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  1. Yep that's what I thought too. I bet he will keep Origin. But I hope he will change the short. He got good scores with it, broke WR and all, so it's ok to move on. Origin, on the other hand, wasn't perfect. Plus there's that 4A Gong.. On the bright side, since he'll stuff it with new elements it will look like a new program. So that's still something to look forward to. Tbh Origin looked great on media day last year (and it got some fans too, just not as universal as,say, Seimei imo).
  2. Oh wow, Oakville is practically next door to Toronto. This does make travelling + accommodation a lot easier. I'm definitely considering it... p/s: I've booked a (cancellable) apartment 10 minutes by Uber from the place, arrive Thursday depart Sunday. Should be good for 4 people to share. Current total price is 200 in total, so would work out to be 50 per person for 3 nights! If anyone is interested, PM me!
  3. I voted for SC + NHK, but imo SC + COR is likely as well. This reminds me of last year, when we were all too sure that he would do SC + NHK, then the mystery assignment turned out and everyone's jaws dropped... LOL Crazy times.
  4. @Old Cat Lady Yeah yeah, please do prepare something. It's my first worlds, super excited! (Though I'll miss most of it live -- Mexico timezone is just not compatible). Could you give a link to how the scoring etc works too?
  5. I agree with you that one needs to gather all the data into one place. I could write codes to scrape, but if skatingscores already did this, I'd like to ask them for permission and credit them for that work. (Or to ask the ISU directly). However, I would refrain from actively looking for things like "block biases" though. We should always look at the data in the most objective way as possible, free of assumptions and biases, and then just accept whatever the data tell us, regardless of whether that contradict or affirm our beliefs (of course, after making sure that we did not make silly errors in the computations or the modelling step). Otherwise, our brain is very primed to selecting and presenting convenient information that affirms our biases, and we just end up seeing things we already assumed, which I think is worse than not analyzing the data at all. Just by glancing at the nice tables you made, I honestly don't find any conclusive evidence of under or overscoring. eg: if we were to zoom in at Jun's score at GPF: the judges are quite divided on him: JPN + FIN + KOR judges give him huge + scores, while three others are huge -, and two are in between. Should we conclude that one group is biased +, the other is biased -, and the "middle ground" ones are fair? No. We can conclude that there's no clear "majority" view on his skates. Doesn't mean that the + or the - are "wrong" camps. While I totally agree that humans have biases in just about everything (subconscious or conscious), if you think about how these biases manifest, it's pretty hard to uncover, unless if it's fairly blatant. (which in my experience as a statistician, it's not at all obvious from this figure skating dataset). We (the statisticans) also have our own biases. So that's why we need lots of data + an objective analysis method.
  6. @yuzuangel Interesting. Well, I just wrote to them directly asking for permission to use their data. (Not that they own the data, honestly, but I'm ok with giving their some credit for doing the scraping work). We'll see. If they say no, I'll write to the ISU to ask for data. And if not, then I'll scrape. The more I think about it, the more I'm convinced that a simple collaborative filtering model with a "judge bias" term, together with a low-rank factorization on the performance's attributes would work well. I'm excited.
  7. I agree with you. This plot by itself is meaningless. The correct thing is to plot PCS by some measure of how "clean" they are, eg: PCS by TES, or PCS by total GOE, for example.
  8. Thanks. Let me contact skatingscores.com directly and see what sort of existing data / analysis / model are there. A model I can think of would be able to make statements like this: * it is likely that judge X favors skaters (S1, S2, S3,...) in TS, which all have the following common attribute (A1, A2 etc). That's probably the kind of thing that we want to look for right? With more detailed data we can even say * it is likely that judge X gives high GOE on the Salchow of skaters (S1, S2, S3,...), whose jumps all have the following common attribute: (A1, A2, etc...) So that's why I want to have as detailed data as possible. Though, given how noisy figure skating score is, I think the bias has to rather huge for a statistical model to pick this up.
  9. It's *amazing* that you entered the stuff by hand. Did you just get such data from the ISU pdf protocol? (and did you enter that raw data by hand, or did you have a script to read off the pdf file?) Let me make sure I understood the definitions of the variables: - TES/GOE/PCS diff of judge A on skater B means: * for each skate( short and free) * take judge A's score on skater B's performance (eg: TES), then subtract off the *average* score of the other judges ? That's your raw data, and after wards the other cells are your calculations? I'd like to get *raw* data (ie: no averaging, no extra statistics, as much info recorded as possible). So for example, ideally for me, I want to get the entire ISU protocols in raw format. Previously we had this data before (for old rules / pre 2018-2019 season), but we didn't have the judge's names, so we couldn't do the judge bias analysis. Sorry for these question - it's actually easier for me to work on the raw data directly, as opposed to the averaged stats. I like your analysis very much though, and will definitely check-in with you to get intuition.
