Tennis predictions, betting odds and Betfair trading | Bet Angel

So, tennis is one of those great sports where, there is a plethora of data and statistics, available to you and that. Means that this is prime, for analysis and using, that data to position, yourself loads. Of sports now present, loads of data I don't think they realize just how valuable this data is to traders, but, that's what I'm going to explore in this, video if. You're. Interested in learning to trade on Betfair then visit the BET Angel Academy where you have detailed, structured, Betfair, trading courses or, why not visit our website where you can download a free trial of bet angel professional, but, also visit, the forum where, you can get detailed images, examples, and downloadable. Files and don't, forget to subscribe to our You Tube channel and click on the bell icon if you want notification, of new videos as they're, released. So. Tennis is a sport that, has a lot of data sat behind it a lot of data is collected redistributed. Reinterpreted. And one of the things I love about sports. Trading, is that many years ago I used to have to collect data and I used to waste enormous, amounts of time trying. To get to the next level of what, I could see within a sport and, now it's just presented, to you on a plate in fact I don't think that, when people published, this sort of data that. They realized what they're doing to, help the betting and trading community because. A lot, of this data is absolutely invaluable if it's. Used in the correct way. So. When I was looking at trying. To crack, their. Puzzle that was tennis I knew. I needed to get to some of the core values I needed to understand, exactly. What. It was that I was looking at and how that would influence the outcome of the event because, think about it if you're reacting to stuff constantly you're always going to be behind the curve what you need to be to be profitable as to be ahead of the action in front of what is about to happen so, that is why tennis, trader on betangel was created because I wanted to model tennis to, allow me to understand, where. The price is going to be at some point in the future and, then, anticipate, that make a judgment, call on whether I think that it's going to happen that's how you profit on tennis and tennis. Trader was created, to allow me to model and then of course. In the product and you can use it too it's, you. Know it's a very complicated. Model. But, what I'm going to do for you here is to show you how this ties in with data that you see published. On ATP. Tour sites and so on, and. How you can put that into Tennis trader to, allow you to get even more accurate and, understand. How the model is created, and. Also you, know things that influence, the. Output to that particular model so. You know better angel over many years sort, of encapsulates, my journey through the markets and, obviously we get some very valuable feedback from.

People Using it and, therefore. That. Goes into as well so we just sort of get the best of both worlds without better, angel I couldn't trade and. In, order to keep, pushing the product Ford, we. Need everybody out there to be able to use it and that allows us to reinvest more money into it and things like tennis trader come. Out of the back end of that process so, tennis trader wasn't a feature that people asked for I, needed. It to be designed so that I could really understand, the opportunity, within tennis and there. It is so let me explain a little bit more depth. How. Its constructed in the way that it works and also, the sort of data that you can look out on websites that will enable you to get more out of it and understand where we're coming from on the model and. You. Know it's important to do that because you. Look at tipping, sites you look at people giving advice and it's. New from the wrong base within every sport, there's a core. Stat. That basically, defines the sport so for example in football it's you know how many goals can be scored and who scores them in tennis. It's all about points getting one and, you're thinking well how can you possibly distill, that into, a model well. Let me explain. So. Behind me you can see the ATP. Tour stats, and I'll, just explain some of these stats to you so you can understand what they are I've, actually visited the, website I've, gone on to the stats leaderboard. And then. I'm looking at more players over the last 52 weeks on all surfaces. And. It's coming up with these stats so I'll explain what some of these are the, SERP rating is basically how good are they at, that's, a stat, that's generated, out of the statistics, so. You can see John Isner is a good server well. I never would have guessed if. You've ever seen John list in a play you'll know what I'm talking about me, lost Ryan, egde is, also a good server as is Kevin Anderson so you can see you, know this is basically saying who, serves well you can see despite his age Roger. Federer is up there as well they're patro, Djokovic. Sam Querrey and. You're sort of thinking well why is there's this emphasis. On the serve, well. If we look at this this is the first serve percentage, and. We're not that interested in it we are interested, but not dramatically, what more interested is in is. The, percentage of first serve points, won because, this is saying that when the player goes, up, to. Serve this, is how, many times he is going to win that particular point and it's, this statistic, that we tend to use. Within. The, model, we're, looking at an, individual, player and we're saying how, often does he win a point on serve and therefore what chance does he have have, actually going on to.

