Nick Beaver

1.2 Modelling Competitor + Strategy Probabilities in Trading Card Games

In the previous post, we discussed our decision to use Bayesian Inference as the preferred method to compute the win probabilities for different players and decks.

We will now expand on how Bayes’ Theorem can help us do this.

We’re going to take for granted that the probabilities here are examples only and that, given this demonstration, we’re also taking for granted that someway, somehow, all the probabilities have been provided to us.

In later parts of this project, we’ll tackle actually getting to the point where we can create such matchups with our own computed proabilities.

The Competitor + Strategy Matrix

Assume we have 8 Competitors (C₁…C₈) and 8 Strategies (S₁…S₈).

We might have a table that looks like this:

	C1	C2	C3	C4	C5	C6	C7	C8
S1	0.331	0.529	0.450	0.626	0.183	0.649	0.257	0.151
S2	0.507	0.271	0.537	0.200	0.258	0.513	0.119	0.330
S3	0.512	0.242	0.287	0.253	0.613	0.393	0.179	0.574
S4	0.677	0.540	0.694	0.610	0.406	0.138	0.209	0.395
S5	0.654	0.222	0.492	0.630	0.569	0.119	0.144	0.397
S6	0.297	0.544	0.534	0.262	0.243	0.432	0.696	0.352
S7	0.351	0.600	0.705	0.119	0.365	0.719	0.399	0.518
S8	0.415	0.342	0.477	0.110	0.205	0.432	0.493	0.134

This table tells us how probable a given Competitor, using a given Strategy is to win, in general. This would be a probability against a disembodied opponent: the probability isn’t conditioned on facing another person or deck. It’s most likely the long term average for the Competitors and their Strategies (wins/losses) expressed as a ratio.

Reading the table, above, we can see that Competitor 2 using Strategy 4 has a .540 probability of winning any game.

But what is this Competitor using this Strategy’s probability of winning against another Competitor and Strategy combination?

Computing Win Probabilities

Last time, we reviewed Bayes’ Theorem in the abstract:

[math] P(A|B)=\frac{P(A)P(B|A)}{P(B)} [/math]

We decided that the win probability for Player A against Player B was a conditional probability, or that this probability was conditioned on the circumstances of these two opponents facing one another.

It wouldn’t make sense for us simply to give a probability of Player A (or Player B) winning in isolation. This is what our table, above, does.

It doesn’t, however, give us a probability of a Competitor + Strategy combination against another Competitor + Strategy combination, which is what we want.

Let’s take the case of Competitor 3 using Strategy 5 (C₃+S₅) playing against Competitor 7 using Strategy 2 (C7+S2).

How do we calculate the probability that C₃+S₅ win a match against C7+S2?

We set up our equation thusly:

[math] P(C3+S5|C7+S3)=\frac{P(C3+S5)P(C7+ S3|C3+S5)}{C7+ S5} [/math]

Let’s examine each of the variables in turn.

P(C₃+S₅ | C₇ + S₃)

This is the win probability of C₃+S₅ against C₇+S₃, which is what we’re looking for.

We won’t know this until the end!

P(C₃+S₅)

Referring to our table above, we find that the probability of C₃+S₅ winning any match is 0.492.

Thus, the value of P(C₃+S₅) is 0.492 in our formula.

P(C₇+S₃|C₃+S₅)

This one is a little trickier. This is the probability that C7+S3 win against C₃+S₅.

And if we think about it, is the opposite of what we’re looking for, P(C₃+S₅|C₇+S₃)!

If we knew this now, we’d be done, because to find the other probability, we simply subtract it from 1. This is something we’ll return to shortly.

For now, let’s leave this as a mystery.

P(C₇+S₃)

This is simply the probability that C7+S3 win any match.

Consulting our table, we see that this is 0.179.

So we’ll use that.

Missing Information

So far, our revised formula looks like this:

[math] P(C3+S5| C7+ S3)= \frac{0.492*P(C7+ S3|C3+S5)}{P(0.179)}[/math]

But what about that pesky P(C₇+S₃|C₃+S₅)?

If we could calculate that, we’d know P(C₃+S₅ | C₇+ S₃), our desired answer, too.

Let’s find an easier way to make this calculation.

Using Excel and Basic Algebra

Let’s take another look at our Competitor and Strategy table:

We know that C₃+S₅ has an overall win probability of 0.492 and that C₇+S₃ has an overall win probability of 0.179.

To make our life easier, we will constrain the probability space to the universe that contains only these two match ups. That is, to say, that 1 (or 100%) will be the combined total probabilities for these two Competitors + Strategies.

We can think of this as a ratio:

[math] Win Probability= \frac{P(C3+C5)}{P(C3+C5) + P(C7+ S3)}[/math]

This pits the probability of C₃+C₅ against the combined probability of C₃+C₅ and C₇+ S₃.

We get the following:

[math] \frac{0.492}{0.492+0.179}=0.733[/math]

This works because the probability that C₃+C₅ win any match is a fraction of the combined probabilities that C₃+C₅ win any match and C₇+S₃ win any match.

In fact, we can put all of this back into Bayes’ Theorem to prove our case.

Remember, that if the P(C₃+C₅|P(C₇ + S₃)) = 0.733, then the probability that the other player win is exactly 1 – this amount, or P(C₇₌ + S₃|C₃+C₅) = 1 – 0.733 = 0.267.

This is because all probabilities must sum to 1 (absolute certainty). All potential outcomes represent the whole of possible outcomes.

[math]P(C3+S5| C7+ S3)=\frac{0.492*0.267}{0.179} =0.733[/math]

All we have to do is divide C_n+S_nby C_n+S_ncombined with C_k+S_k.

This is much easier.

What we’ve done here is normalize the probabilities of the two competitors such that their conditional probabilities sum to 1, like this:

The Expanded C_n+S_n Matrix

To carry this theory into action, we pit each and every combination of Competitors + Strategies (C_n+S_n) against each other in the same way as we did above for C₃+C₅ against C₇+S₃.

Our previous win probability table has 8 rows and 8 columns. This one has 64 rows and 64 columns.

