How Fair Is My D20? (2015)

http://www.markfickett.com/stuff/artPage.php?id=389

by jandeboevrie • 7 years ago

194 68 7 years ago

Yhippa• 7 years ago

Interesting. I went to the most recent Prerelease event for Magic: the Gathering and my first opponent told me to not use the D20 that came with the kit and to use his individual D6s. He said they had known biases. Maybe he was on to something.

rapfaria• 7 years ago

Your opponent told you to use the die he brought?

He was probably on to something.

quink2• 7 years ago

If the opponent picked from the same pool that sounds OK.

At least way better than spindown dice, which are known to be weighted.

reificator• 7 years ago

I get where you're coming from, but I honestly assume no malice. It's fairly common knowledge in tabletop circles that spindown dice will have an unbalanced distribution. They're definitely made to be used only as a counter.

Now, whether it matters if you use a weighted die to determine who goes first is a different story. If you're both using the same die, who cares?

busterarm• 7 years ago

The D20s that come with Magic products are spindown dice, not normal D20s. The faces are ordered for ease of lifetracking and are _not_ optimized for random rolls.

Because the dice aren't evenly weighted, they have a strong bias. IIRC, Spindown D20s crit somewhere around 30% of the time.

ufo• 7 years ago

More specifically, in the spindown each number is adjacent to its predecessor and successor. In a regular d20 the numbers are more spread out, and opposite faces add up to 21.

beatgammit• 7 years ago

The only time I used a D20 in magic was for keeping track of life totals. If you're rolling to see who starts, it doesn't really matter if it's biased if you use the same die.

I guess some cards use a dice roll, but that's pretty rare.

aceld111• 7 years ago

As a mtg player, I really don't get why can't we use spin-down dice as high roll at the beginning of the game.

brianwawok• 7 years ago

As a fellow MTG player, mostly people hearing a story once how someone tested a spindown dice, and it wasn't fair.

But the average MTG player at a con did not take stats in college, and not worth a fight. So ya just pull out another dice and smile and roll it.

quink2• 7 years ago

First thing I can think of is that it may matter if the distribution isn’t linear, although not really sure how it would.

The second more straightforward one is that the spindown dice vary from set to set and even within the set sometimes. As such the weighting is likely going to vary a lot.

danielvinson• 7 years ago

I'm a former competitive MtG player. My playgroup found that with a bit of practice and a specific technique, we could roll 17+ on any spindown dice almost every time (try rolling the die with it starting in your hand with the 20 facing upwards with a sideways motion). While technically you can use any method you choose to randomly determine the start of a game, these dice have been proven to not be "random" thus cannot be used in a tournament. It doesn't matter at all in casual play, but in a tournament, you're just giving your opponent a chance to play first for free.

woliveirajr• 7 years ago

Should add [2015] to the title

sctb• 7 years ago

Updated. Thanks!

toufiqbarhamov• 7 years ago

Hi sctb, I’m given to understand that you’re one of the moderators here. I’ve tried to contact you twice in two weeks through email without a response, so I’m concerned that it’s hitting your spam folder. Is there a better way to contact you? I don’t feel good about inserting my comment in an unrelated post like this, but I’m unsure what else to do.

markfickett3• 7 years ago

Hah yes, as the author I was surprised to see this pop up again! But it's a pleasant surprise for sure.

jandeboevrie• 7 years ago

It was on Lobste.rs first and I thought people here might like it as well.

Fomite2• 7 years ago

teej• 7 years ago

Here’s a fascinating vizualization of 6000 simulated D6 rolls - https://www.reddit.com/r/dataisbeautiful/comments/au25nq/sim...

nickthegreek2• 7 years ago

there is also the saltwater float test for lighter plastic dice.

https://www.youtube.com/watch?v=VI3N4Qg-JZM

Anyone know of an easy way to do metal dice?

swashboon• 7 years ago

just float in mercury or lead :)

isoprophlex• 7 years ago

A fluidised bed setup? (Would generate some pretty bad dust, but it might beat mercury vapors)

tedmcory772• 7 years ago

Have you ever seen numbers run on float tested dice that test as biased?

Metal dice are less likely to have balance issues on the individual dice as long as the mold is balanced (because they are solid and heavy).

Source - I own a dice company.

nickthegreek2• 7 years ago

I have not, but that sounds like a great kinda thing that a dice company should post! My d&d players are _kinda_ dice obsessed. What is your company? My buddy and I run a small business making dice towers/trays on a laser.

