{"id":15,"date":"2010-08-19T19:38:52","date_gmt":"2010-08-19T19:38:52","guid":{"rendered":"https:\/\/www.mattbusche.org\/blog\/?p=15"},"modified":"2015-10-28T01:41:33","modified_gmt":"2015-10-28T01:41:33","slug":"zilch","status":"publish","type":"post","link":"https:\/\/www.mattbusche.org\/blog\/article\/zilch\/","title":{"rendered":"Maximizing Expected Scores in the Game of Zilch"},"content":{"rendered":"<p><img decoding=\"async\" src=\"http:\/\/www.mattbusche.org\/images\/dice.jpg\" alt=\"A Throw of the Dice\" \/><\/p>\n<div style=\"font-size:80%; text-align:right; margin-bottom:20px;\">Image by <a href=\"http:\/\/www.flickr.com\/photos\/thunderchild5\/\" target=\"_blank\" rel=\"noopener\">Thunderchild7<\/a><\/div>\n<p>Zilch is a fun little dice game codified into an online game by Gaby<br \/>\nVanhegan that can be played at<br \/>\n<a href=\"http:\/\/playr.co.uk\/\">http:\/\/playr.co.uk\/<\/a>.  Zilch is actually a<br \/>\nvariation of the game Farkle which goes by several other names including<br \/>\nZonk, 5000, 10000, Wimp Out,<br \/>\nGreed, Squelch and Hot Dice<sup class=\"ref\"><a href=\"#R1\">1<\/a><\/sup>.  I&#8217;ve<br \/>\nworked out the strategy that maximizes your expected game score and wanted to<br \/>\nshare the analysis, my strategy finder software, and the strategy itself.<br \/>\nDepending on whether you have zero, one or two consecutive zilches from<br \/>\nprevious turns, three successively more conservative turn-play strategies are<br \/>\nrequired to maximize your long term average score.  Using these three strategies<br \/>\nyou rack up an average of 620.855 points per turn, which is the best you<br \/>\ncan possibly do.<\/p>\n<p><!--more--><\/p>\n<p>Beyond the scope of Gaby&#8217;s implementation of Zilch, the scoring rules of<br \/>\nFarkle vary from venue to venue and the strategies provided here do not<br \/>\ngenerally apply, but the analysis and the software do.<\/p>\n<p>If you understand conditional probabilities, expectations, and can do a<br \/>\nlittle algebra, you should be able to follow along.  If you&#8217;re just here to<br \/>\ntake the money and go pound someone in the game, you&#8217;ll need to at least read<br \/>\nand understand <a href=\"#formulation\">Strategy Formulation<\/a> before you try<br \/>\nto interpret the <a href=\"#T0\">tables<\/a>.<\/p>\n<h2>Contents<\/h2>\n<div class=\"outline\">\n<div class=\"i2\"><a href=\"#background\">Background<\/a><\/div>\n<div class=\"i2\"><a href=\"#rules\">The rules of Zilch<\/a><\/div>\n<div class=\"i2\"><a href=\"#limitations\">Limitations<\/a><\/div>\n<div class=\"i2\"><a href=\"#analysis\">Analysis<\/a><\/div>\n<div class=\"i3\"><a href=\"#formulation\">Strategy formulation<\/a><\/div>\n<div class=\"i3\"><a href=\"#esn\">Finding E(s,n) &#8211; the Zilch strategy function<\/a><\/div>\n<div class=\"i3\"><a href=\"#allTurn\">Maximizing expected score across all turns<\/a><\/div>\n<div class=\"i2\"><a href=\"#results\">Results<\/a><\/div>\n<div class=\"i3\"><a href=\"#optimal\">The optimal strategies<\/a><\/div>\n<div class=\"i3\"><a href=\"#T0\">Strategy T<sub>0<\/sub>: playing with no consecutive zilches<\/a><\/div>\n<div class=\"i3\"><a href=\"#T1\">Strategy T<sub>1<\/sub>: playing with one consecutive zilch<\/a><\/div>\n<div class=\"i3\"><a href=\"#T2\">Strategy T<sub>2<\/sub>: playing with two consecutive zilches<\/a><\/div>\n<div class=\"i2\"><a href=\"#software\">Software<\/a><\/div>\n<div class=\"i2\"><a href=\"#conclusions\">Conclusions<\/a><\/div>\n<div class=\"i2\"><a href=\"#references\">References<\/a><\/div>\n<\/div>\n<p><a name=\"background\"><\/a><\/p>\n<h2>Background<\/h2>\n<p>I&#8217;ve found several blog postings where folks have offered probabilistic<br \/>\nanalyses of various aspects of the game<sup class=\"ref\"><a href=\"#R2\">2<\/a>,<a href=\"#R3\">3<\/a>,<a href=\"#R4\">4<\/a><\/sup>, but none (that I&#8217;ve seen) find the game<br \/>\nstrategy that maximizes your expected points.  It is possible<br \/>\nthat I&#8217;m the first to publish these solutions.  If not, it was still a fun<br \/>\nproblem.  I&#8217;ve always enjoyed software, algorithms, optimization,<br \/>\nand probabilities and this problem delves into all of these areas.<\/p>\n<p><a name=\"rules\"><\/a><\/p>\n<h2>The Rules of Zilch<\/h2>\n<p>Zilch is played with two players and six six-sided dice.  (Though really<br \/>\nthere&#8217;s nothing to stop you playing with more people, but this is not<br \/>\nsupported in the online game.)