Wins? ↓	C1+S1	C1+S2	C1+S3	C1+S4	C1+S5	C1+S6	C1+S7	C1+S8	C2+S1	C2+S2	C2+S3	C2+S4	C2+S5	C2+S6	C2+S7	C2+S8	C3+S1	C3+S2	C3+S3	C3+S4	C3+S5	C3+S6	C3+S7	C3+S8	C4+S1	C4+S2	C4+S3	C4+S4	C4+S5	C4+S6	C4+S7	C4+S8	C5+S1	C5+S2	C5+S3	C5+S4	C5+S5	C5+S6	C5+S7	C5+S8	C6+S1	C6+S2	C6+S3	C6+S4	C6+S5	C6+S6	C6+S7	C6+S8	C7+S1	C7+S2	C7+S3	C7+S4	C7+S5	C7+S6	C7+S7	C7+S8	C8+S1	C8+S2	C8+S3	C8+S4	C8+S5	C8+S6	C8+S7	C8+S8
C1+S1	0.5	0.394988067	0.392645314	0.328373016	0.336040609	0.527070064	0.485337243	0.443699732	0.384883721	0.549833887	0.577661431	0.380022962	0.598553345	0.378285714	0.355531686	0.491827637	0.423815621	0.381336406	0.535598706	0.322926829	0.40218712	0.38265896	0.319498069	0.409653465	0.345872518	0.623352166	0.566780822	0.351753454	0.344432882	0.558178752	0.735555556	0.750566893	0.643968872	0.56196944	0.350635593	0.449118046	0.367777778	0.576655052	0.475574713	0.617537313	0.337755102	0.392180095	0.45718232	0.70575693	0.735555556	0.433813893	0.315238095	0.433813893	0.56292517	0.735555556	0.649019608	0.612962963	0.696842105	0.322297955	0.453424658	0.401699029	0.686721992	0.50075643	0.365745856	0.455922865	0.45467033	0.484626647	0.389870436	0.711827957
C1+S2	0.605011933	0.5	0.497546614	0.428209459	0.436692506	0.630597015	0.590909091	0.54989154	0.489382239	0.651670951	0.676902537	0.484240688	0.695473251	0.482397716	0.45799458	0.597173145	0.529780564	0.485632184	0.638539043	0.42214821	0.507507508	0.4870317	0.418316832	0.515243902	0.447484554	0.717114569	0.667105263	0.45389436	0.44591029	0.659297789	0.809904153	0.82171799	0.734782609	0.662745098	0.452678571	0.555312158	0.471189591	0.676	0.581422018	0.712078652	0.438581315	0.497058824	0.563333333	0.786046512	0.809904153	0.539936102	0.413539967	0.539936102	0.663612565	0.809904153	0.739067055	0.708100559	0.778801843	0.421446384	0.559602649	0.507	0.770516717	0.605734767	0.469010176	0.562084257	0.560840708	0.590221187	0.494634146	0.790951638
C1+S3	0.607354686	0.502453386	0.5	0.430613961	0.439108062	0.632880099	0.593279258	0.55231931	0.491834774	0.653895275	0.679045093	0.486692015	0.697547684	0.484848485	0.460431655	0.599531616	0.532224532	0.488083889	0.640801001	0.424543947	0.509960159	0.489483748	0.420706656	0.517694641	0.449912127	0.719101124	0.669281046	0.456327986	0.448336252	0.661498708	0.81141046	0.823151125	0.736690647	0.664935065	0.455111111	0.557734205	0.473635523	0.678145695	0.583808438	0.714086471	0.440999139	0.499512195	0.565745856	0.787692308	0.81141046	0.542372881	0.415922015	0.542372881	0.66579974	0.81141046	0.740955137	0.710124827	0.780487805	0.42384106	0.562019759	0.509452736	0.77224736	0.60807601	0.47145488	0.564498346	0.563256326	0.592592593	0.497087379	0.792569659
C1+S4	0.671626984	0.571790541	0.569386039	0.5	0.50864012	0.695071869	0.658560311	0.61996337	0.561359867	0.714135021	0.736670294	0.556285949	0.753058954	0.554463554	0.530148786	0.66437684	0.600709849	0.557660626	0.702282158	0.493800146	0.579127459	0.559042114	0.489869754	0.586655113	0.519570223	0.771949829	0.727956989	0.526029526	0.517980107	0.720979766	0.850502513	0.860228717	0.787209302	0.724064171	0.524806202	0.62511542	0.543338684	0.735869565	0.649712092	0.767573696	0.510558069	0.568907563	0.63271028	0.830674847	0.850502513	0.610459874	0.48495702	0.610459874	0.7248394	0.850502513	0.79088785	0.764108352	0.824604141	0.493080845	0.629182156	0.578632479	0.81763285	0.672293942	0.541167066	0.631529851	0.630353818	0.657920311	0.566527197	0.834771887
C1+S5	0.663959391	0.563307494	0.560891938	0.49135988	0.5	0.687697161	0.650746269	0.611786717	0.552831784	0.707027027	0.729910714	0.547738693	0.746575342	0.54590985	0.5215311	0.656626506	0.592391304	0.549118388	0.695005313	0.485163205	0.570680628	0.550505051	0.481236203	0.578249337	0.5109375	0.765807963	0.721058434	0.517405063	0.509345794	0.713973799	0.846054334	0.856020942	0.781362007	0.717105263	0.516179953	0.616981132	0.534750613	0.72909699	0.641805692	0.761350407	0.501918649	0.560411311	0.624641834	0.825757576	0.846054334	0.602209945	0.476329206	0.602209945	0.717892426	0.846054334	0.785114046	0.757821553	0.819548872	0.484444444	0.621082621	0.570183086	0.81242236	0.664634146	0.53257329	0.623450906	0.62226451	0.650099404	0.558020478	0.829949239
C1+S6	0.472929936	0.369402985	0.367119901	0.304928131	0.312302839	0.5	0.458333333	0.417134831	0.359564165	0.522887324	0.551020408	0.35483871	0.572254335	0.353151011	0.331103679	0.464788732	0.397590361	0.356115108	0.508561644	0.299697275	0.376425856	0.357400722	0.296407186	0.38372093	0.321776815	0.597585513	0.54	0.327453142	0.32038835	0.531305903	0.713942308	0.72972973	0.61875	0.535135135	0.326373626	0.422475107	0.34295612	0.55	0.448640483	0.591633466	0.313953488	0.366666667	0.430434783	0.682758621	0.713942308	0.407407407	0.292322835	0.407407407	0.536101083	0.713942308	0.62394958	0.586956522	0.673469388	0.299093656	0.426724138	0.375949367	0.662946429	0.473684211	0.340987371	0.429190751	0.42795389	0.457627119	0.364417178	0.689095128
C1+S7	0.514662757	0.409090909	0.406720742	0.341439689	0.349253731	0.541666667	0.5	0.458224543	0.398863636	0.564308682	0.591905565	0.393939394	0.612565445	0.392178771	0.369085174	0.506493506	0.438202247	0.39527027	0.55015674	0.335885167	0.416370107	0.396610169	0.332386364	0.423913043	0.35926305	0.637023593	0.581125828	0.365244537	0.357798165	0.572593801	0.746808511	0.761388286	0.657303371	0.57635468	0.364107884	0.463672391	0.381521739	0.590909091	0.490223464	0.631294964	0.351	0.40625	0.471774194	0.717791411	0.746808511	0.448275862	0.328037383	0.448275862	0.577302632	0.746808511	0.662264151	0.626785714	0.709090909	0.335243553	0.468	0.415876777	0.699203187	0.515418502	0.379459459	0.470509383	0.469251337	0.499288762	0.403912543	0.72371134
C1+S8	0.556300268	0.45010846	0.44768069	0.38003663	0.388213283	0.582865169	0.541775457	0.5	0.439618644	0.604956268	0.631659056	0.434554974	0.651491366	0.43274244	0.408866995	0.548216645	0.479768786	0.43592437	0.591168091	0.374211001	0.45755237	0.437302424	0.370535714	0.465246637	0.398655139	0.674796748	0.621257485	0.404878049	0.397129187	0.612998523	0.777153558	0.79047619	0.693979933	0.616641902	0.403696498	0.505481121	0.421747967	0.630699088	0.532051282	0.669354839	0.390037594	0.447198276	0.513613861	0.75045208	0.777153558	0.489964581	0.365961199	0.489964581	0.617559524	0.777153558	0.698653199	0.665064103	0.742397138	0.373537354	0.50982801	0.457048458	0.733215548	0.55704698	0.419615774	0.512345679	0.511083744	0.5410691	0.444801715	0.755919854
C2+S1	0.615116279	0.510617761	0.508165226	0.438640133	0.447168216	0.640435835	0.601136364	0.560381356	0.5	0.66125	0.68612192	0.494855005	0.704394141	0.493010252	0.468556244	0.607347876	0.540347293	0.496247655	0.648284314	0.432542927	0.518119491	0.497648166	0.428687196	0.52584493	0.458008658	0.725651578	0.676470588	0.464442493	0.456427955	0.668773704	0.816358025	0.827856025	0.742977528	0.672172808	0.463222417	0.565775401	0.481785064	0.685233161	0.591722595	0.720708447	0.449066214	0.507677543	0.573752711	0.793103448	0.816358025	0.550468262	0.423878205	0.550468262	0.67302799	0.816358025	0.747175141	0.716802168	0.786032689	0.431836735	0.570043103	0.517612524	0.777941176	0.615832363	0.479601088	0.572510823	0.571274298	0.60045403	0.505253104	0.797888386
C2+S2	0.450166113	0.348329049	0.346104725	0.285864979	0.292972973	0.477112676	0.435691318	0.395043732	0.33875	0.5	0.528265107	0.334155364	0.54969574	0.332515337	0.311136625	0.442088091	0.375866852	0.33539604	0.485663082	0.280829016	0.355176933	0.336645963	0.277663934	0.362299465	0.302118172	0.57537155	0.517175573	0.307604994	0.300776915	0.508442777	0.694871795	0.711286089	0.5969163	0.512287335	0.306561086	0.400295421	0.322619048	0.527237354	0.426100629	0.569327731	0.294565217	0.345663265	0.40813253	0.662591687	0.694871795	0.385490754	0.273737374	0.385490754	0.513257576	0.694871795	0.602222222	0.564583333	0.653012048	0.28024819	0.404477612	0.354712042	0.642180095	0.450915141	0.320710059	0.406906907	0.405688623	0.434991974	0.34347275	0.669135802