11thEarlOfMar• 7 years ago

Makes me wonder the extent to which the rolling surface would affect the outcome. A harder surface would cause more bouncing. Would more bouncing increase or decrease the relative fairness?

delecti2• 7 years ago

One common test of a die's fairness is floating it in salt-water, which allows any irregularity in the weight distribution to show itself. From that, intuitively I would assume that zero resistance (as much bouncing as possible/needed) would result in the unfairness making itself most apparent. Meanwhile, zero bouncing would cause the die to stick where it lands, making any unfairness the result of how it was thrown, and it's easier to cause a lot of randomness in that regard.

That said, I'm not sure that's generalizable to more realistic amounts of bouncing ("only a bit of bouncing" as opposed to "none at all", and "kinda a lot of bouncing" as opposed to "effectively zero resistance").

grawprog• 7 years ago

I've never actually heard of the salt water test. It makes sense thinking about it. I got a bag of dice from my dad, from his d&d days, from when he was younger than me. There's a huge mix of some really weird dice in there. They're fairly worn, some of the numbers aren't visible any more, and their original quality ranges wildly. I wouldn't mind dropping them all in a bucket of salt water to see now. I've drawn my own conclusions about them over the years of using them, it'd be interesting to see how well they match up.

Also, i wonder how my dad's homemade d20, made out of a double d10(d20 with 0-9 twice, 0's used as 10 and 20) with half the numbers coloured red(11-20 is red), with a pen, would rank up, it was likely just done randomly.

ryanmcbride2• 7 years ago

As far as I know continued bouncing would give the d20 more time to find its center, so it would be less random. That's pretty much the whole idea behind Gamescience dice. They aren't tumbled, so the edges are sharp and sometimes there's exposed mold flashing, but they stop rolling faster, meaning they're less likely to find their center

im3w1l• 7 years ago

Would less tumbling make it easier for a skilled thrower to control the outcome?

appleiigs2• 7 years ago

The mechanical rolling and computer vision is impressive, but wish he had noted if the results were statistically significant. Just a final touch to the article. At 100-150 rolls per face, my gut is saying no. I guess I'm going to have to whip up a couple loops in python after work to satisfy my curiosity.

jcranmer2• 7 years ago

The usual gut reaction for statistical significance is that n*p should be 20, or 20 rolls per face. 100-150 should be statistically significant.

eterm3• 7 years ago

You can't assign significance to a sample size alone.

A sample size of 10 can be significant (if it were 10 1's for example), and a sample size of 100,000 can be not significant, for example if you were to roll 4,953 1's.

eterm3• 7 years ago

Yes, if these graphs had confidence intervals they would be a lot more informative.

markfickett3• 7 years ago

As the author -- I agree! I did some preliminary work to make confidence intervals, but didn't get around to updating the writeup.

These are my draft updated charts: http://www.markfickett.com/tmp/dice/chart.html

I used bootstrapped subsamples to generate the confidence intervals: https://github.com/markfickett/dicehistogram/blob/master/sum...

Fomite2• 7 years ago

One of the dangers, especially with statistical tests of uniformity, is that they often over detect departures from uniformity when using large samples.

enthdegree• 7 years ago

Would have liked to have seen a bootstrap estimate of the die's empirical entropy to see how much it is lacking against uniform.

markfickett3• 7 years ago

If you want to do that analysis, I'd be very interested to see it / hear how you do it. All the data is in the GitHub repo, for example https://github.com/markfickett/dicehistogram/blob/master/dat... lists the rolls for one test.

I ran bootstrapped subsampling to estimate confidence intervals (see comment above), not sure how similar that is to what you're asking about.

amiheines• 7 years ago

This reminds me of an old post with a dice rolling machine for a gaming site capable of producing 1.3 million dice rolls per day, http://gamesbyemail.com/News/DiceOMatic

badfrog• 7 years ago

Currently, GamesByEmail.com uses some 80,000+ die rolls for play in games like Backgammon, Gambit (a RISK clone), W.W.II (an Axis & Allies clone) and others. To generate the die rolls, I have used Math.random, Random.org and other sources, but have always received numerous complaints that the dice are not random enough.

That's a super cool machine, but the justification seems a bit silly. The randomization library in any programming language should be good enough for casual games, and random.org uses atmospheric noise which is almost certainly more random than dice: https://www.random.org/history/

aidenn06• 7 years ago

This is to make players happy, not to provide better randomness. Many players will not trust any random data coming from a computer.

eterm3• 7 years ago

As an approximation, we can estimate each face with an approximation to the binomial at looking at where the cut off is for rejections at p=0.05.

