RUDYmentary: Pro tip on tracking plays via SBRSpreadsheet

[jjgold]

Some still call into true locals

[Cuse0323]

The best part about all of this when someone wants to see a ticket from those posting on here for years and they act like they got some fuking local where they call there bets in but then they taking live lines and shit. This ain’t the fuking 80s anymore,,, All the bookies now are using some sort of platform so folks can place bets from anywhere at any time. Ton of broke fuks here air betting there diks off without a pot to piss in and they know who they are.

:

[Cuse0323]

Some still call into true locals

Yeah, and never bet online while they post on an internet gambling forum where they bet points to win BTC.

[Biff41]

To me, while converting to dollars is a good idea, the real purpose of a spreadsheet track or a series of air bets is to evaluate whether your system or style of betting can keep up with casino. With JJ he may be posting a lot of bets....say Chicago Bears look good here.. . Clemson looks good against Notre Dame..Lakers look good when Lebron is coming in form and jelling with Alonzo .....Etc.. Etc ....but he may not be focusing on a winning betting style. Look I'm not knocking JJ. This is probably how most people get started in sportsbetting as hobby. But my point is folks need to first research the main techniques and ideas for winning betting and then understand their own style and from their focus on what they are good at......not easy. That's my rant for the day.

[RudyRuetigger]

whether to track units or money, nobody really gives a fukk

i was explaining a basic reason why to track in terms of cash, not units

kvb comes in with a genius idea, that a break even player will lose juice over the long term to prove me wrong





nobody has a 100% breakeven win rate and he wanted to jump this from a basic thread to something he deemed smart

the topic he wants to go is something completely different

then leads to expected value vs expected growth and he doesnt even know that

which is why its best to just track in money on your spreadsheet

[DiggityDaggityDo]

Wow... I’ve been doing it wrong for 4 fukkin years.

[GT21Megatron]

I’m gonna drive down to the pay phone at the Piggly Wiggly and get my Wisconsin second half play in with Paul. Hope I get there in time and the payphone is still there. I have my change ready

[KVB]

...kvb comes in with a genius idea, that a break even player will lose juice over the long term to prove me wrong...

No, a breakeven bettor would do just that, breakeven. Don’t be a dipshit. I never tried to prove you wrong, I was talking about the perils of your suggested bet sizing.

Gold even chimed in to troll you in the face of obvious math, and you fell for it.

...the topic he wants to go is something completely different

then leads to expected value vs expected growth and he doesnt even know that...

I wrote these exact words to keep the conversation away from expected value over expected growth, because, specifically, that isn’t the topic.

...Nearly every bettor at SBR should not even think about betting a percent of their current bankroll, it's tough to be that good and will most certainly ruin any tracking thread...

I don’t think you tried to misrepresent me this time, I just think I was way over your head and you seem to want to fight and argue.

Go ahead, brah, but this thread is amateur hour and I think it was best that my input should stay at that level. Sorry you didn't understand it.

[RudyRuetigger]

No, a breakeven bettor would do just that, breakeven. Don’t be a dipshit. I never tried to prove you wrong, I was talking about the perils of your suggested bet sizing.

Gold even chimed in to troll you in the face of obvious math, and you fell for it.





I wrote these exact words to keep the conversation away from expected value over expected growth, because, specifically, that isn’t the topic.



I don’t think you tried to misrepresent me this time, I just think I was way over your head and you seem to want to fight and argue.

Go ahead, brah, but this thread is amateur hour and I think it was best that my input should stay at that level. Sorry you didn't understand it.

absolutely disturbing

completely wrong on almost all points

[RudyRuetigger]

absolutely disturbing

completely wrong on almost all points

people can argue picks all they want...some win and some lose

but why has kvb posted 2 hours after i made this post but not responded here?

[Biff41]

If KVB feels the thread is amateur hour he may be too busy working up another act.

[RudyRuetigger]

Like I said, not to pick on this guy again but hes down to 61.87 units from starting with 100 units

with 30 units pending on a 4 team teaser

https://www.sportsbookreview.com/forum/players-talk/3513536-ditties-10-bankroll-bets-p2.html#post28306121

if he wins, units will be very inflated

who even knows how much 30units is worth now?

im sure its not $30, which is what 10% of the roll started out as (x3units)

[jjgold]

KVB as sharp as they come

This thread above him


As far as spreadsheets mine is the model on tracking

[RudyRuetigger]

KVB as sharp as they come

This thread above him

guy couldnt hold my pencil while taking an abstract algebra class

[jjgold]

Rudy I met him

Very technical


You could not compete with him gambling

Beer yes you can

[RudyRuetigger]

Rudy I met him

Very technical


You could not compete with him gambling

Beer yes you can

guy avoiding this thread

wanted me to do the math on a breakeven player

sad



i think he is a wannabe nerd


you know...those guys in revenge of the nerds that cheer on the nerds...that is KVB

[jjgold]

Rudy any plays tonight?