C2+S3	0.422338569	0.323097463	0.320954907	0.263329706	0.270089286	0.448979592	0.408094435	0.368340944	0.31387808	0.471734893	0.5	0.309462916	0.521551724	0.307888041	0.287410926	0.414383562	0.349710983	0.310654685	0.457466919	0.258547009	0.329700272	0.31185567	0.255543823	0.336578581	0.278801843	0.547511312	0.488888889	0.284037559	0.277522936	0.48015873	0.670360111	0.6875	0.569411765	0.484	0.283040936	0.37345679	0.298397041	0.498969072	0.398682043	0.541387025	0.271604938	0.320529801	0.381102362	0.636842105	0.670360111	0.359050445	0.25182102	0.359050445	0.48496994	0.670360111	0.574821853	0.536585366	0.626943005	0.257995736	0.377535101	0.329251701	0.615776081	0.423076923	0.296568627	0.379905808	0.378716745	0.407407407	0.318421053	0.643617021
C2+S4	0.619977038	0.515759312	0.513307985	0.443714051	0.452261307	0.64516129	0.606060606	0.565445026	0.505144995	0.665844636	0.690537084	0.5	0.708661417	0.498154982	0.473684211	0.612244898	0.545454545	0.501392758	0.652962515	0.437601297	0.523255814	0.502793296	0.43373494	0.530973451	0.463121784	0.72972973	0.680958386	0.469565217	0.461538462	0.673316708	0.819423369	0.830769231	0.746887967	0.676691729	0.468343452	0.570824524	0.486925158	0.689655172	0.596685083	0.724832215	0.454163162	0.512820513	0.578778135	0.796460177	0.819423369	0.555555556	0.428911835	0.555555556	0.677540778	0.819423369	0.751043115	0.720961282	0.789473684	0.436893204	0.575079872	0.522749274	0.781476122	0.620689655	0.484739677	0.577540107	0.576307364	0.605381166	0.510396975	0.801186944
C2+S5	0.401446655	0.304526749	0.302452316	0.246941046	0.253424658	0.427745665	0.387434555	0.348508634	0.295605859	0.45030426	0.478448276	0.291338583	0.5	0.289817232	0.270072993	0.393617021	0.330357143	0.292490119	0.436149312	0.242358079	0.31092437	0.293650794	0.239482201	0.317596567	0.261792453	0.526066351	0.467368421	0.266826923	0.26056338	0.458677686	0.651026393	0.668674699	0.548148148	0.4625	0.265868263	0.353503185	0.280657396	0.477419355	0.378194208	0.519906323	0.254879449	0.302040816	0.36097561	0.616666667	0.651026393	0.339449541	0.235919235	0.339449541	0.463465553	0.651026393	0.55361596	0.515081206	0.606557377	0.241830065	0.357487923	0.31048951	0.595174263	0.402173913	0.278894472	0.359805511	0.358642973	0.386759582	0.3	0.623595506
C2+S6	0.621714286	0.517602284	0.515151515	0.445536446	0.45409015	0.646848989	0.607821229	0.56725756	0.506989748	0.667484663	0.692111959	0.501845018	0.710182768	0.5	0.475524476	0.613995485	0.547283702	0.503237743	0.654632972	0.439418417	0.525096525	0.504638219	0.435548439	0.53281097	0.464957265	0.731182796	0.682559598	0.471403813	0.463373083	0.674937965	0.820512821	0.831804281	0.748280605	0.678304239	0.470181504	0.572631579	0.488769093	0.691232529	0.598459846	0.726301736	0.455993294	0.514664144	0.580576307	0.797653959	0.820512821	0.557377049	0.430720507	0.557377049	0.679151061	0.820512821	0.75242047	0.722443559	0.790697674	0.438709677	0.576882291	0.524590164	0.782733813	0.622425629	0.486583184	0.579339723	0.578108395	0.607142857	0.512241055	0.802359882
C2+S7	0.644468314	0.54200542	0.539568345	0.469851214	0.4784689	0.668896321	0.630914826	0.591133005	0.531443756	0.688863375	0.712589074	0.526315789	0.729927007	0.524475524	0.5	0.636942675	0.571428571	0.527704485	0.67643743	0.463678516	0.549450549	0.529100529	0.459770115	0.557103064	0.489396411	0.75	0.703399766	0.495867769	0.487804878	0.696055684	0.83449235	0.845070423	0.766283525	0.699300699	0.494641385	0.596421471	0.513259196	0.711743772	0.621761658	0.745341615	0.480384307	0.539083558	0.604229607	0.81300813	0.83449235	0.581395349	0.454890068	0.581395349	0.700116686	0.83449235	0.770218228	0.741656366	0.806451613	0.462962963	0.600600601	0.54894785	0.798934754	0.64516129	0.511073254	0.603015075	0.601805416	0.630252101	0.53667263	0.817438692
C2+S8	0.508172363	0.402826855	0.400468384	0.33562316	0.343373494	0.535211268	0.493506494	0.451783355	0.392652124	0.557911909	0.585616438	0.387755102	0.606382979	0.386004515	0.363057325	0.5	0.431818182	0.389078498	0.543720191	0.33011583	0.410071942	0.390410959	0.326647564	0.417582418	0.353305785	0.63099631	0.574789916	0.359243697	0.351851852	0.566225166	0.74186551	0.756637168	0.651428571	0.57	0.358115183	0.457219251	0.375411636	0.584615385	0.483734088	0.625228519	0.345105954	0.4	0.465306122	0.7125	0.74186551	0.441860465	0.322337418	0.441860465	0.570951586	0.74186551	0.656429942	0.620689655	0.703703704	0.329479769	0.461538462	0.409580838	0.693711968	0.508928571	0.373362445	0.464043419	0.462787551	0.492795389	0.397674419	0.718487395
C3+S1	0.576184379	0.470219436	0.467775468	0.399290151	0.407608696	0.602409639	0.561797753	0.520231214	0.459652707	0.624133148	0.650289017	0.454545455	0.669642857	0.452716298	0.428571429	0.568181818	0.5	0.455927052	0.610583446	0.393356643	0.477707006	0.457317073	0.38961039	0.485436893	0.418215613	0.692307692	0.640113798	0.424528302	0.416666667	0.632022472	0.79086116	0.803571429	0.710900474	0.63559322	0.423330198	0.525700935	0.441609421	0.649350649	0.552147239	0.687022901	0.409463148	0.46728972	0.533807829	0.765306122	0.79086116	0.510204082	0.384944397	0.510204082	0.636492221	0.79086116	0.715421304	0.682852807	0.757575758	0.392670157	0.530035336	0.477200424	0.74875208	0.576923077	0.439453125	0.532544379	0.531286895	0.561097257	0.464876033	0.770547945
C3+S2	0.618663594	0.514367816	0.511916111	0.442339374	0.450881612	0.643884892	0.60472973	0.56407563	0.503752345	0.66460396	0.689345315	0.498607242	0.707509881	0.496762257	0.472295515	0.610921502	0.544072948	0.5	0.651699029	0.436230707	0.521865889	0.50140056	0.43236715	0.529585799	0.461736887	0.728629579	0.679746835	0.468177855	0.460154242	0.672090113	0.818597561	0.829984544	0.745833333	0.675471698	0.466956522	0.569459173	0.485533454	0.688461538	0.595343681	0.723719677	0.452782462	0.511428571	0.577419355	0.795555556	0.818597561	0.554179567	0.427547771	0.554179567	0.676322418	0.818597561	0.75	0.719839142	0.788546256	0.435523114	0.573717949	0.521359223	0.780523256	0.619377163	0.483348335	0.576180258	0.574946467	0.604049494	0.509004739	0.800298063
C3+S3	0.464401294	0.361460957	0.359198999	0.297717842	0.304994687	0.491438356	0.44984326	0.408831909	0.351715686	0.514336918	0.542533081	0.347037485	0.563850688	0.345367028	0.32356257	0.456279809	0.389416554	0.348300971	0.5	0.292558614	0.368421053	0.349573691	0.289314516	0.37565445	0.314348302	0.589322382	0.531481481	0.319955407	0.312977099	0.52276867	0.706896552	0.722921914	0.610638298	0.526605505	0.318888889	0.414141414	0.335280374	0.541509434	0.440184049	0.583333333	0.306623932	0.35875	0.422058824	0.675294118	0.706896552	0.399165508	0.28528827	0.399165508	0.527573529	0.706896552	0.615879828	0.578629032	0.665893271	0.291963377	0.418367347	0.367948718	0.655251142	0.465153971	0.333333333	0.420821114	0.419590643	0.44913928	0.356521739	0.681710214
C3+S4	0.677073171	0.57785179	0.575456053	0.506199854	0.514836795	0.700302725	0.664114833	0.625788999	0.567457073	0.719170984	0.741452991	0.562398703	0.757641921	0.560581583	0.536321484	0.66988417	0.606643357	0.563769293	0.707441386	0.5	0.585160202	0.56514658	0.49606862	0.59265585	0.525757576	0.776286353	0.732840549	0.532208589	0.524169184	0.725941423	0.853628536	0.86318408	0.791334094	0.728991597	0.530986993	0.630909091	0.549485352	0.740661686	0.655335222	0.771968854	0.516753537	0.574979287	0.638454462	0.834134615	0.853628536	0.61634103	0.491153574	0.61634103	0.729758149	0.853628536	0.794959908	0.76854928	0.828162291	0.499280576	0.63494968	0.584667228	0.821301775	0.677734375	0.547318612	0.63728191	0.636113657	0.663479924	0.572607261	0.838164251
C3+S5	0.59781288	0.492492492	0.490039841	0.420872541	0.429319372	0.623574144	0.583629893	0.54244763	0.481880509	0.644823067	0.670299728	0.476744186	0.68907563	0.474903475	0.450549451	0.589928058	0.522292994	0.478134111	0.631578947	0.414839798	0.5	0.479532164	0.411027569	0.507739938	0.440071556	0.710982659	0.660402685	0.44646098	0.438502674	0.652519894	0.805237316	0.817275748	0.728888889	0.656	0.445248869	0.547884187	0.463713478	0.669387755	0.574095683	0.705882353	0.431200701	0.489552239	0.555932203	0.780952381	0.805237316	0.532467532	0.406275805	0.532467532	0.656875834	0.805237316	0.733233979	0.701854494	0.773584906	0.414141414	0.552188552	0.499492386	0.765163297	0.598540146	0.461538462	0.554678692	0.553430821	0.582938389	0.487128713	0.785942492