Win The game so if, we look at is simplistically. Roger. Federer has about an eighty percent chance of, winning one, point, in a, service game on average. So. Basically, what, we're saying here is that if Roger Federer steps up and serves. 80, percent of the time he, will win that particular point so, what's the chance of Roger Federer, on average, winning. A game 40-love. So. It would be 15-love, 30-love. 40-love game. That, would be four points, so, if we do point eight to the power of four you've. Now got the percentage, chance of Roger. Federer winning. Again. -, laughs, it's. As simple as that that you go how. Easy was that but the problem is when. You look at tennis, there's. An infinite number of paths so that it can follow so you'd have to do forty low forty fifteen forty thirty, forty. Thirty where a player 130 lev up and then Roger Federer won it by coming back or he went 15. 15. Love 15, or or love, 15 there are an infinite, number of paths and that tennis, trader does the hard way for you there basically, but, let's have a look at some of these stats as well and dig around a little bit deeper within here so, you can see that Roger Federer has an 80% chance of winning a point, on his first serve, but 20%. Of the time he, doesn't or, maybe he, fails to get that serve in and therefore. You can see winning, a point on a second, serve drops, off fairly, dramatically, so. You know there are some important things in there 62 percent of the time he gets to serve in 80. Percent of those he wins but. If you do about 40% of the time he doesn't get it first service and he has to do a second serving about 60% of the time he wins those points. The, game's one. Tennis. Trader will do that for you so you don't need to particularly. Worry about that and you can see the number of aces the player, gets on on average within him but of course this is only really one side of the equation because, you've also got to look at, the returns of serve as well so. What you can see on here are all of the server, stats so we can see is known as the top of the list pedram Federer Djokovic. Query. Rafa. Nadal. Seems. To do pretty well as well he wins about 72 percent of the games and so you can see these are all of the service and then you can just scan down the list you can see they're actually in the sort of 70s, that's, about the area in which most of them are at and then as we get down to the slightly lower ranked players they, start to go into the 60s, and so, on so. Those, are all of the service, or. The. Serve leaders, they call them but we can also look because, obviously tennis, is involves, striking. A ball and then somebody playing it back we, can also look at the return leaders as well so. The, return leaders are basically the, first survey, that the player steps up he serves the ball and then, the guy tries to get it back so these are the percentages, of how, effective, players. Are at returning serve so. You can see Rafa Nadal is top. Of that list, I'm Schwartzman, Fabio. Fognini. Djokovic. David, go file you. Can see that Gao more fees they're, all good. Returners, of serve so you can see here you know it. Tends to be sort of in the in the 30s, and, the top players tend to be about 35% so. You're sort of saying there's a 70% maybe, up to this high as an 80% chance of somebody. Doing, a servant getting a point but. Then you've got to balance that out with how good the return of service as well so there's a mixture, between the, two there but. This, is where it gets interesting because obviously if somebody's got a 70% chance of winning a serve and somebody else has got a 70% chance of winning a service, game you, need to adjust that slightly based upon the return percentages.

But, Effectively, those two players are evenly, matched if you assess that they've both got a 70 percent chance of winning. A point against, their opponent. You. Can you can tell that they're fairly evenly matched so that it's the gap really between the, chance of each one winning a point on serve that defines how the match is priced and how those positions. Develop, as the match progresses I'll. Explain, a little bit more in a second. But. Yeah you can actually look at that I mean you can actually do that by surface, types as well so, if we look at surface type you can see Rafa Nadal on clay as. Brilliant, he's way above everybody else in terms of anticipating. And returning a seven clay which, we all know but there is the, data. Presented. To, you in in an actual percent so, you can see that there are some players that are good at clay, and. Some. That are better, at hard courts because if we switch to hardcore you can see Djokovic. Is at the top there and Rafa, Nadal drops down a little bit so can you see the difference in player, styles that you have there as well so yeah. You know these are quite basic stats but they offer a great, deal of insight so you. Know one of the things that I'll. Do here is if, you. Look at the difference between scale between players you know just a 1%, because in a tennis match there are hundreds, of points and what. There can be hundreds of points. Just. A 1%, skill that gap between two players creates. A significant. Difference in terms of their percentage chance of winning the match because 1%. Multiplied, by 200, points for example is going, to create a very large gap and. If the gap is you know a 5% difference it's. Gonna be massive. In terms, of how you'd expect to, price the match I have, done a graph on it somewhere what I should do is throw that up on the screen but, basically when you look at a player, with. Equal levels of skill they'll obviously be priced at evens. You know it's a 50/50 chance whether one of these two players could win but, as that skill gap increases then the odds change. Dramatically. So, what I'll do is I'll bring up a full image, of that on the screen so you can see how. Just a small percentage in skill difference between players, creates. A massive gap in terms of their chance of winning a match because it's played over loads of points it's, a bit like saying you know the first person to score ten, goals in a football match you. Know you have to reach that target effectively. In tennis as opposed to in a football match where your time limited so, the more chances you get to do that the bigger the skill gap will be and, if. You're looking even at a tiny percentage, that, will mass apply a massive, play that will multiply to a massive difference over. The course of a, match so yeah, the. Graphic that, I have, put on the screen or will put on the screen at this particular, moment in time yeah. Because I haven't done it yet will, show, you that, gap between the. Difference in in players so that's why you often see tennis match is priced at 105 102 103 because. There's probably only a 5 to 10% difference in skill between the two players because. But because, you're playing it over so many points. You. Know it relates, to massive difference in the outcome of for the individual, match so. Yeah school difference between players is quite small but I gets magnified over. Many points and that's, it, creates a massive difference in terms of that, percentage, chance of winning. But. Some the, the interesting, thing is you look at the men's game on tennis. And it's very different to the ones game so what I'm gonna do now is I'm gonna scoot off and we'll bring up the WTA, stats, and, we'll have a look at those so. I switched to the WTA, sites, now, which. Is where you can find all of the women's stats and for people who aren't into, tennis ATP, is the association, of tennis professionals there's, the men's game, WTA's. Women's, Tennis Association the. Women's. Game, different. Websites similar, stats they.