[RudyRuetigger]

no

on a date

went to bathroom to post

[jjgold]

Ok cool

[RudyRuetigger]

might make a new thread in a couple hours

[juicername]

might make a new thread in a couple hours

Rudy is legit. A true asset for the uneducated masses.

[RudyRuetigger]

Rudy is legit. A true asset for the uneducated masses.

the next one is going to be ONLY for those losing gamblers

just a FUN FACT up next

my secretary is typing it up

[HurryUpAndDrink]

Good thread Rudy

[RudyRuetigger]

thanks bro

[Jayvegas420]

From a tracking perspective units are not only complicated to follow there are easily fudged. I find units can be useful to try and gauge how strong a player thinks his edge is for any particular game.

[RudyRuetigger]

From a tracking perspective units are not only complicated to follow there are easily fudged. I find units can be useful to try and gauge how strong a player thinks his edge is for any particular game.

do not go by units

Note: This is not supposed to be a "Think Tank"-style thread but rather one that's meant to be accessible to a wider Players Talk audience. As always feel free to ask any relevant questions.

Handicapper A has a record of 12-68 for +79 units (obviously he's been betting many underdogs), while Handicapper B has a record of 63-17 for +26.5 units (obviously he's betting many favorites).

Based on these records who can we say is more likely to be a +EV handicapper?

Well, the truth is that armed with solely this information we can't say very much at all.

Even if we assume that each bettor were solely placing uncorrelated bets (and so, for example, weren't double counting a bet on a 5 inning line and a bet on a full game line) there are least two additional pieces of information that would further need to be considered:

1. How much did each handicapper wager on each bet?
2. At what odds were each bet placed?

One concept of great use to statisticians when analyzing data is that of the standard deviation. This refers to the degree of variability within a set of random (or partially random) data that may be attributed to chance.

For example, were you to flip a fair coin 1,000 times, then on average you'd expect to see 500 heads and 500 tails. But this doesn't mean you'd always expect to see exactly that heads/tails breakdown: sometimes you'd see 520 heads and 480 tails; or 488 heads and 512 tails; or every once in a long, long, long, long while 598 heads and 402 tails. In fact you'd only expect to see exactly 500 heads and 500 tails with probability 2.523%, which, while still the single most likely outcome is nevertheless a big dog to occur (fair odds of about +3864).

So this is where standard deviation comes in to play.

Every random variable is associated with both a "mean" (which is just an "average") and a "standard deviation". The mean tells us the expected value of the random variable, while the standard deviation tells us (loosely speaking) the expected degree to which we expect that that random value will tend deviate from that mean.

So let's go back to the example of flipping 1,000 coins. Obviously, the mean is 500 heads and 500 tails (which is what we'd "expect" to see on average). The standard deviation (and for now, don't worry where I'm getting this figure) is 15.81 heads.

So what does this standard deviation figure really tell us?

Well, for sufficiently large data sets it allows us to estimate the probability of a given event (or a rarer event) occurring. The way we do this is by formulating what's known as a "Z-score". The formula for a Z-score is given as follows:

Z = (Actual - Expected) / (Standard_Deviation)

So let's calculate the Z-score for each of the 4 heads/tails combinations above:

1. Z(500 heads) = (500 - 500) / 15.81 ≈ = 0
2. Z(520 heads) = (520 - 500) / 15.81 ≈ = 1.2649
3. Z(488 heads) = (488 - 500) / 15.81 ≈ = -0.7589
4. Z(598 heads) = (598 - 500) / 15.81 ≈ = 6.1981

OK so now we have a bunch of Z-scores. Now what?

We know from what's known as "The Central Limit Theorem" that as random data sets get sufficiently large the distribution approaches what's known as a "Gaussian" or simply a "Normal" distribution. The net effect of this is that we can treat Z-scores obtained from sufficiently large data sets as normally distributed random variables with a mean of 0 and a unit standard deviation.

Back when I was younger I remember our stats text books had pages of tables that converted between Z-scores and probabilities (not to mention the tables related to other commonly used distributions that are beyond the scope of this brief article). Luckily, those of us with MS Excel or OpenOffice Calc (or Google) no longer need to flip to the back of a book every time we encounter a Z-score.