C3+S6	0.61734104	0.5129683	0.510516252	0.440957886	0.449494949	0.642599278	0.603389831	0.562697576	0.502351834	0.663354037	0.68814433	0.497206704	0.706349206	0.495361781	0.470899471	0.609589041	0.542682927	0.49859944	0.650426309	0.43485342	0.520467836	0.5	0.430992736	0.528189911	0.460344828	0.727520436	0.678526048	0.466783217	0.458762887	0.670854271	0.817764165	0.829192547	0.744769874	0.674242424	0.465562337	0.568085106	0.48413418	0.687258687	0.593993326	0.722598106	0.451394759	0.510028653	0.57605178	0.794642857	0.817764165	0.552795031	0.426177175	0.552795031	0.675094817	0.817764165	0.748948107	0.718707941	0.787610619	0.434146341	0.572347267	0.519961052	0.779562044	0.618055556	0.481949458	0.574811625	0.573576799	0.602708804	0.507604563	0.799401198
C3+S7	0.680501931	0.581683168	0.579293344	0.510130246	0.518763797	0.703592814	0.667613636	0.629464286	0.571312804	0.722336066	0.744456177	0.56626506	0.760517799	0.564451561	0.540229885	0.673352436	0.61038961	0.56763285	0.710685484	0.50393138	0.588972431	0.569007264	0.5	0.596446701	0.529676935	0.779005525	0.735908142	0.536121673	0.528089888	0.729058945	0.855582524	0.865030675	0.793918919	0.732087227	0.534901366	0.634563456	0.553375196	0.743670886	0.658878505	0.774725275	0.520679468	0.578817734	0.642076503	0.836298932	0.855582524	0.62005277	0.49508427	0.62005277	0.732848233	0.855582524	0.797511312	0.771334792	0.830388693	0.503211991	0.638586957	0.588480801	0.823598131	0.68115942	0.551211884	0.640909091	0.639745917	0.666982025	0.576451349	0.840286055
C3+S8	0.590346535	0.484756098	0.482305359	0.413344887	0.421750663	0.61627907	0.576086957	0.534753363	0.47415507	0.637700535	0.663421419	0.469026549	0.682403433	0.46718903	0.442896936	0.582417582	0.514563107	0.470414201	0.62434555	0.40734415	0.492260062	0.471810089	0.403553299	0.5	0.432456936	0.704579025	0.653424658	0.438822447	0.430894309	0.645466847	0.80033557	0.812606474	0.722727273	0.648979592	0.437614679	0.540203851	0.456022945	0.6625	0.566508314	0.69941349	0.423623446	0.481818182	0.548275862	0.775609756	0.80033557	0.524752475	0.398829431	0.524752475	0.64986376	0.80033557	0.727134146	0.695335277	0.768115942	0.406649616	0.544520548	0.491752577	0.75955414	0.591078067	0.453853473	0.547018349	0.54576659	0.575392039	0.479396985	0.780687398
C4+S1	0.654127482	0.552515446	0.550087873	0.480429777	0.4890625	0.218637993	0.64073695	0.601344861	0.541991342	0.697881828	0.721198157	0.536878216	0.738207547	0.535042735	0.510603589	0.646694215	0.581784387	0.538263113	0.685651698	0.474242424	0.559928444	0.539655172	0.470323065	0.567543064	0.5	0.757869249	0.712172924	0.506472492	0.498407643	0.704954955	0.840268456	0.850543478	0.773794808	0.708144796	0.505246166	0.606589147	0.523849372	0.720368239	0.631685166	0.753309266	0.490980392	0.549604917	0.614327772	0.819371728	0.840268456	0.59168242	0.465427509	0.59168242	0.708946772	0.840268456	0.777639752	0.749700599	0.812987013	0.473524962	0.610731707	0.559428061	0.805662806	0.654811715	0.521666667	0.613124388	0.611925709	0.6400818	0.547202797	0.823684211
C4+S2	0.376647834	0.282885431	0.280898876	0.228050171	0.234192037	0.282894737	0.362976407	0.325203252	0.274348422	0.42462845	0.452488688	0.27027027	0.473933649	0.268817204	0.25	0.36900369	0.307692308	0.271370421	0.410677618	0.223713647	0.289017341	0.272479564	0.220994475	0.295420975	0.242130751	0.5	0.441501104	0.24691358	0.240963855	0.432900433	0.626959248	0.64516129	0.522193211	0.436681223	0.24600246	0.330033003	0.260078023	0.451467269	0.353982301	0.49382716	0.23557126	0.280504909	0.337268128	0.591715976	0.626959248	0.316455696	0.217627856	0.316455696	0.437636761	0.626959248	0.527704485	0.488997555	0.581395349	0.223214286	0.333889816	0.288600289	0.56980057	0.377358491	0.258397933	0.336134454	0.335008375	0.362318841	0.278551532	0.598802395
C4+S3	0.433219178	0.332894737	0.330718954	0.272043011	0.278941566	0.483820047	0.418874172	0.378742515	0.323529412	0.482824427	0.511111111	0.319041614	0.532631579	0.317440402	0.296600234	0.425210084	0.359886202	0.320253165	0.468518519	0.267159451	0.339597315	0.321473952	0.264091858	0.346575342	0.287827076	0.558498896	0.5	0.293163384	0.286523216	0.491262136	0.680107527	0.696969697	0.580275229	0.495107632	0.292147806	0.383915023	0.307785888	0.510080645	0.409385113	0.552401747	0.280487805	0.330287206	0.391640867	0.647058824	0.680107527	0.369343066	0.260288066	0.369343066	0.496078431	0.680107527	0.585648148	0.547619048	0.637279597	0.266596417	0.38803681	0.339142091	0.626237624	0.433962264	0.30592503	0.390432099	0.389230769	0.418181818	0.328145266	0.65374677
C4+S4	0.648246546	0.54610564	0.543672014	0.473970474	0.482594937	0.383018868	0.634755463	0.595121951	0.535557507	0.692395006	0.715962441	0.530434783	0.733173077	0.528596187	0.504132231	0.640756303	0.575471698	0.531822145	0.680044593	0.467791411	0.55353902	0.533216783	0.463878327	0.561177553	0.493527508	0.75308642	0.706836616	0.5	0.491935484	0.699541284	0.836762689	0.847222222	0.769230769	0.702764977	0.498773508	0.600393701	0.517387617	0.715123095	0.625641026	0.748466258	0.484511517	0.54318789	0.608175474	0.815508021	0.836762689	0.585412668	0.458991723	0.585412668	0.703575548	0.836762689	0.773130545	0.744810745	0.809018568	0.467075038	0.604558969	0.553037171	0.801576873	0.64893617	0.515202703	0.606965174	0.605759682	0.634095634	0.540780142	0.819892473
C4+S5	0.655567118	0.55408971	0.551663748	0.482019893	0.490654206	0.465249387	0.642201835	0.602870813	0.543572045	0.699223085	0.722477064	0.538461538	0.73943662	0.536626917	0.512195122	0.648148148	0.583333333	0.539845758	0.687022901	0.475830816	0.561497326	0.541237113	0.471910112	0.569105691	0.501592357	0.759036145	0.713476784	0.508064516	0.5	0.706278027	0.841121495	0.851351351	0.774907749	0.709459459	0.506838294	0.608108108	0.525437865	0.721649485	0.633165829	0.754491018	0.492572322	0.551181102	0.615835777	0.8203125	0.841121495	0.593220339	0.467012602	0.593220339	0.710259301	0.841121495	0.778739184	0.750893921	0.813953488	0.475113122	0.612244898	0.560997329	0.806658131	0.65625	0.523255814	0.614634146	0.613437196	0.641547862	0.548780488	0.82460733
C4+S6	0.441821248	0.340702211	0.338501292	0.279020234	0.286026201	0.27090301	0.427406199	0.387001477	0.331226296	0.491557223	0.51984127	0.326683292	0.541322314	0.325062035	0.303944316	0.433774834	0.367977528	0.327909887	0.47723133	0.274058577	0.347480106	0.329145729	0.270941055	0.354533153	0.295045045	0.567099567	0.508737864	0.300458716	0.293721973	0.5	0.687664042	0.704301075	0.588764045	0.503846154	0.299428571	0.392215569	0.315282792	0.518811881	0.417862839	0.561027837	0.287596048	0.338064516	0.4	0.655	0.687664042	0.377521614	0.267074414	0.377521614	0.504816956	0.687664042	0.594104308	0.55626327	0.645320197	0.27348643	0.396369138	0.347019868	0.634382567	0.442567568	0.313397129	0.398782344	0.397572079	0.426710098	0.335897436	0.661616162
C4+S7	0.264444444	0.190095847	0.18858954	0.149497487	0.153945666	0.358194308	0.253191489	0.222846442	0.183641975	0.305128205	0.329639889	0.180576631	0.348973607	0.179487179	0.16550765	0.25813449	0.20913884	0.181402439	0.293103448	0.146371464	0.194762684	0.182235835	0.144417476	0.19966443	0.159731544	0.373040752	0.319892473	0.163237311	0.158878505	0.312335958	0.5	0.519650655	0.394039735	0.315649867	0.162568306	0.226666667	0.172965116	0.328729282	0.245867769	0.367283951	0.154947917	0.188291139	0.232421875	0.463035019	0.5	0.215970962	0.142004773	0.215970962	0.316489362	0.5	0.399328859	0.362804878	0.452471483	0.14601227	0.22972973	0.194444444	0.440740741	0.265033408	0.171717172	0.23151751	0.230620155	0.252653928	0.186813187	0.470355731
C4+S8	0.249433107	0.17828201	0.176848875	0.139771283	0.143979058	0.238649593	0.238611714	0.20952381	0.172143975	0.288713911	0.3125	0.169230769	0.331325301	0.168195719	0.154929577	0.243362832	0.196428571	0.170015456	0.277078086	0.13681592	0.182724252	0.170807453	0.134969325	0.187393526	0.149456522	0.35483871	0.303030303	0.152777778	0.148648649	0.295698925	0.480349345	0.5	0.375426621	0.298913043	0.152143845	0.213178295	0.162002946	0.311614731	0.231578947	0.349206349	0.144927536	0.176565008	0.218687873	0.443548387	0.480349345	0.20295203	0.132689988	0.20295203	0.29972752	0.480349345	0.380622837	0.344827586	0.433070866	0.136476427	0.21611002	0.182421227	0.421455939	0.25	0.160818713	0.217821782	0.216962525	0.238095238	0.175159236	0.450819672
