of this Committee on Earth Observation Satellites Analysis Ready data and there are product family specifications which are the full documents I'll give you an example of one and in our case we're looking at one of the optical products because remote sensing water quality is done by optical earth observation so this is the definition it's processed to a minimum set of requirements and organized into a form that allows immediate analysis with a minimum of additional user effort also very important and interoperability through time and with other datasets then satellite data becomes really useful so how does that how does this work well we've set metadata standards and now providers of data can do a self-assessment there's a whole there's a whole table for that on the web they can do a self-assessment how good they are and how far they reach these metadata standards then their self-assessment goes to an international peer review panel and they then verify whether this is correct and then they can get a effectively a stamp of approval that they are compliant I'm not going to go through all these metadata fields but I'm trying to give you an idea of what's involved which is this is the general metadata which is similar for most earth observation types so also for terrestrial and agricultural and geological applications so these are all the metadata you require including some actions and you've got threshold and target threshold is that's the minimum target is optimum if you can reach that that would be fantastic so the middle column is threshold the right column is target in the next slide I don't have that threshold and target although those columns are still there so this is general metadata which we've been trying to keep as similar as possible for the aquatic as for the terrestrial and other applications then we go to per pixel metadata so for each pixel and so we have massive amounts of pixels petabytes of pixels for each per pixel metadata we do want this information so you also have to look at clouds of course because you can't see them but you also have to look at cloud shadows you also need a land water mask but you also in especially northern hemisphere you need sea like and river ice masks etc etc so you have to identify do you see sun glint at the water surface do you see white caps from waves etc is there floating vegetation on the surface which can if you're looking for water quality those algorithms can't deal with floating vegetation so you need to flag this so there are many of these per pixel metadata then really important for remote sensing you have to do all these atmospheric corrections so you need to be able to know your water vapor your ozone corrections other trace gaseous corrections carbon dioxide for instance or methane or etc so you have to do all these corrections as well and this is a more detailed this is drilling into just one example where you say for instance you know the solar and viewing geometry that the metadata provides every solar and sensor viewing estimate and scenic angles which is quite logical if you think about it and that so there are multiple pages of these kind of metadata that have to be that have have these criteria in them and then the providers will self-assess against them this is lake burley griffin another time series provided by geoscience australia we're looking at total suspended metal levels and you can see the image changing on the left on the right you see a Huffmiller diagram which gives you along the black transect from the right of lake burley griffin to the left it gives you the total suspended sediment patterns and from this you can actually find weather types when there were lots of floods from 1987 to 1991-92 massive amounts of suspended sediment in the lake the millennium drought is visible from 2001 to 2013-11 you can see the lake was very clear because there was no major influx of suspended matter then you saw in 2010 and 2011 there were large inflow events with lots of stability again and you can hide total suspended matter and then you've got a relatively calm player again and we're now extending this time series to present and you would see in the last two years you would see massive increases in suspended matter again so you can see this kind of data can really be used to provide a lot of information so the development of this analysis ready data for aquatic reflectance was initiated in march 2020 it was endorsed one year and three months later and it applies to very specifically remote sensing data over coastal and inland waters and the version one is now available from the seos ard website so you can see there are also analysis ready data products now for surface reflectance surface temperature normalized radar backscatter polarimetric radar aquatic reflectance ocean radar backscatter and nighttime light surface radiance and many more are in development european space agency is actually beginning to use this to do a self-assessment as is the united states geological survey for their land-set products now we did use the land product family statement for terrestrial remote sensing as much as possible but we had to modify all these fields because they did not appear or were used for or need to be used in terrestrial remote sensing but they do are required in aquatic ecosystem earth observation so here you see some requirements we had to modify and new requirements that had to be identified and there are some changes that we had to do in the radiometric and abstract corrections as well so we had to do quite a lot of adjustments so the effect of all of this is that this is another way to mature the use of earth observation coastal inland waters because there's now a international metadata standards people groups that provide this data can now do a self-assessment which will help operationalize the information it will aid in the comparison from different providers in what they output the providers are all going to have to meet this new standard which didn't exist before and that will lead to trust by end users because they know it's now compliant and the most difficult aspects we have are still the surface effects at the water interface and effects in the atmosphere which we still have to work on and the interesting I'll get to that later there's an interesting consequence of this for research these are