Using the Excel function =NORMSDIST() (which the Excel help files explain, "Returns the standard normal cumulative distribution function. The distribution has a mean of 0 (zero) and a standard deviation of one. Use this function in place of a table of standard normal curve areas.") we can estimate the probabilities associated with each of the 4 Z-scores above:

1. P(500 or more heads) ≈ 1- NORMSDIST(Z(500 heads)) = NORMSDIST(0) = 50%
2. P(520 or more heads) ≈ 1 - NORMSDIST(1.2649) ≈ 10.30%
3. P(488 or more heads) ≈ 1 - NORMSDIST(-0.7589) ≈ 77.61%
4. P(598 or more heads) ≈ 1 - NORMSDIST(6.1981) ≈ 0.00000002858%

Note that because the NORMSDIST() function gives us the probability of the specified number or fewer heads, we subtract the resultant value from to give us the probability of the specified number or more heads.

There's actually a potentially easier, if less instructive, way of obtaining the same results using the related Excel function NORMDIST() (which the Excel help files explain, "Returns the normal distribution for the specified mean and standard deviation. This function has a very wide range of applications in statistics, including hypothesis testing."). This allows us to obtain identical results as those above without having to manually calculate a Z-score. The format is =NORMDIST(actual, mean, standard_deviation, TRUE). To wit:

1. P(500 or more heads) ≈ 1 - NORMDIST(500, 500, 15.81, TRUE) = 50%
2. P(520 or more heads) ≈ 1 - NORMDIST(500, 520, 15.81, TRUE) ≈ 10.30%
3. P(488 or more heads) ≈ 1 - NORMDIST(500, 488, 15.81, TRUE) ≈ 77.61%
4. P(598 or more heads) ≈ 1 - NORMDIST(500, 598, 15.81, TRUE) ≈ 0.00000002858%

which are of course values to identical to those obtained above.

So the next logical question for many sports bettor might be, "How would one use this to compare records between handicappers?"

Well the answer is pretty simple. We calculate a mean and standard deviation for each handicapper based upon his bets, and then using Z-scores determine the probability of obtaining such a record by chance alone.

The mean is the easy part. If we forget assume no juice, then the expected result for a handicapper is 0, in other words over the long run we expect him to break even. This is actually a bit less onerous an assumption than it might initially appear. Remember, we're not trying to determine if a handicapper is able to perform slightly better than a coin flipper, but rather determine how likely he is to be better than a breakeven handicapper. (Of no less importance is the fact this simplification makes the calculations much easier and allows to only concern ourselves only with the price of each bet rather than necessitate recording the price of the opposing side as well, so as to be able to calculate juice.)

The standard deviation is only slightly trickier. Recall from basic probability that the standard deviation is the square root of what's known as the variance (and that's really all you need to know about variance -- sqrt(variance) = standard deviation, and by the same token (standard deviation)^2 = variance). The standard deviation of a single "binary outcome" bet (meaning that the bet can only either win a certain amount or lose a certain amount -- we leave out pushes from our analysis) is given by this simple formula:

variance = (bet_size)^2 * (decimal_odds - 1)

(To convert from US to decimal odds you can reead the refresher in this post, punch up my Odds Converter, or use the US2DEC() function in my VBA Sports Betting template for Excel.)

So let's look at a couple of examples:

1. A 1 unit bet at => variance = 1^2 * ( - 1) = 4
2. A 1 unit bet at => variance = 1^2 * ( - 1) = 2
3. A 2 unit bet at => variance = 3^2 * ( - 1) ≈ 3.63636
4. A 3 unit bet at => variance = 3^2 * ( - 1) = 1.8

To then determine the variance across multiple bets, we simply sum up the variances of each individual bet.

Taking the square root of the sum then yields the standard deviation (which will be either in dollar or unit terms depending on how we choose to measure bet size).

So the total standard deviation of the 4 bets above would be given by:[indent]standard deviation = sqrt(4+2+3.63636+1.8) = 3.38177 units.

So now let's return to our two original handicappers (A & B) from above, Handicapper A with his record of 50-30 for +36 units, and Handicapper B with his record of 48-32 for +16 units.