C5+S1	0.356031128	0.265217391	0.263309353	0.212790698	0.218637993	0.218637993	0.342696629	0.306020067	0.257022472	0.4030837	0.430588235	0.253112033	0.451851852	0.251719395	0.233716475	0.348571429	0.289099526	0.254166667	0.389361702	0.208665906	0.271111111	0.255230126	0.206081081	0.277272727	0.226205192	0.477806789	0.419724771	0.230769231	0.225092251	0.411235955	0.605960265	0.624573379	0.5	0.414965986	0.229899497	0.310696095	0.243351064	0.429577465	0.333941606	0.471649485	0.219951923	0.262931034	0.317708333	0.570093458	0.605960265	0.297560976	0.202882483	0.297560976	0.415909091	0.605960265	0.505524862	0.466836735	0.559633028	0.208191126	0.31443299	0.270710059	0.547904192	0.356725146	0.241743725	0.316608997	0.315517241	0.342056075	0.261055635	0.577287066
C5+S2	0.43803056	0.337254902	0.335064935	0.275935829	0.282894737	0.282894737	0.42364532	0.383358098	0.327827192	0.487712665	0.516	0.323308271	0.5375	0.321695761	0.300699301	0.43	0.36440678	0.324528302	0.473394495	0.271008403	0.344	0.325757576	0.267912773	0.351020408	0.291855204	0.563318777	0.504892368	0.297235023	0.290540541	0.496153846	0.684350133	0.701086957	0.585034014	0.5	0.296211251	0.388554217	0.311970979	0.51497006	0.414125201	0.557235421	0.284454245	0.33463035	0.396313364	0.651515152	0.684350133	0.373913043	0.264073695	0.373913043	0.500970874	0.684350133	0.590389016	0.552462527	0.641791045	0.270440252	0.392694064	0.343541944	0.630806846	0.43877551	0.310096154	0.395099541	0.39389313	0.42295082	0.332474227	0.658163265
C5+S3	0.649364407	0.547321429	0.544888889	0.475193798	0.483820047	0.483820047	0.635892116	0.596303502	0.536777583	0.693438914	0.716959064	0.531656548	0.734131737	0.529818496	0.505358615	0.641884817	0.576669802	0.533043478	0.681111111	0.469013007	0.554751131	0.534437663	0.465098634	0.562385321	0.494753834	0.75399754	0.707852194	0.501226492	0.493161706	0.700571429	0.837431694	0.847856155	0.770100503	0.703788749	0.5	0.601570167	0.518612521	0.716121495	0.626789366	0.749388753	0.485736926	0.544404973	0.609343936	0.816245007	0.837431694	0.586602871	0.46021021	0.586602871	0.704597701	0.837431694	0.773989899	0.745742092	0.809775429	0.468296409	0.605731225	0.554249548	0.802356021	0.650053022	0.51642797	0.608134921	0.606930693	0.635233161	0.541998232	0.820615797
C5+S4	0.550881954	0.444687842	0.442265795	0.37488458	0.383018868	0.383018868	0.536327609	0.494518879	0.434224599	0.599704579	0.62654321	0.429175476	0.646496815	0.427368421	0.403578529	0.542780749	0.474299065	0.430540827	0.585858586	0.369090909	0.452115813	0.431914894	0.365436544	0.459796149	0.393410853	0.669966997	0.616084977	0.399606299	0.391891892	0.607784431	0.773333333	0.786821705	0.689303905	0.611445783	0.398429833	0.5	0.416410256	0.625577812	0.526588846	0.664484452	0.384834123	0.441784548	0.508135169	0.746323529	0.773333333	0.484486874	0.360888889	0.484486874	0.612368024	0.773333333	0.694017094	0.660162602	0.738181818	0.368421053	0.504347826	0.451612903	0.728904847	0.551630435	0.414285714	0.506866417	0.505603985	0.535620053	0.439393939	0.751851852
C5+S5	0.632222222	0.528810409	0.526364477	0.456661316	0.465249387	0.465249387	0.618478261	0.578252033	0.518214936	0.677380952	0.701602959	0.513074842	0.719342604	0.511230907	0.486740804	0.624588364	0.558390579	0.514466546	0.664719626	0.450514648	0.536286522	0.51586582	0.446624804	0.543977055	0.476150628	0.739921977	0.692214112	0.482612383	0.474562135	0.684717208	0.827034884	0.837997054	0.756648936	0.688029021	0.481387479	0.583589744	0.5	0.700738916	0.609207709	0.735142119	0.467159278	0.525878004	0.591476091	0.804809052	0.827034884	0.568431568	0.441770186	0.568431568	0.688861985	0.827034884	0.760695187	0.731362468	0.798036466	0.449802372	0.587809917	0.535781544	0.790277778	0.632925473	0.497812773	0.590248963	0.589026915	0.617806732	0.523459062	0.809388336
C5+S6	0.423344948	0.324	0.321854305	0.264130435	0.27090301	0.27090301	0.409090909	0.369300912	0.314766839	0.472762646	0.501030928	0.310344828	0.522580645	0.308767471	0.288256228	0.415384615	0.350649351	0.311538462	0.458490566	0.259338314	0.330612245	0.312741313	0.256329114	0.3375	0.279631761	0.548532731	0.489919355	0.284876905	0.278350515	0.481188119	0.671270718	0.688385269	0.570422535	0.48502994	0.283878505	0.374422188	0.299261084	0.5	0.399671053	0.542410714	0.272421525	0.321428571	0.382075472	0.637795276	0.671270718	0.36	0.252598753	0.36	0.486	0.671270718	0.575829384	0.537610619	0.627906977	0.258785942	0.378504673	0.330163043	0.616751269	0.42408377	0.297429621	0.380877743	0.3796875	0.408403361	0.319316689	0.644562334
C5+S7	0.524425287	0.418577982	0.416191562	0.350287908	0.358194308	0.358194308	0.509776536	0.467948718	0.408277405	0.573899371	0.601317957	0.403314917	0.621805792	0.401540154	0.378238342	0.516265912	0.447852761	0.404656319	0.559815951	0.344664778	0.425904317	0.406006674	0.341121495	0.433491686	0.368314834	0.646017699	0.590614887	0.374358974	0.366834171	0.582137161	0.754132231	0.768421053	0.666058394	0.585874799	0.373210634	0.473411154	0.390792291	0.600328947	0.5	0.640350877	0.359960552	0.41571754	0.481530343	0.725646123	0.754132231	0.457967378	0.336715867	0.457967378	0.58681672	0.754132231	0.670955882	0.635888502	0.717092338	0.34401508	0.477748691	0.425407925	0.707364341	0.525179856	0.388711395	0.480263158	0.479002625	0.509065551	0.413363533	0.731462926
C5+S8	0.382462687	0.287921348	0.285913529	0.232426304	0.238649593	0.238649593	0.368705036	0.330645161	0.279291553	0.430672269	0.458612975	0.275167785	0.480093677	0.273698264	0.254658385	0.374771481	0.312977099	0.276280323	0.416666667	0.228031146	0.294117647	0.277401894	0.225274725	0.30058651	0.246690734	0.50617284	0.447598253	0.251533742	0.245508982	0.438972163	0.632716049	0.650793651	0.528350515	0.442764579	0.250611247	0.335515548	0.264857881	0.457589286	0.359649123	0.5	0.240046838	0.28551532	0.342809365	0.597667638	0.632716049	0.321821036	0.221861472	0.321821036	0.443722944	0.632716049	0.533854167	0.495169082	0.58739255	0.227524972	0.339403974	0.293696275	0.575842697	0.38317757	0.263157895	0.341666667	0.340531561	0.368043088	0.283540802	0.604719764
C6+S1	0.662244898	0.561418685	0.559000861	0.489441931	0.498081351	0.498081351	0.649	0.609962406	0.550933786	0.705434783	0.728395062	0.545836838	0.745120551	0.544006706	0.519615693	0.654894046	0.590536852	0.547217538	0.693376068	0.483246463	0.568799299	0.548605241	0.479320532	0.576376554	0.509019608	0.76442874	0.719512195	0.515488483	0.507427678	0.712403952	0.845052083	0.855072464	0.780048077	0.715545755	0.514263074	0.615165877	0.532840722	0.727578475	0.640039448	0.759953162	0.5	0.558519793	0.622840691	0.824650572	0.845052083	0.600370028	0.474415205	0.600370028	0.716335541	0.845052083	0.783816425	0.756410256	0.818411097	0.482527881	0.619274809	0.568301226	0.81125	0.662921348	0.530662306	0.62164751	0.620458891	0.648351648	0.556126821	0.828863346
C6+S2	0.607819905	0.502941176	0.500487805	0.431092437	0.439588689	0.439588689	0.59375	0.552801724	0.492322457	0.654336735	0.679470199	0.487179487	0.697959184	0.485335856	0.460916442	0.6	0.53271028	0.488571429	0.64125	0.425020713	0.510447761	0.489971347	0.421182266	0.518181818	0.450395083	0.719495091	0.669712794	0.45681211	0.448818898	0.661935484	0.811708861	0.823434992	0.737068966	0.66536965	0.455595027	0.558215452	0.474121996	0.678571429	0.58428246	0.71448468	0.441480207	0.5	0.566225166	0.788018433	0.811708861	0.542857143	0.416396104	0.542857143	0.666233766	0.811708861	0.74132948	0.710526316	0.780821918	0.424317618	0.5625	0.509940358	0.772590361	0.608540925	0.471941122	0.564977974	0.563736264	0.593063584	0.49757517	0.792890263