If you're looking at a single face,

With 2000 rolls, you would expect a range of 81-120. (0.0405- 0.0600)

At 3000 rolls, that "narrows"\* to 127-174 (0.0423 - 0.580)

At just 100 rolls, anywhere between 1 and 10 occurences looks fair.

However, it would be better to do a proper chi-squared test, this was just illustrative, so let's do that.

Let's take the chessex opaque purple, which looks like it has 8300 rolls. By our approximations above, we expect to see rolls between 377 and 454.

In our actual data we appear to have a minimum of 313 with face13, and a maximum of 531 with face17.

So let's do a pearson's chi-squared test. Rolling 8300 times we expect 415 for each face.

We calculate for each observation, the difference between that and the expected value, and divide by the expected value, and then sum over all faces.

This gives a value of 155.3108 . We then have to compare this to the chi-squared test for 19 degrees of freedom. (There are 19 degrees of freedom because we have 20 faces, so after we have 19 results, the 20th must be fixed by being 8300 minus the sum of the first 19 faces).

Digging out our statistical tables (you DO have statistical tables right?), and lookup at 19 degrees of freedom, we can see 155 far exceeds even the p=0.01 level.

So we can conclude that the chessex opaque purple die rolled here is biased. (Or the die-roller is).

\* It narrows in proportion to the total, the absolute margin is wider. This is something that people often forget when dealing with the law of large numbers.

jcranmer2• 7 years ago

So we can conclude that the chessex opaque purple die rolled here is biased. (Or the die-roller is).

We could use conditional probabilities to determine if the die is biased or if the roller is biased, I think: see if P(face is 19 | face was n before roll) = P(face is 19) by statistical hypothesis testing. Not that the data we have tells whether or not.

appleiigs2• 7 years ago

Python3

    import random, statistics

    num_of_sims = 10000
    num_of_rolls = 3000
    results = []

    for s in range(num_of_sims):

        sum_of_rolls = 0

        # roll 20 sided dice
        for r in range(num_of_rolls):
            sum_of_rolls += random.randint(1,20)

        # keep track of the average value
        results.append(sum_of_rolls / num_of_rolls)

    print("ave: ", statistics.mean(results)) # which is 10.49915
    print("stdev: ", statistics.stdev(results)) # which is 0.10492

Now where did I put my statistical tables?

viraptor• 7 years ago

(There are 19 degrees of freedom because we have 20 faces, so after we have 19 results, the 20th must be fixed by being 8300 minus the sum of the first 19 faces).

I've read the degrees of freedom in statistics explained so many times without actually understanding it. Now I get it. It's that simple. Thank you!

lmilcin2• 7 years ago

I have worked, about 15 years ago, on a contract for a company that amongst other things produced automated roulette tables.

They had a large hall packed with those that would constantly spin up, drop the ball and record results. There was mathematician employed to check series for any statistical anomalies. I had few chats with the guy, I was quite impressed the level of detail and care to make sure the wheels are perfectly symmetrical and fair.

Most of the cost of the machine goes into making the wheel symmetrical. I remember something like 20 or 30 thousand dollars spent on the single piece of metal that becomes the wheel.

aidenn06• 7 years ago

It's interesting they put so much work into that because roulette tables have a ~5% house edge, so even a fairly large bias wouldn't cost the house.

DuskStar• 7 years ago

Until that 5% edge turns out to be a 7% edge (thanks to the bias) and the relevant regulators come down on you like a ton of bricks for cheating your players.

jaggederest• 7 years ago

Yes, from what I understand, the casino edge is required to be extremely precise. Returning too much money to gamblers is penalized just as harshly as returning too little.

This is why casinos like you to gamble more, regardless of what form, because their edge is fixed by regulators. Only by increasing volume can they increase returns.

lmilcin2• 7 years ago

When in operation the cost of the hardware and development returns in just a few days or weeks at most.

mjlee• 7 years ago

Edward Thorp and Claude Shannon would disagree:

https://www.engadget.com/2013/09/18/edward-thorp-father-of-w...

tinus_hn• 7 years ago

I think it’s pretty important for gamblers that the game is fair so they don’t feel cheated when they lose.

hajile• 7 years ago

https://www.snopes.com/fact-check/the-full-monte/

sd_mikey• 7 years ago

I would love to see this experiment done with the d20 from The Dice Lab. They make their d20 dice with "ideally-balanced vertex sums while retaining the opposite-side numbering convention". They explain why this makes for a bit fairer dice here. https://mathartfun.com/thedicelab.com/BalancedStdPoly.html

thaumasiotes• 7 years ago

They explain why this makes for a bit fairer dice here.