  10. This is great! I've been looking for this kind of data in the earlier project with another satellite here. Would you like to collaborate on this? I'd love to analyze this dataset. Some questions: a/ The judge spreadsheet that you uploaded was averaged over all skaters in all competitions that this judge participated in? Are there judges which appeared in multiple competitions? Did you make a distinction between seniors and juniors? b/ Do you have the *raw* data (one judge delta for each performance, with label as to which performance it is)? What's the raw format like? (another spread sheet? Or some database?) I'd like to work with the raw data if possible. (I have a stats background and worked on some collaborative filtering problems before (ie: how Netflix recommends movies to us). This problem has that flavor, so probably the same math would give us interesting insights). @shanshani Please feel free to PM me if you want to talk more about it -- or, we can discuss it openly here and hopefully other techie satellites can join us. I'm excited!
  11. @LeadenMyr That's a great cake! Did you eat it in his honor? I'm inspired!
  12. Um. Well, I'm probably biased, but I had ED to some extent while doing a lot of sports in my teenage years. There was a long stretch of time when I would eat only yogurt for lunch and diner in a bid to lose weight. And definitely before weighing in for competitions I would dehydrate myself intentionally to make sure that I don't have "excess water" in my body, and then drink up later. It's common practice, done in a "controlled" way. Eventually I quit due to injuries, which may or may not be related, one would never know (it's a sport with high rate of injuries anyway). But let me clarify why it's tough for athletes to take the ED message. Their initial reaction would be "what, not another one of these unnecessary concerns from people who don't understand athletes anyway." Or they could say : "no that's totally not me, I'm just managing my diet responsibly". I, honestly, still identify with these messages so much, that i find the hype over Alina's comment hard to understand. 1/ All top athletes manage their diets. This makes sense, we are what we eat. But nutrition science is a dark art - nobody knows what works 100%, and then there's our own body that's unique too. So often you would just go with the trend - do what others do - do what works for you. eg: having a full breakfast / lunch, then a fruit for dinner, is *very* common. But not everyone ends their career with injuries. And those who did - well, it's just part of sports. It's hard to pin down (except for clinically clear ED cases) that the imbalance of whatever intake was the cause. So, ED exists on a continuous scale, and normal athletes are quite up-there already (definitely *far* from the general public's way of diet management). 2/ Puberty is complicated: while we gain an enormous amount of muscles, there's also some random fat deposits that we're not used to. There's a lot of self-consciousness / bodyshaming from the athlete themselves: why can't I be like XYZ kind of mentality. And I think this is an issue not in sports, but in society as a whole. In athletics, the male body is the symbol of strength, power, etc. Think of a sport - any sport -- and name a few stars. Now, tell me, "what's the body type of an athlete in this sport? Long-distance runners? Thin and well-defined, like raisins, almost fat-free. Rowers: some upper arm muscles, but mostly enormous legs. Swimmers: broad shoulders etc. Now, how many of the bodies you have mentioned are based on *female* athletes? For me, zero. I have plenty of female athletes whom I admire, but the male body type is still what I associate with the top performance. And with this, it's natural for female athletes to hate the changes that happen to them (their bodies seem to be going in the wrong direction). 3/ There's the notion that if you have period, then you're not practicing hard enough. It's true that if you train lots + not eat much, there's no period (or it's super light, and very irregular). But we don't feel anything weird, and so we think it's just a result of hard training. If anything, it is very convenient not to have heavy periods, and it confirms that we've been working hard. THere's also a theory floating around in my team that the blood just get reabsorbed by the body, so that it's very "efficient". We all believed it in. And we didn't bother to check. There wasn't time , plus, a lot of the times, you just need to work yourself into believing, and then you will achieve. That's the mentality in sports, and we're used to that. 4/ As teenagers, we're still kids. Having a family etc, honestly, was not on my radar. Boys / loves are just nuisances, so to speak. Our idols train hard, have grit, go through all the tough stuff, and we want to do that too. So while I'm very grateful that Akiko spoke up -- words came from an athlete there's a lot of credibility with them -- but I don't find the reasoning she gave too compelling. (It sounds like that's what she's thinking about now, but not years back then when she was in competitions) 5/ Athletes push boundaries, physical and mental ones. We cut corners. Whether we like it or not, we get injured. Physically. Mentally. And we triumph. No pain no gain - then, why not push the internals of the body to the limits too? Pains and injuries, sadly, are necessities in sports, and to get anywhere, be on any podium with some competition, you must be able to overcome the challenges. So, related to my point 3/, it's like a badge of pride to push yourself to the limits, and survive. The long ramble is to say: it's part of the job, we accept it, we take pride in being able condition our bodies into crazy shapes. Yes we're damaging it, but any obsession is unhealthy, and to win you just have to be obsessed. Athletes are mature -- and of course they know the risks (though they may not assess it correctly, or choose to do it anyway for crazy reasons). . But how's (managing your diet) is that different from running on the treadmill until having cardiac arrhythmia, for example? (Positive risk from over training, and yes it does happen). Or how about tonnes of people skate with sprained ankles, broken bones, this and that. I mean, your body is not perfect everyday, should you give in to every single cuts? I'm sure that a lot of what I just said are like "common myths" around ED, but this is really how athletes think, and to convince them, you would need to address those points. (Actually, I do have a theory on what to do, but it's late now so let me just post this).
  13. I like Jason's ACI SP quite a bit! The music.. hmmmm.... but his spins were beatiful. I wish Lambiel tipped him to do more variations though.
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