C6+S3	0.54281768	0.436666667	0.434254144	0.36728972	0.375358166	0.375358166	0.528225806	0.486386139	0.426247289	0.59186747	0.618897638	0.421221865	0.63902439	0.419423693	0.395770393	0.534693878	0.466192171	0.422580645	0.577941176	0.361545538	0.444067797	0.42394822	0.357923497	0.451724138	0.385672228	0.662731872	0.608359133	0.391824526	0.384164223	0.6	0.767578125	0.781312127	0.682291667	0.603686636	0.390656064	0.491864831	0.408523909	0.617924528	0.518469657	0.657190635	0.377159309	0.433774834	0.5	0.740112994	0.767578125	0.476363636	0.353417266	0.476363636	0.604615385	0.767578125	0.687062937	0.65282392	0.731843575	0.360881543	0.496212121	0.443566591	0.722426471	0.543568465	0.406411582	0.498730964	0.497468354	0.527516779	0.431394072	0.74573055
C6+S4	0.29424307	0.213953488	0.212307692	0.169325153	0.174242424	0.174242424	0.282208589	0.24954792	0.206896552	0.337408313	0.363157895	0.203539823	0.383333333	0.202346041	0.18699187	0.2875	0.234693878	0.204444444	0.324705882	0.165865385	0.219047619	0.205357143	0.163701068	0.224390244	0.180628272	0.408284024	0.352941176	0.184491979	0.1796875	0.345	0.536964981	0.556451613	0.429906542	0.348484848	0.183754993	0.253676471	0.195190948	0.362204724	0.274353877	0.402332362	0.175349428	0.211981567	0.259887006	0.5	0.536964981	0.242105263	0.161026838	0.242105263	0.349367089	0.536964981	0.43533123	0.397694524	0.489361702	0.165467626	0.25698324	0.218700475	0.477508651	0.294871795	0.193820225	0.25891182	0.257943925	0.281632653	0.210365854	0.507352941
C6+S5	0.264444444	0.190095847	0.18858954	0.149497487	0.153945666	0.153945666	0.253191489	0.222846442	0.183641975	0.305128205	0.329639889	0.180576631	0.348973607	0.179487179	0.16550765	0.25813449	0.20913884	0.181402439	0.293103448	0.146371464	0.194762684	0.182235835	0.144417476	0.19966443	0.159731544	0.373040752	0.319892473	0.163237311	0.158878505	0.312335958	0.5	0.519650655	0.394039735	0.315649867	0.162568306	0.226666667	0.172965116	0.328729282	0.245867769	0.367283951	0.154947917	0.188291139	0.232421875	0.463035019	0.5	0.215970962	0.142004773	0.215970962	0.316489362	0.5	0.399328859	0.362804878	0.452471483	0.14601227	0.22972973	0.194444444	0.440740741	0.265033408	0.171717172	0.23151751	0.230620155	0.252653928	0.186813187	0.470355731
C6+S6	0.566186107	0.460063898	0.457627119	0.389540126	0.397790055	0.397790055	0.551724138	0.510035419	0.449531738	0.614509246	0.640949555	0.444444444	0.660550459	0.442622951	0.418604651	0.558139535	0.489795918	0.445820433	0.600834492	0.38365897	0.467532468	0.447204969	0.37994723	0.475247525	0.40831758	0.683544304	0.630656934	0.414587332	0.406779661	0.622478386	0.784029038	0.79704797	0.702439024	0.626086957	0.413397129	0.515513126	0.431568432	0.64	0.542032622	0.678178964	0.399629972	0.457142857	0.523636364	0.757894737	0.784029038	0.5	0.375325804	0.5	0.626995646	0.784029038	0.707037643	0.673946958	0.75	0.382978723	0.519855596	0.467027027	0.740994854	0.566929134	0.429423459	0.522370012	0.521109771	0.551020408	0.454736842	0.763250883
C6+S7	0.684761905	0.586460033	0.584077985	0.51504298	0.523670794	0.523670794	0.671962617	0.634038801	0.576121795	0.726262626	0.74817898	0.571088165	0.764080765	0.569279493	0.545109932	0.677662582	0.615055603	0.572452229	0.71471173	0.508846426	0.593724195	0.573822825	0.50491573	0.601170569	0.534572491	0.782372144	0.739711934	0.541008277	0.532987398	0.732925586	0.857995227	0.867310012	0.797117517	0.735926305	0.53978979	0.639111111	0.558229814	0.747401247	0.663284133	0.778138528	0.525584795	0.583603896	0.646582734	0.838973162	0.857995227	0.624674196	0.5	0.624674196	0.736680328	0.857995227	0.800668151	0.774784483	0.833140209	0.508127208	0.643112701	0.593234323	0.826436782	0.685414681	0.556071152	0.645421903	0.644265233	0.671335201	0.581244947	0.842907386
C6+S8	0.566186107	0.460063898	0.457627119	0.389540126	0.397790055	0.397790055	0.551724138	0.510035419	0.449531738	0.614509246	0.640949555	0.444444444	0.660550459	0.442622951	0.418604651	0.558139535	0.489795918	0.445820433	0.600834492	0.38365897	0.467532468	0.447204969	0.37994723	0.475247525	0.40831758	0.683544304	0.630656934	0.414587332	0.406779661	0.622478386	0.784029038	0.79704797	0.702439024	0.626086957	0.413397129	0.515513126	0.431568432	0.64	0.542032622	0.678178964	0.399629972	0.457142857	0.523636364	0.757894737	0.784029038	0.5	0.375325804	0.5	0.626995646	0.784029038	0.707037643	0.673946958	0.75	0.382978723	0.519855596	0.467027027	0.740994854	0.566929134	0.429423459	0.522370012	0.521109771	0.551020408	0.454736842	0.763250883
C7+S1	0.43707483	0.336387435	0.33420026	0.2751606	0.282107574	0.282107574	0.422697368	0.382440476	0.32697201	0.486742424	0.51503006	0.322459222	0.536534447	0.320848939	0.299883314	0.429048414	0.363507779	0.323677582	0.472426471	0.270241851	0.343124166	0.324905183	0.267151767	0.35013624	0.291053228	0.562363239	0.503921569	0.296424452	0.289740699	0.495183044	0.683510638	0.70027248	0.584090909	0.499029126	0.295402299	0.387631976	0.311138015	0.514	0.41318328	0.556277056	0.283664459	0.333766234	0.395384615	0.650632911	0.683510638	0.373004354	0.263319672	0.373004354	0.5	0.683510638	0.589449541	0.551502146	0.640897756	0.269674711	0.391768293	0.342666667	0.629901961	0.437819421	0.309265945	0.394171779	0.392966361	0.422003284	0.331612903	0.657289003
C7+S2	0.264444444	0.190095847	0.18858954	0.149497487	0.153945666	0.153945666	0.253191489	0.222846442	0.183641975	0.305128205	0.329639889	0.180576631	0.348973607	0.179487179	0.16550765	0.25813449	0.20913884	0.181402439	0.293103448	0.146371464	0.194762684	0.182235835	0.144417476	0.19966443	0.159731544	0.373040752	0.319892473	0.163237311	0.158878505	0.312335958	0.5	0.519650655	0.394039735	0.315649867	0.162568306	0.226666667	0.172965116	0.328729282	0.245867769	0.367283951	0.154947917	0.188291139	0.232421875	0.463035019	0.5	0.215970962	0.142004773	0.215970962	0.316489362	0.5	0.399328859	0.362804878	0.452471483	0.14601227	0.22972973	0.194444444	0.440740741	0.265033408	0.171717172	0.23151751	0.230620155	0.252653928	0.186813187	0.470355731
C7+S3	0.350980392	0.260932945	0.259044863	0.20911215	0.214885954	0.214885954	0.337735849	0.301346801	0.252824859	0.397777778	0.425178147	0.248956885	0.44638404	0.24757953	0.229781772	0.343570058	0.284578696	0.25	0.384120172	0.205040092	0.266766021	0.251051893	0.202488688	0.272865854	0.222360248	0.472295515	0.414351852	0.226869455	0.221260816	0.405895692	0.600671141	0.619377163	0.494475138	0.409610984	0.226010101	0.305982906	0.239304813	0.424170616	0.329044118	0.466145833	0.216183575	0.25867052	0.312937063	0.56466877	0.600671141	0.292962357	0.199331849	0.292962357	0.410550459	0.600671141	0.5	0.461340206	0.554179567	0.204571429	0.309688581	0.266369048	0.542424242	0.351669941	0.237715803	0.31184669	0.310763889	0.337099812	0.256814921	0.571884984
C7+S4	0.387037037	0.291899441	0.289875173	0.235891648	0.242178447	0.242178447	0.373214286	0.334935897	0.283197832	0.435416667	0.463414634	0.279038718	0.484918794	0.277556441	0.258343634	0.379310345	0.317147193	0.280160858	0.421370968	0.23145072	0.298145506	0.281292059	0.228665208	0.304664723	0.250299401	0.511002445	0.452380952	0.255189255	0.249106079	0.44373673	0.637195122	0.655172414	0.533163265	0.447537473	0.254257908	0.339837398	0.268637532	0.462389381	0.364111498	0.504830918	0.243589744	0.289473684	0.34717608	0.602305476	0.637195122	0.326053042	0.225215517	0.326053042	0.448497854	0.637195122	0.538659794	0.5	0.592067989	0.230939227	0.34375	0.297720798	0.580555556	0.387755102	0.266922095	0.34602649	0.344884488	0.37254902	0.287482806	0.609329446
C7+S5	0.303157895	0.221198157	0.219512195	0.175395859	0.180451128	0.180451128	0.290909091	0.257602862	0.213967311	0.346987952	0.373056995	0.210526316	0.393442623	0.209302326	0.193548387	0.296296296	0.242424242	0.211453744	0.334106729	0.171837709	0.226415094	0.212389381	0.169611307	0.231884058	0.187012987	0.418604651	0.362720403	0.190981432	0.186046512	0.354679803	0.547528517	0.566929134	0.440366972	0.358208955	0.190224571	0.261818182	0.201963534	0.372093023	0.282907662	0.41260745	0.181588903	0.219178082	0.268156425	0.510638298	0.547528517	0.25	0.166859791	0.25	0.359102244	0.547528517	0.445820433	0.407932011	0.5	0.171428571	0.26519337	0.226059655	0.488135593	0.303797468	0.200557103	0.26716141	0.266173752	0.290322581	0.217522659	0.517985612