all some of the issues that we now really have to focus our research on so having these metadata standards getting the global community expert community together we then actually are identifying the weakest spots in our processing of earth observation data which is fantastic because we never had that in such a consolidated way which of course can lead to research programs with space agencies or research agencies or universities so it's fantastic it was an unexpected result that having these metadata standards identifies the area of research and development investment that is going to be needed and even if we do have the metadata fields filled in for threshold which is the minimum there's still quite a lot of research to go to target which is what would be ideal so this is a fascinating consequence we did not even anticipate when we started this process this is the date page on the seals website where you can go to and you can read much more about this and that's the end of my presentation


When you're looking for data, another great way of getting data is through scraping. And what that means is pulling information from web pages. I like to think of it as when data is hiding in the open, it's there, you can see it, but there's not an easy immediate way to get that data. Now, when you're dealing with scraping, you can get data in several different formats, you can get HTML text from web pages, you can HTML tables, the rows and columns that appear on web pages, you can scrape data from PDFs, and you can scrape data from all sorts of media like images and video and audio. Now, we'll make one very important qualification before we say anything else. Pay attention to copyright and privacy. Just because something is on the web doesn't mean you're allowed to pull it out. Information gets copyrighted. And so when I use examples here, I make sure that this is stuff that's publicly available, and you should do the same when you're doing your own analyses. Now, if you want to scrape data, there's a couple of ways to do it. Number one is to use apps that are developed for this. So for instance, import.io is one of my favorites. It's both a web page that sits address, and it's a downloadable app. There's also scraper wiki, there's an application called tabula, and you can even do scraping and Google Sheets, which I'll demonstrate in a second and Excel. Or if you don't want to use an app, or if you want to do something that apps don't really let you do, you can code your scraper, you can do it directly in our or Python, or bash, or even Java or PHP. Now, what you're going to do is you're going to be looking for information on the web page. If you're looking for HTML text, what you're going to do is you're going to pull structured text from web pages, similar to how a reader view works in a browser, it uses HTML tags on the web page to identify what's the important information. So that's things like body and h one for header one and P for paragraph in the angle brackets. You can also get information from HTML tables, although this is a physical table of rows and columns I'm showing you. This also uses HTML table tags, that's like table and TR for table row and TD for table data, that's a cell. The trick is when you're doing this, you need the table number. And sometimes you just have to find that through trial and error. Let me give you an example of how this works. Let's take a look at this Wikipedia page on the Iron Chef America competition. I'm going to go to the web right now and show you that one. So here we are in Wikipedia, Iron Chef America. And if you scroll down a little bit, you see we got a whole bunch of text here, we got our table of contents. And then we come down here, we have a table that lists the winners, the statistics for the winners. And let's say we want to pull that from this web page into another program for us to analyze. Well, there's an extremely easy way to do this with Google sheets. All we need to do is open up a Google sheet and then sell a one of that Google sheet, we paste in this formula, it's import HTML, then you give the web page, then you say that you're importing a table, you have to put that stuff in quotes and the index number for the table. I had to poke around a little bit to figure out that this one was table number two. So let me go to Google sheets and show you how this works. Here I have a Google sheet. And right now it's got nothing in it. But watch this, if I come here to this cell, and I simply paste in that information, all this stuff to sort of magically propagates into the sheet makes it extremely easy to deal with. And now I can, for instance, save this as a CSV file put in another program, lots of options. And so this is one way that I'm scraping the data from a web page because I didn't use an API, but I just use a very simple one line command in Google sheets to get the information. Now that was an HTML table, you can also scrape data from PDFs. You have to be aware of whether it's a native PDF, I call that a text PDF or a scanned or image PDF. And what it does with native PDFs is it looks for text elements, again, those are like code that indicates this is text. And you can deal with raster images, that's pixel images or vector, which draws the lines. And that's what makes them infinitely scalable in many situations. And then in PDFs, you can deal with tabular data, but you probably have to use a specialized program like scraper wiki or tabula in order to get that. And then finally media like images and video and audio, getting images is easy, you can download them in a lot of different ways. And then if you want to read data from them, say for instance, you have a heat map of a country, you can go through it, but you'll probably have to write a program that loops through the image pixel by pixel, to read the data, and then encode it numerically into your statistical program. Now that's my very brief summary. And let's summarize that. First off, if the data you're trying to get at doesn't have an existing API, you can try scraping. And you can use specialized apps for scraping, or you can write code in a language like our Python. But no matter what you do, be sensitive to issues of copyright and privacy. So you don't get yourself in hot water. But instead, you make an analysis that can be of great use to you or to your client.