Obviously Converge, in terms of the stats that everybody's looking at so. I've ranked the women. Players here by their world ranking, you can see her soccer diameter. Soccer is number one at the moment you, can see C gets about 60%, of our serves in and wins, about 71%, of those services. She does get in, but. If you actually look down. This list you can see that generally. We're looking at the service percentages, they're a bit weaker than the men, so. This is where gender comes into play because, the men tends to be able to serve much harder and faster tend, to be a bit stronger and often, they tend to be taller as well not always but they, height. Is an advantage in tennis because you can get more height on the ball and, you can hit it harder, over the net which makes it more difficult to, return, you. Can generally see that the women's, game. There's. A tendency to for. That first service, point. One on first serve to be a little bit lower and that. Is because they're not serving is hard and it's. Easier to return so, the women's game tend, to be a little bit more competitive less, predictable, than the men's and. Especially, if you start throwing, in you know clay surfaces, and stuff like that that changes. The mix considerably. So. Yeah you, tend to get more volatility when, you're looking at the women's game, because breaks, of serve occur more frequently that's, the net upshot of what we're looking at within, here if. We look at the return percentages, here you, can see the return percentages, as I sort of you know just indicated, are much much higher so again being. Able to return a serve increases, the chance of winning a point and increasing, chance. Of winning the point increases, your chance of breaking serve so, this is why the women's, tennis tends to be slightly, better to trade than the men's because the men's is a bit boom bash now I'm.

Using A lot of regression, to, try and win a point suppose the women's game is a little bit more uncertain. But again you can see the sort of stats reflected, here in terms. Of the. Way that they, are, played out if, I go and rank these I've just realized it in rank these by, the. Top players but you can you can sort of see they're the, sort of data that we're looking at here now, the chance of returning a serve. Is, actually, sort of you know a little bit higher overall, I have showing, this on some of the. Videos. That I've done previously I've actually got long-term stats in there but all of these stats are freely, available so, what I'm trying to do is show you where. These stats are what, they sort of reveal and. You. Can then go off and play and do your own set of analysis on it from there but these are the sort of stats that I tend to look at and you, know there's, infinite, layers of depth you can go to but. You. Know I'm not going to do that on a video that just take far too long but yeah these are the sort of stats that are available give you a clue as to how good players. Are at serving, and returning observe, and. It's worth checking them out if you're going to analyze their match properly it may give you a bit of an indication a clue as, to how the match could play out and how competitive it will be and whether. There's, a good chance of a break of serve occurring at some point within the match so yeah have a look at these sites if. You want to get. Underneath the skin of a lot of these tennis matches so. How does this all fit in to, what you do when you fire up potential, and use tennis trader well. It. All makes perfect sense, because the way that tennis trader is constructed, is it's basically looking at the. Odds within a match so I've, just discovered this match that's fairly even and. It's. Basically, sort of saying well okay, let's. Look at the odds let's compare this to all, of the matches that we've seen, the. Type of match that we're looking at and let's, calculate out, what. That. Percentage is what is the implied percentage, that. Either, of these players is going to win a point on surf, that's. How tennis trade is constructed, using the stats that. You have seen that. We've just been looking at on those websites apart, from tennis trader has been developed. Into a model and it, monitors every, single path that could happen within the match works out the probabilities. Of that and then, it comes up with a price for you so, when you first go in and you use tennis trader you click on the calibrate, button and, that's.