C7+S6	0.677702045	0.578553616	0.57615894	0.506919155	0.515555556	0.515555556	0.664756447	0.626462646	0.568163265	0.71975181	0.742004264	0.563106796	0.758169935	0.561290323	0.537037037	0.670520231	0.607329843	0.564476886	0.708036623	0.500719424	0.585858586	0.565853659	0.496788009	0.593350384	0.526475038	0.776785714	0.733403583	0.532924962	0.524886878	0.72651357	0.85398773	0.863523573	0.791808874	0.729559748	0.531703591	0.631578947	0.550197628	0.741214058	0.65598492	0.772475028	0.517472119	0.575682382	0.639118457	0.834532374	0.85398773	0.617021277	0.491872792	0.617021277	0.730325289	0.85398773	0.795428571	0.769060773	0.828571429	0.5	0.635616438	0.585365854	0.821723731	0.678362573	0.548031496	0.637946838	0.636779506	0.664122137	0.573311367	0.838554217
C7+S7	0.546575342	0.440397351	0.437980241	0.370817844	0.378917379	0.378917379	0.532	0.49017199	0.429956897	0.595522388	0.622464899	0.424920128	0.642512077	0.423117709	0.399399399	0.538461538	0.469964664	0.426282051	0.581632653	0.36505032	0.447811448	0.427652733	0.361413043	0.455479452	0.389268293	0.666110184	0.61196319	0.395441031	0.387755102	0.603630862	0.77027027	0.78388998	0.68556701	0.607305936	0.394268775	0.495652174	0.412190083	0.621495327	0.522251309	0.660596026	0.380725191	0.4375	0.503787879	0.74301676	0.77027027	0.480144404	0.356887299	0.480144404	0.608231707	0.77027027	0.690311419	0.65625	0.73480663	0.364383562	0.5	0.447309417	0.725454545	0.547325103	0.410071942	0.502518892	0.501256281	0.531291611	0.435114504	0.748592871
C7+S8	0.598300971	0.493	0.490547264	0.421367521	0.429816914	0.429816914	0.584123223	0.542951542	0.482387476	0.645287958	0.670748299	0.477250726	0.68951049	0.475409836	0.45105215	0.590419162	0.522799576	0.478640777	0.632051282	0.415332772	0.500507614	0.480038948	0.411519199	0.508247423	0.440571939	0.711399711	0.660857909	0.446962829	0.439002671	0.652980132	0.805555556	0.817578773	0.729289941	0.656458056	0.445750452	0.548387097	0.464218456	0.669836957	0.574592075	0.706303725	0.431698774	0.490059642	0.556433409	0.781299525	0.805555556	0.532972973	0.406765677	0.532972973	0.657333333	0.805555556	0.733630952	0.702279202	0.773940345	0.414634146	0.552690583	0.5	0.76552795	0.599027947	0.462043112	0.55518018	0.553932584	0.583431953	0.487636004	0.786283892
C8+S1	0.313278008	0.229483283	0.22775264	0.18236715	0.18757764	0.18757764	0.300796813	0.266784452	0.222058824	0.357819905	0.384223919	0.218523878	0.404825737	0.217266187	0.201065246	0.306288032	0.25124792	0.219476744	0.344748858	0.178698225	0.234836703	0.220437956	0.176401869	0.24044586	0.194337194	0.43019943	0.373762376	0.198423127	0.193341869	0.365617433	0.559259259	0.578544061	0.452095808	0.369193154	0.197643979	0.271095153	0.209722222	0.383248731	0.292635659	0.424157303	0.18875	0.227409639	0.277573529	0.522491349	0.559259259	0.259005146	0.173563218	0.259005146	0.370098039	0.559259259	0.457575758	0.419444444	0.511864407	0.178276269	0.274545455	0.23447205	0.5	0.313929314	0.208275862	0.276556777	0.275547445	0.300198807	0.225710015	0.529824561
C8+S2	0.49924357	0.394265233	0.39192399	0.327706058	0.335365854	0.335365854	0.484581498	0.44295302	0.384167637	0.549084859	0.576923077	0.379310345	0.597826087	0.377574371	0.35483871	0.491071429	0.423076923	0.380622837	0.534846029	0.322265625	0.401459854	0.381944444	0.31884058	0.408921933	0.345188285	0.622641509	0.566037736	0.35106383	0.34375	0.557432432	0.734966592	0.75	0.643274854	0.56122449	0.349946978	0.448369565	0.367074527	0.57591623	0.474820144	0.61682243	0.337078652	0.391459075	0.456431535	0.705128205	0.734966592	0.433070866	0.314585319	0.433070866	0.562180579	0.734966592	0.648330059	0.612244898	0.696202532	0.321637427	0.452674897	0.400972053	0.686070686	0.5	0.365044248	0.455172414	0.45392022	0.483870968	0.389150943	0.711206897
C8+S3	0.634254144	0.530989824	0.52854512	0.458832934	0.46742671	0.46742671	0.620540541	0.580384226	0.520398912	0.679289941	0.703431373	0.515260323	0.721105528	0.513416816	0.488926746	0.626637555	0.560546875	0.516651665	0.666666667	0.452681388	0.538461538	0.518050542	0.448788116	0.546146527	0.478333333	0.741602067	0.69407497	0.484797297	0.476744186	0.686602871	0.828282828	0.839181287	0.758256275	0.689903846	0.48357203	0.585714286	0.502187227	0.702570379	0.611288605	0.736842105	0.469337694	0.528058878	0.593588418	0.806179775	0.828282828	0.570576541	0.443928848	0.570576541	0.690734055	0.828282828	0.762284197	0.733077905	0.799442897	0.451968504	0.589928058	0.537956888	0.791724138	0.634955752	0.5	0.592363261	0.591143151	0.61987041	0.525641026	0.810734463
C8+S4	0.544077135	0.437915743	0.435501654	0.368470149	0.376549094	0.376549094	0.529490617	0.487654321	0.427489177	0.593093093	0.620094192	0.422459893	0.640194489	0.420660277	0.396984925	0.535956581	0.467455621	0.423819742	0.579178886	0.36271809	0.445321308	0.425188375	0.359090909	0.452981651	0.386875612	0.663865546	0.609567901	0.393034826	0.385365854	0.601217656	0.76848249	0.782178218	0.683391003	0.604900459	0.391865079	0.493133583	0.409751037	0.619122257	0.519736842	0.658333333	0.37835249	0.435022026	0.501269036	0.74108818	0.76848249	0.477629988	0.354578097	0.477629988	0.605828221	0.76848249	0.68815331	0.65397351	0.73283859	0.362053162	0.497481108	0.44481982	0.723443223	0.544827586	0.407636739	0.5	0.498737374	0.528781794	0.43263965	0.746691871
C8+S5	0.54532967	0.439159292	0.436743674	0.369646182	0.37773549	0.37773549	0.530748663	0.488916256	0.428725702	0.594311377	0.621283255	0.423692636	0.641357027	0.421891605	0.398194584	0.537212449	0.468713105	0.425053533	0.580409357	0.363886343	0.446569179	0.426423201	0.360254083	0.45423341	0.388074291	0.664991625	0.610769231	0.394240318	0.386562804	0.602427921	0.769379845	0.783037475	0.684482759	0.60610687	0.393069307	0.494396015	0.410973085	0.6203125	0.520997375	0.659468439	0.379541109	0.436263736	0.502531646	0.742056075	0.769379845	0.478890229	0.355734767	0.478890229	0.607033639	0.769379845	0.689236111	0.655115512	0.733826248	0.363220494	0.498743719	0.446067416	0.724452555	0.54607978	0.408856849	0.501262626	0.5	0.530040053	0.433879781	0.747645951
C8+S6	0.515373353	0.409778813	0.407407407	0.342079689	0.349900596	0.349900596	0.500711238	0.4589309	0.39954597	0.565008026	0.592592593	0.394618834	0.613240418	0.392857143	0.369747899	0.507204611	0.438902743	0.395950506	0.55086072	0.336520076	0.417061611	0.397291196	0.333017975	0.424607961	0.3599182	0.637681159	0.581818182	0.365904366	0.358452138	0.573289902	0.747346072	0.761904762	0.657943925	0.57704918	0.364766839	0.464379947	0.382193268	0.591596639	0.490934449	0.631956912	0.351648352	0.406936416	0.472483221	0.718367347	0.747346072	0.448979592	0.328664799	0.448979592	0.577996716	0.747346072	0.662900188	0.62745098	0.709677419	0.335877863	0.468708389	0.416568047	0.699801193	0.516129032	0.38012959	0.471218206	0.469959947	0.5	0.404597701	0.724279835
C8+S7	0.610129564	0.505365854	0.502912621	0.433472803	0.441979522	0.441979522	0.596087457	0.555198285	0.494746896	0.65652725	0.681578947	0.489603025	0.7	0.487758945	0.46332737	0.602325581	0.535123967	0.490995261	0.643478261	0.427392739	0.512871287	0.492395437	0.423548651	0.520603015	0.452797203	0.721448468	0.671854734	0.459219858	0.451219512	0.664102564	0.813186813	0.824840764	0.738944365	0.667525773	0.458001768	0.560606061	0.476540938	0.680683311	0.586636467	0.716459198	0.443873179	0.50242483	0.568605928	0.789634146	0.813186813	0.545263158	0.418755053	0.545263158	0.668387097	0.813186813	0.743185079	0.712517194	0.782477341	0.426688633	0.564885496	0.512363996	0.774289985	0.610849057	0.474358974	0.56736035	0.566120219	0.595402299	0.5	0.794478528
C8+S8	0.288172043	0.209048362	0.207430341	0.165228113	0.170050761	0.170050761	0.27628866	0.244080146	0.202111614	0.330864198	0.356382979	0.198813056	0.376404494	0.197640118	0.182561308	0.281512605	0.229452055	0.199701937	0.318289786	0.161835749	0.214057508	0.200598802	0.159713945	0.219312602	0.176315789	0.401197605	0.34625323	0.180107527	0.17539267	0.338383838	0.529644269	0.549180328	0.422712934	0.341836735	0.179384203	0.248148148	0.190611664	0.355437666	0.268537074	0.395280236	0.171136654	0.207109737	0.25426945	0.492647059	0.529644269	0.236749117	0.157092614	0.236749117	0.342710997	0.529644269	0.428115016	0.390670554	0.482014388	0.161445783	0.251407129	0.213716108	0.470175439	0.288793103	0.189265537	0.253308129	0.252354049	0.275720165	0.205521472	0.5