<\/p>\n<p>Each player takes turns rolling the dice.  The dice in a roll can be worth<br \/>\npoints either individually or in combination.  If any points are available<br \/>\nfrom the roll, the player must set aside some or all of those scoring dice,<br \/>\nadding the score from those dice to their point total for the turn.  After<br \/>\neach roll, a player may either reroll the remaining dice to try for more<br \/>\npoints or may bank the points accumulated this turn (though you can<br \/>\nnever bank less than 300 points).<\/p>\n<p>If no dice in a roll score, then the player loses all points accumulated<br \/>\nthis turn and their turn is ended.  This is called a zilch, a sorrowful event<br \/>\nindeed.<\/p>\n<p>If all dice in a roll score, the player gets to continue his turn with all<br \/>\nsix dice.  This is called a free roll and is guaranteed to brighten your<br \/>\nday.<\/p>\n<p>A player may continue rolling again and again accumulating ever more points<br \/>\nuntil he either decides to bank those points or loses them all to a zilch.<\/p>\n<p>If a player ends three consecutive turns with a zilch, they not only lose<br \/>\ntheir points from the turn but also lose 500 points from their banked game<br \/>\nscore.  (This is the only way to lose banked points.)  After a triple zilch,<br \/>\nyour consecutive zilch count is reset to zero so you&#8217;re safe from another triple<br \/>\nzilch penalty for at least three more turns.<\/p>\n<p>The game ends when one player has banked a total of 10,000 points and all<br \/>\nother players have had a final turn.<\/p>\n<p>Scoring is as follows:<\/p>\n<ul>\n<li>Each 1 is worth 100 points.<\/li>\n<li>Each 5 is worth 50 points.<\/li>\n<li>A set of three 1s is worth 1000 points.<br \/>\n    A set of three 2s is worth 200 points.<br \/>\n    A set of three 3s is worth 300 points.<br \/>\n    A set of three 4s is worth 400 points.<br \/>\n    A set of three 5s is worth 500 points.<br \/>\n    A set of three 6s is worth 600 points.<br \/>\n    Each extra die in a set doubles the value of the set.  So four 4s are worth 800 points and six 1s are worth 8000.\n<\/li>\n<li>Three pair is worth 1500 points.<\/li>\n<li>A six die straight is worth 1500 points.<\/li>\n<li>Six dice with no other scoring options at all are worth 500 points.  (And<br \/>\nthis is why a 6 die roll is called a free roll:  you can&#8217;t zilch when rolling<br \/>\n6 dice.)<\/li>\n<li>Each die can only be used once when scoring.  (If you roll two 1s, two 2s,<br \/>\nand two 3s you can either count the two 1s for 200 or use all six dice for<br \/>\nthree-pair and 1500 points &mdash; you can&#8217;t use the ones both ways for 1700<br \/>\npoints.)<\/li>\n<\/ul>\n<p><a name=\"limitations\"><\/a><\/p>\n<h2>Limitations<\/h2>\n<p>The strategy presented will maximize your expected Zilch scores, but this<br \/>\nis not necessarily the same strategy that will let you reach 10,000 points in<br \/>\nthe fewest number of turns; and certainly falls short of giving a complete<br \/>\ngaming strategy that will maximize your chances of winning the game<sup><a\nhref=\"#R5\" class=\"ref\">5<\/a><\/sup>, the holy grail of Zilch analysis.  In<br \/>\nparticular, the strategy considers neither your current overall score, nor<br \/>\nyour opponent&#8217;s score, nor the fact that the game ends when a player reaches<br \/>\n10,000 points (after the other player gets a final turn).  All that I offer is<br \/>\na way to maximize your expected Zilch scores.<\/p>\n<p>My intuition is that when you&#8217;re in the lead you should play more<br \/>\nconservatively; and when you&#8217;re behind you should play more aggressively.<br \/>\n(Though I think it a common mistake to be too aggressive too early when behind.)<br \/>\nConsider this extreme example.  Let&#8217;s say you&#8217;re currently beating your<br \/>\nopponent 7500 to 1500 and it&#8217;s your turn.  On your turn you rack up 2500<br \/>\npoints and are faced with the choice of either banking the 2500 or rolling<br \/>\nfive dice to go for more points.  The strategy identified here advises you to<br \/>\nroll the five dice; but surely in this case it is better to bank the 2500,<br \/>\nputting you at the game goal of 10,000 points and forcing your opponent to try<br \/>\nto put out 8550 points in a single turn to steal the win away from you.