Well... they explain why the opposite-side numbering convention makes for fairer dice. They don't say anything at all about balanced vertex sums other than "we believe it's important".

Just compare the reasoning:

If a die is unintentionally oblate (slightly flattened on opposing sides), the flatter regions are more likely to turn up when the die is tossed. If these two opposite numbers were 19 and 20 for example, then the die would on average roll high, since these two numbers would come up too often. Having the two numbers add to 21 avoids any such bias in the average number rolled. For this reason, the opposite-side numbering convention improves fairness.

Equally important in our opinion is balancing of the vertex sums.

This does not give me confidence that the vertex sums matter.

no_identd• 7 years ago

The paper describing these dies might help then:

http://www2.oberlin.edu/math/faculty/bosch/nbd.pdf Bosch, Robert; Fathauer, Robert, Segerman, Henry - Numerically Balanced Dice (2016)

(btw., here's the about page for The Die Lab: https://www.mathartfun.com/thedicelab.com/DiceDesign.html)

More various stuff on fair dice:

On fair but irregular plyhedral dice:

http://statweb.stanford.edu/~cgates/PERSI/papers/fairdice.pd... Diaconis, Persi; Keller, Joseph B. - Fair Dice (1989)

https://mathoverflow.net/questions/46684/fair-but-irregular-...

https://pp.bme.hu/ar/article/download/7607/6570/ - Várkonyi, Péter L. - The Secret of Gambling with Irregular Dice: Estimating the Face Statistics of Polyhedra (2014)

https://web.archive.org/web/20110925191300/http://blog.eqnet...

Note: The link to http://maths.dur.ac.uk:80/~dma0cvj/mathphys/supplements/supp... in the comments there is broken and the archived version doesn't have the images, but the PDF copy survives in the archive. (One can find the other PDFs from that page here, by filtering: https://web.archive.org/web/*/http://www.maths.dur.ac.uk/~dm...)

"Polyisohedral" dices: * http://loki3.com/poly/polyisohedra.html * http://loki3.com/poly/fair-dice.html

http://www.mathpuzzle.com/MAA/37-Fair%20Dice/mathgames_05_16...

https://web.archive.org/web/20050602020925/http://www.geocit...

https://savevsdragon.blogspot.com/2011/11/brief-history-of-p...

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.78.03... How random is dice tossing?

aidenn06• 7 years ago

Interesting that this confirms other findings that the gamescience dice must have the sprue-stub removed for fair rolling. This is intuitively true, but contrary to Gamescience's marketing.

aidenn06• 7 years ago

It would be interesting to take some of the unfair dice and sand down the faces until they are equal diameters. That's a big time commitment though.

nullc• 7 years ago

Von Neumann's algorithm for simulating a fair coin from a coin which is arbitrarily biased (but with independent throws) has moral analogs for any number of faces. By using more state you can also extract more data per throw.

Pieter Wuille created a table based implementation for a d6: https://gist.github.com/sipa/1913cf8aae565ddad0d1de7f2e9f7f3... though it isn't terribly efficient -- extracting only 2.722 bits per 4 roles, instead of the 10.34 which is theoretically possible -- because the table becomes fairly large fairly fast. d20 would be even worse.

https://gist.github.com/sipa/1621c40775007f1c27a39b608a765b1... is a similar implementation for two sides that extracts more than half the theoretical entropy.

If your application wanted uniform d20 throws a table that converted independent but biased d20 throws into unbiased d20 throws would be possible (though like above it would be inefficient unless it were very big.)

Calashle0202• 7 years ago

Very nice work! I am not sure what method of analysis would be the most appropriate, but the sequence matrix deserves a closer look. You mention the possibility of one side being preferentially followed by another one, but you only investigate the simple case of the two sides being equal (preference for the diagonal). However, the correlation could be less obvious, such as one side being followed by its opposite, or by an adjacent one.

purplezooey• 7 years ago

That's pretty neat. Wonder if he wore a hole in the wood veneered desk.

zimpenfish• 7 years ago

For the graphs showing "normalised frequencies", I'd drop the "based at zero" bars and draw them from 1 instead. You'd lose a lot of orange ink that's distracting and show the deviation much more clearly.

Something like https://rjp.is/dice-graph.png (best I can do with Preview, sorry!)

En_gr_Student• 7 years ago

I wonder about auto-correlation and repeated sequences of runs. If it isn't totally random, then it is partly not random. What is the nature of the non-randomness?

How Fair Is My D20? (2015)

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