'very little risk' - I think standard deviation of return on S&P is something like 15%-20%...I wouldn't define a strategy with a buffer of 2.7% very little risk when the standard deviation is that high...
I don't know more than the basics, my thought was if you pocket $2b/year and invest it, you have $13B+ in 10 years (plus your own $28b you've invested that I didn't include). So $40B to whether a storm every 10 years seems reasonable.
They wouldn't have to buy it back immediately. Short sellers would borrow the stock from a long and pay a predetermined interest rate for however long they're borrowing it. They technically don't have to rebuy the stock unless they get margin called (if the collateral posted is no longer deemed sufficient for the counterparty to allow the borrowing position) or need to close out positions because of some risk tolerance threshold being met. Usually when this happens to a bunch of shorts at the same time they must all rebuy, driving prices higher, which is called a short squeeze, but it is usually determined by someone cutting losses on a short position or positive news coming out driving prices up.
Short sellers don't need Tesla to fail to make money. There's plenty of room between Tesla being worth 50-60 billion and Tesla being worth 0. 50-60 billion of market cap means that Tesla has to do some absolutely crazy things in the next few years in an increasingly competitive environment while they've struggled consistently to meet production targets in less competitive environments. They have some problems such as a convertible bond issue for almost one billion due in Feb'19 that only adds to the cash burn problems if they can't meet the $360 convertible price. Short sellers push a narrative because they want the price to go down, but they really only take the position because they think that the market has currently mispriced the firm and there is opportunity there. They're not inventing problems, they're pointing out that they're there (perhaps exaggerating, but that's for the people to identify if true or not with the money they put on longs/shorts for Tesla).
From following various soccer blogs, it seems that defensive stats aren't as polished and explored as offensive ones. I'm curious what stats beyond things such as tackles/interceptions are looked at. For example, Maldini has the reputation of being one of the top defenders ever, but also is known for his quote "If i have to tackle, then I have already made a mistake" (paraphrased). His tackling stats seem to support that style of play in that he made fewer challenges than most. Perhaps he made tons of interceptions, and in that sense, never had to tackle? I'm unable to find a good source of his playing stats.
Anyways, what sort of things do you look at for defensive players? It seems that its when I look at things such as WhoScored's statistical team of the season, it has players such as Mustafi, who generally has a negative reputation for his play. I suspect he is so high because the rating metric used by whoscored overvalues offensive contributions of defenders, vs. pundits more likely look for a defender's defensive contributions. Are there any form of 'advanced stats' for defenders beyond the basic measured stats of challenges, interceptions, etc, that you and/or the industry looks for?
Defensive metrics are very difficult for a couple reasons.
The first problem is the data. The soccer viewing public is largely familiar with event-level data, typically provided by (my previous employer) Opta. They've done a great job normalizing soccer statistics on the cultural level, but the information they've collected at scale isn't that useful for creating good defensive metrics.
Other companies have sensed an opportunity here and have started providing more detailed data around things such as defensive pressure. Suddenly, you can contextualize each offensive event with the level of defensive pressure applied to it. I think this will be a game changer, but we're in early days there.
Other companies provide player-tracking solutions that give you real-time position of all players on the field. This is great because you have a "complete" picture of the game, but it requires a lot of work to build more sophisticated spatial/geometric models.
There's also the "Howard Effect", coined largely as a basketball term, but it's similar to the Maldini example you provided. Some defenders are so good that they don't have to be "active" defenders. That's something which is really difficult to adequately control for.
Thanks! Also, what are some sources for stats that would be available for free online? I've looked at some 538 stuff, some Statsbomb stuff, whoscored, and football-data.
THere's similar things like this in other sports, like American Football. You don't tell an amazing cornerback by just counting how many passes he broke down or intercepted: You also look at how often the player he was covering was targeted at all, and compare to their baseline. When a received that is normally amazing barely gets passed to, and when he does, the plays are not very fruitful, it's the defender's fault. When it comes to easy to digest statistics, that's handled by counting passing attempts towards the defender's area.
You can do the exact same thing in soccer, if you have the data: You can assign responsibilities to players, just through computer vision. If Messi gets 3 touches in an attacking position when Sergio Ramos is defending him, you can credit that to Ramos, and compare that to Messi's touches vs the average Barcelona opponent.
What Maldini meant by that quote was that as a defender, you should be in the right position so that the dangerous pass is never made, or the attacker doesn't have the chance to run past you. Tackling is sort of a last-ditch effort to stop the other player, and comes with risks of conceding fouls/penalties.
Hmm yes, my interest is that this sort of defender may be hard to identify purely from event driven stats, as stats mostly track actions done (tackles succeeded/attempted, interceptions made). A player such as Maldini wouldn't have shown up on lists sorted for tackles made, although he may have shown up on tackle success % or interceptions (not sure because I can't find a good source of data for his playing stats). Despite this, he has the reputation of being one of the best defenders to play the game. I'm just curious about what sort of metrics could identify a player such as Maldini.
Do you have any recommendations for how a hobbyist can get more into the field? Someone who has a technical background, but works in a different field unrelated to sports at all. Any reading material to get familiar with some of the stats and metrics that are used in the industry?
There isn't a ton of great public resources out there. For the most part, anyone who's writing smart analysis in the public space gets hired away to a club. It's exactly what happened in other sports.
But, I would read "The Numbers Game: Why Everything You Know About Soccer Is Wrong" and read the backlogs of the StatsBomb blog. That will get you up to speed pretty quickly.
