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

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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

© Copyright 2019. Tehai. All rights reserved. .

Bet Angel is a phenomenal piece of software and by extension, that must apply to Mr. Webb and his team as well. Thanks for the Tennis video. Just got to learn how to put it into practice now. Any chance of a video with you trading one set of Tennis in Practice mode with small stakes. Always asking for more.

Question: Do you think that in order to trade early Horse Racing Markets I need to be watching them individually in order to be successful? Do I need to have 10 screens or monitors with one race on each screen in order to be watching them visually in order to follow the moves up and down? I've tried with two screens and to be honest, it's impossible to follow the moves even if you have them listed in Guardian. 10 Monitors – is it needed?