You’ll notice that starting with Row 1, Column 1 (position [1,1]) and following along a perfect diagonal (positions [2,2], [3,3], [4,4], etc.) all the probabilities are 0.5, or dead even. This is because due to the way the table is set up, each C_n+S_n is pitted against itself exactly once.

There are also 448 other instances of the same Competitor facing itself with a different Strategy.

These 512 matchups notwithstanding, our table does give us the win probabilities for every real combination of C_n+S_n.

This is Bayes’ Theorem at work.

We’re on to a start.

1.1 Bayesian Inference & Conditional Probability in Trading Card Games

With the foundations of our project set, this first post seeks to demonstrate the reason for choosing Bayesian Inference as our probabilistic framework.

What is Probability?

When we say probability, at least in terms of this project in general and events wagering in particular, what we mean is:

“How certain (or uncertain) are we that a given outcome will occur?”

That is, without knowing what the future holds, how do we assign a value to our belief that a given outcome will occur?

A probability of 0 means that we are certain that an outcome has no chance of occurring, while a probability of 1 means that we are certain that an outcome has an absolute chance of occurring.

It’s a bit like this:

Most of what we experience in life isn’t all the way in the red toward 0 nor all the way to the right at 1. It’s somewhere in between.

But where, exactly?

Classical Probability and Poor Inferences

When we think of probability generally, six-sided dice and coins come most frequently to mind and are used very liberally to demonstrate examples of probability.

We assume that rolling a 6 on a six-side die is 1/6 and that getting a heads on a coin flip is 1/2.

These are true for the purposes of those thought experiments.

We might be tempted to extend these thought experiments further and apply them to the case of assigning probabilities to a two-player, winner-take-all game like a trading card game (TCG).

If Player A has played 1,000 games and we know that he or she has won 759 of those games, we might say that the probability that Player A win the 1,001st game is 0.759.

That would be a false assumption.

What this simple model lacks is conditionality.

In the 1,001st game, Player A will not play against some long-run average player under some long-run average conditions, but against a particular player under particular conditions.

What’s more, Player A may never have played this theoretical 1,001st opponent before and may never have seen this opponent’s strategy. In fact, that opponent’s strategy might be completely different from the previous 1,000 strategies Player A has encountered, and might be, something no one has ever seen or accounted for before.

What is Player A’s probability of winning now?

We must conclude that Player A’s probability of winning the 1,001st game is conditioned on these, and many more, circumstances.

Likewise, this 1,001st opponent, call him or her Player B, has a win probability that is likewise conditioned on Player A, Player A’s strategy, and the circumstances of their meeting to play.

Bayesian Inference

The only theoretical framework that allows us to assign these probabilities, in this example and the whole of this project, is Bayes Theorem.

Bayes’ Theorem states that:

[math] P(A|B)=\frac{P(A)P(B|A)}{P(B)}\ [/math]

Applied to our case, this means that the probability of Player A winning given that he or she plays against Player B, P(A|B), is equal to the probability that Player A win any match, P(A), times the probability that Player B win given that he or she plays against Player A, P(B|A), over the probability that Player B win any match, P(B).

As we’ll see in the next post, using Excel the and R programming language to construct matrixes of player and strategy combinations, this is easy to compute.

Project 1: What if a Sportsbook Offered Odds on Trading Card Games?

Background

I’ve been a lifelong fan of trading card games.

Ever since the Star Wars CCG (Customizable Card Game) in 1995 and later, Pokémon TCG (Trading Card Game) in 1999 (in the U.S.), I’ve been hooked.

Trading card games are games of skill where two competitors construct decks of cards from those available in the game and play against one another.

One player wins and another loses. (Sometimes, there is a draw.) These games are “zero-sum” in this way.

Working in the gambling industry, as I have, for 10 years now led me to ask: “What if a sportsbook placed betting prices on the outcome of trading card game events like they do for professional sports events?”

Basically: what if you can bet on games like Pokémon and Magic: the Gathering or Yu-Gi-Oh?

What would this take to make work? What are the theoretical concepts than underpin such an endeavor? What kind of profit could the sportsbook expect?

I attempt to answer these and more during the course of this project.

I aim for this project to change and evolve as its proceeds, knowing that the final conclusions I draw may be very different from my starting assumptions.

I hope also to get some comment from readers to help improve what’s being done here.

This project is both a demonstration and also some food for thought.

Objectives

My objectives for this project are:

Demonstrate how Bayesian Inference can help us construct a predictive model for two-player, winner-take-all events (card games).
Demonstrate how, given the probabilities assumed by these inferences, odds and betting prices by a fictional sportsbook (“TCGBook”) can be set.
Model the outcomes of fictional and real matchups in a trading card game tournament setting.
Model the profit and loss of our fictional sportsbook (“TCGBook”).
Open these ideas to the public for comment, critique, and improvement.

Limitations

Before starting on this quest to model our TCGBook endeavor, it is important that I acknowledge a few key limitations.

We compare our subject, trading card games, to the tried-and-true professional sports leagues on which our sports betting idea and models are largely based.

Data Availability

The data for card game events can be very hard to come by.

Most of the data sources are compiled by fans of the games and not the hosts or producers of the games themselves. The “big dogs”, as it were, do not wish to disclose their proprietary information. Or at least, not all of it. Maybe they never thought to or they not in a place to do this regularly.

The fans that do this tireless service for us should be acknowledged for their efforts, both for this project, and more importantly, for the fandom and playerbases of these games.

That being said, much of the data that we would like to have is simply unavailable or is, at best, incomplete.

In real sports betting, sportsbooks are able to rely heavily on data aggregators to compile every conceivable bit of data about sports, events, scores, goals, fouls, players, training, coaches, etc. This isn’t the case for trading card games. The interest and size of the market just isn’t the same. It’s much smaller.

We would love to see data on each major tournament, broken down by each round. We would love to see player data reported with unique ID keys to keep variations of a player’s name or misspellings from confusing the data. We’d love to see local, sanctioned tournament data, too. But these are not realities.

We will work within these limitations and show that, at least conceptually, our idea is possible.

We’ll focus only on the widely available data, namely that from major tournaments and the highest ranked players and best known strategies.

Nature of Trading Card Game Events

Trading card game events don’t work like professional sports matches.

In professional sports matches, we know which team will play against which team and on what date. This allows the sportsbook advance knowledge of these events and gives it time to compute odds and set prices. Season schedules for any major sport are announced well ahead of time.

This is not the case for card game tournaments.

At local tournaments, anyone can show up with a deck to sign up to play. At major events, any number of qualified players can show up (or not show up). Add to this the possibility of any given strategy (i.e. deck of cards) being used by any competitor, and the matchups are simply unknowable ahead of time.

In this project we will simply ignore this as a problem. We will make the assumption that the odds are set sometime in advance of the event taking place (maybe just minutes before). Making this assumption allows us to proceed to demonstrate our ideas.

Feasibility of Taking Bets

This project isn’t a serious attempt to find a way to start taking bets on trading card games.

This may or may not be legal in any jurisdiction, and what is proposed in this project is not legal advice nor an inducement to try and make this work outside of the law.

To complicate matters, the participants of many card game events are under the legal age to gamble in many places.

Nowadays, most jurisdictions (at least in the U.S.) allow betting on college sports, where the expectation is that competitors are least 18 years of age.

Whether or not taking bets on such events would fly with gaming regulators is not considered here. This is about proving a concept (and having fun while doing it).

Don’t take anything in this project too seriously as far as making money at gambling on trading card games goes.

This is a big “what if” sort of project.

Assumptions

With our objectives in mind, and our limitations outlined, we’ll make the following assumptions for this project:

All probabilistic modelling will be based on Bayesian (not Frequentist) inference.
We will briefly discuss, but largely ignore, the outcome of ties. We care only about win probabilities (and consequently, not win probabilities).
Win probabilities are expected to describe the win probability of matches; that is, “best two-out-of-three” matches in which the first competitor to win two games, wins the match. (This is the circumstance which often contributes to a draw between players: a time limit for the match it met with neither player having a decisive, tie-breaking win).
The outcomes we seek are not only probabilistic, but also commercial: this is about setting bet prices for potential bettors. As “the house”, we expect to make money in the long run. Our models, odds, and prices will reflect that desire.
As mentioned previously, we assume that we know who is playing and which deck they are using before the match. We know the identities of players and the decks they each use beforehand, thus, giving rise to our probabilities for each player to win and the consequent bet prices for each side of the match.
While I will take time to explain many of the theories and logic behind each step we take in this project, I will assume that readers have some familiarity with the mathematics of probability, statistical inference, the software systems we’ll use, and the games we are speaking about. Feel free to ask in the comments if you’re unsure about something!

Segments

The project is broken down into the following segments, each with its own dedicated page:

1.1 Bayesian Inference & Conditional Probability
1.2 Modelling Competitor + Strategy Probabilities
1.3 Win/Loss Odds & Betting Prices
1.4 Building Competitor A Model: Glicko Scores
1.5 Building a Strategy Model: Deck Quality and the Metagame
1.6 Fine-Tuning the TCG Sportsbook Model
1.7 Simulating a TCG World Tournament (1,000 Times!)
1.8 TCG Sportsbook Finished White Paper