What The calibrate button does, it looks at the odds it looks at the score and it goes hmm. I've, seen this before and then, it comes. Out with a route figure to. Be able to calculate all of that data fort, however. Did you know that you can actually modify that to yourself, so. I've. Truncated, the, matrix. Here so that we can just keep it on the screen at, the moment if I move, this and expand it which is going to take a couple of seconds so bear with me while I do that. Just. Need to bring, up the entire set matrix give, me a second one I reposition. This. What's. Tennis trader is doing is basically plotting, a path with every conceivable point, within the match that, could occur when players have, a set, percentage. So. The calibrate, basically. Looks at the odds looks at the players looks at the match and then, basically, works, out what that percentage, is however if, you go next to the calibrate, button here, you, can actually see that, there's a little spanner and if we click on that spanner it brings up a dialog box which I shall bring, actually. I can't bring it there because it's gonna be. Pinned to the top so, I'll move it to its left in which case and you. Can see here it says calibrate, with the seed value of a. Certain. Number there so 0.65. Is actually. The. Win on serve percent, to the you see on those, WTA, and ATP, sites, so it's basically saying, I'm. Gonna look at 65%. Look at these two players and then calculate, out from that seed percentage, as. Close as I can to your seed value the, difference in skill between these two players and calculate. The value from there. So. Um yeah that you can actually directly, manipulate, the output from, tennis, trader and the best way to demonstrate this, is to use fixed calibration. Values so if you're an experienced, tennis trader and you're using all sorts of data and stats to look at a match where, you've done loads of epic research before, a match starts, and you, want to input that into the model you can use tennis trader as just a calculating, engine so, for example if I do a fixed calibration, say we, think both of them are going to win, on. Serve seventy percent at the time, and. We apply that then. Can you see what it does to the score can you see that it says ii, ii. Ii ii ii ii ii ii ii ii ii ii ii ii ii odds. Of two that either of these players gonna win why does it say that because. That's. What the model is set at it's, basically saying there's an equal chance of either player winning, this particular match if, i look at the match grid you can see, it's. Evens they're basically, because. We're saying that both players are absolutely. Well in every respect they, both win a surf. Point, on serve at the same rate as they can return and they cancel each other out and therefore. They're exactly, equal, if I. Redo. This calibration now and then put one player 1% lower. And. Apply it again then, what you will see is that, that changes, so you can actually propagate, out in. The difference that are 1%, difference in skill would have across the entire match, and you can actually see that beautifully, presented for you on tennis trader so. If you want to use tennis trader sort, of in its, semi, intelligent, mode where it tries to do all of that for you it. Will basically try and correlate this, setup you've given it the score and the skill of the players and it roughly, works that out. But. You can actually do that all yourself if you want to go to the ATP and the WTA sites you want to build your own model in terms of how, you think those two numbers are going to interact with each other with each other then, you can just plug them in to tennis trader and it will do all of that for you so, if I trim this again to a 68%, chance and, apply it you'll. See how that influences, the outcome and, if. I do it again. With. A 5% skill difference and apply it you'll. See how. That affects the income as well so, if we see a match between, a player that has a 10% difference in skill then. You can see we're down into the 107's, effectively. In. Terms of their predicted. Odds of winning the particular, match of that particular moment in time so, you can then began to, look at things the other way around you. Can basically say, this match is priced at 102 105, 107, so. It is saying that Djokovic. Is 10% better than some other player and therefore. You can sort of say is that true is that really true and therefore, you can take your position whether it's a betting or trading decision, around, that, sort of data perfectly, possible to. Do. But. You, know that's the essence of the system but also think about it you know the first set. Has gone by and you're, beginning to notice a different sort, of, way. That one player is playing or something that he's doing this different or perhaps you think he's tiring you can actually use, a fixed, calibration, value to keep. That. Percentage, exactly, like that you wanted all the way through the map so if you suddenly think that that temp sensical difference, has.

Shrunk A bit because of something that you can see on court then, you can adjust the model as you go along so, if you really really want to get into the nitty-gritty of it adjust. Those values as the match progresses but. We're talking about a higher level of use there, of tennis, trader and that's, at a level that most people don't tend to work out however with. A model and the engine, within Tennis trader will allow you to manipulate, and, play around that to your heart's content, it's. Probably, the most complicated piece of work we've ever done on the product it. Does all sorts of clever stuff and its. Accuracy is down to you really because if you want to tweak the calibration, values based upon what you see you, can either tweak, them to. Understand. Where the price will go based upon your assumption, or you. Look at what the prices are within the market and then, you actually work out what the calibration, value is. Telling you about how. People are discounting, information, into the market maybe. They've, looked at these two players and one is quite clearly better than the other and therefore, you, know they, start expanding that percentage, or maybe they think the opposite that the highest skilled player is having a bit of an F gain and the percentage starts to shrink again but. Whichever way you use it it's a really powerful tool it's, perfect, for training on tennis it's one of the best bits of work that we've done and you should absolutely learn, to use it it will absolutely completely. Transform, the way that you trade tennis. You.

2019-06-04 17:33

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