Let's say that the two handicappers respective results were obtained from the following 80 bets:

    Bet    Decim.
Odds    Size    Odds    Variance
+900    9    10    729
+900    8    10    576
+900    8    10    576
+900    8    10    576
+900    8    10    576
+900    8    10    576
+900    6    10    324
+900    6    10    324
+900    6    10    324
+900    6    10    324
+900    6    10    324
+900    4    10    144
+900    1    10    9
+900    1    10    9
+900    1    10    9
+900    1    10    9
+900    1    10    9
+800    8    9    512
+800    8    9    512
+800    8    9    512
+800    8    9    512
+800    6    9    288
+800    4    9    128
+800    4    9    128
+800    4    9    128
+800    2    9    32
+800    2    9    32
+700    8    8    448
+700    4    8    112
+700    2    8    28
+700    2    8    28
+700    2    8    28
+600    8    7    384
+600    8    7    384
+600    8    7    384
+600    8    7    384
+600    6    7    216
+600    6    7    216
+600    4    7    96
+600    2    7    24
+500    8    6    320
+500    6    6    180
+500    6    6    180
+500    6    6    180
+500    6    6    180
+500    2    6    20
+400    8    5    256
+400    8    5    256
+400    6    5    144
+400    4    5    64
+400    2    5    16
+400    1    5    4
+300    8    4    192
+300    8    4    192
+300    8    4    192
+300    4    4    48
+200    8    3    128
+200    8    3    128
+200    8    3    128
+200    8    3    128
+200    8    3    128
+200    8    3    128
+200    8    3    128
+200    8    3    128
+200    8    3    128
+200    6    3    72
+200    6    3    72
+200    6    3    72
+200    4    3    32
+200    2    3    8
+200    2    3    8
+200    2    3    8
+200    2    3    8
+200    2    3    8
+200    1    3    2
+200    1    3    2
+200    1    3    2
+200    1    3    2
+200    1    3    2
+200    1    3    2
Total Variance:   14,810
Standard Deviation = sqrt(14,810) [hcc]asymp[/hcc] 121.696 units

    Bet    Decim.
Odds    Size    Odds    Variance
-900    9    1.1111    9
-900    9    1.11111    9
-900    9    1.11111    9
-900    9    1.11111    9
-900    9    1.11111    9
-900    9    1.11111    9
-900    9    1.11111    9
-900    9    1.11111    9
-900    9    1.11111    9
-900    9    1.11111    9
-800    8    1.125    8
-800    8    1.125    8
-800    8    1.125    8
-800    8    1.125    8
-800    8    1.125    8
-800    8    1.125    8
-800    8    1.125    8
-800    8    1.125    8
-800    8    1.125    8
-800    8    1.125    8
-700    7    1.14286    7
-700    7    1.14286    7
-700    7    1.14286    7
-700    7    1.14286    7
-700    7    1.14286    7
-600    6    1.16667    6
-600    6    1.16667    6
-600    6    1.16667    6
-600    6    1.16667    6
-600    6    1.16667    6
-600    6    1.16667    6
-600    6    1.16667    6
-600    6    1.16667    6
-500    5    1.2    5
-500    5    1.2    5
-500    5    1.2    5
-500    5    1.2    5
-500    5    1.2    5
-500    5    1.2    5
-400    4    1.25    4
-400    4    1.25    4
-400    4    1.25    4
-400    4    1.25    4
-400    4    1.25    4
-300    3    1.33333    3
-300    3    1.33333    3
-300    3    1.33333    3
-300    3    1.33333    3
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
-200    1    1.5    0.5
+100    1    2    1
+100    1    2    1
+100    1    2    1
+100    1    2    1
+100    1    2    1
+100    1    2    1
Total Variance:      334
Standard Deviation = sqrt(334) [hcc]asymp[/hcc] 18.276 units

So calculating the Z-score for handicappers A & B we have:

Z(han. A) = (79 units - 0 units) / 121.696 units ≈ 0.6492
Z(han. B) = (26.5 units - 0 units) / 18.28 units ≈ 1.4500

Converting to probabilities using Excel's NORMSDIST() function yields:

P(obtaining handicapper A's result or better purely by chance) ≈ 1 - NORMSDIST(0.6492) ≈ 25.812%
P(obtaining handicapper B's result or better purely by chance) ≈ 1 - NORMSDIST(1.4500) ≈ 7.353%

So what we see is that a bettor placing the same bets as handicapper A would, purely by chance, obtain the same results as A (or better) about a quarter of the time.

Similarly, a bettor placing the same bets as handicapper B would, purely by chance, obtain the same results as B (or better) a bit less less than one time out of every 13.

So anyway, in the interest of simplicity while I've certainly glossed some very important points, I hope this describes a simple framework through which handicappers' records may be compared and analyzed going forward.

So remember ... next time a handicapper tells you he's 32-30 for +15 units a good response would be, "Oh yeah, what's your Z-score?"

(A couple notes of caution -- Z-scores are less reliable over small sample sizes, tending to sometimes vastly overstate actual significance. They'll also be less reliable if the odds examined are over an extremely wide range, especially if there are are a small number of bets at very long odds. There are certainly other ways to measure a handicapper's success, but a discussion of this would be beyond the scope of this article.)