<\/p>\n<p><a name=\"analysis\"><\/a><\/p>\n<h2>Analysis<\/h2>\n<p><a name=\"formulation\"><\/a><\/p>\n<h3>Strategy Formulation<\/h3>\n<p>I will start by showing how to maximize the expected points for a<br \/>\nparticular turn.  Because of the three consecutive zilch rule, the strategy<br \/>\nthat actually maximizes the average points gained across all turns is<br \/>\ndifferent:  it is possible to trade off some expected gain in those turns<br \/>\nwhere you have either zero or one consecutive zilches to reduce your zilch<br \/>\nprobability and more strongly avoid even getting into a turn where you are<br \/>\nfacing your third consecutive zilch.  I will solve for this more complete<br \/>\nstrategy later, but for now let&#8217;s stick with maximizing the expected points<br \/>\nfor a single turn and just ignore how such a greedy strategy might negatively<br \/>\naffect the outcome of subsequent turns.<\/p>\n<p>For my purposes, a Zilch turn has a state that may be completely defined by<br \/>\ntwo variables (s,&nbsp;n) where s is the number of points accumulated in the<br \/>\ncurrent turn, and n is the number of dice you are about to roll.  At the<br \/>\nbeginning of a new turn, the turn state is (s=0, n=6).  Let&#8217;s say for your<br \/>\nopening roll you throw:<\/p>\n<p style=\"text-align:center\">1, 3, 3, 4, 4, 6<\/p>\n<p>The turn state will then advance to (s=100, n=5).  You actually have no<br \/>\nchoice here:  you must always select at least one scoring die and since the 1<br \/>\n(worth 100 points) is the only scoring die, you must select it.  Furthermore,<br \/>\nyou are not allowed to bank less than 300 points so you must roll the five<br \/>\nremaining dice.<\/p>\n<p>Suppose with the remaining 5 dice you roll:<\/p>\n<p style=\"text-align:center\">1, 1, 2, 3, 5<\/p>\n<p>Here you have three scoring dice:  two 1s and a 5.  You now have a choice<br \/>\nof turn states that you may enter:<\/p>\n<ol style=\"list-style-type: upper-alpha;\">\n<li>(s=150, n=4)  (take just the 5)<\/li>\n<li>(s=200, n=4)  (take a single 1)<\/li>\n<li>(s=250, n=3)  (take a single 1 plus the 5)<\/li>\n<li>(s=300, n=3)  (take the two 1s)<\/li>\n<li>(s=350, n=2)  (take the two 1s plus the 5)<\/li>\n<\/ol>\n<p>Note that s includes not just the points taken from this roll, but also all<br \/>\npoints accumulated in previous rolls during this turn as well.  It should be<br \/>\nclear that state B is better than A and state D is better than C.  Of the<br \/>\nremaining three states (B, D and E) it&#8217;s not so obvious which is better.  You<br \/>\nalso have the option of banking from either of states D or E (but not from B<br \/>\nsince you don&#8217;t have 300 points in that case).  Obviously, banking from state<br \/>\nD is just plain dumb:  if you&#8217;re going to bank you&#8217;ll do so from state E to<br \/>\nbank as many points as you can!  That leaves you with four reasonable<br \/>\nchoices:<\/p>\n<ol>\n<li>enter state B = (s=200, n=4) and roll;<\/li>\n<li>enter state D = (s=300, n=3) and roll;<\/li>\n<li>enter state E = (s=350, n=2) and roll; or<\/li>\n<li>enter state E = (s=350, n=2) and bank.<\/li>\n<\/ol>\n<p>My objective is to find the optimal turn play strategy that defines what to<br \/>\ndo in all such situations which when followed will maximize the expected<br \/>\nnumber of points for the entire turn starting from any given turn state.<\/p>\n<p>Let E(s,&nbsp;n) be the expected number of additional points you will gain for<br \/>\nthe turn if you (perhaps non-optimally) roll while in state (s,&nbsp;n) but then<br \/>\nfollow the optimal turn strategy (which we hope to find) for all subsequent<br \/>\ndecisions in the turn.  Note that E(s,&nbsp;n) includes not just the expected<br \/>\npoints for the upcoming roll, but all the expected points from all subsequent<br \/>\nrolls, if any, as dictated by chance and the optimal play strategy.<\/p>\n<p>Suppose we somehow solve for E(s,&nbsp;n) and find that:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>E(s=200, n=4) =<\/td>\n<td>149<\/td>\n<td width=\"50%\"\/><\/tr>\n<tr>\n<td width=\"50%\"\/>\n<td>E(s=300, n=3) =<\/td>\n<td>34<\/td>\n<td width=\"50%\"\/><\/tr>\n<tr>\n<td width=\"50%\"\/>\n<td>E(s=350, n=2) =<\/td>\n<td>-20<\/td>\n<td width=\"50%\"\/><\/tr>\n<\/table>\n<\/div>\n<p>Applying this information to the example leads to the following final<br \/>\nexpected scores for the turn.<\/p>\n<ol>\n<li>Final expected score by rolling from state B = 200 + 149 = 349.<\/li>\n<li>Final expected score by rolling from state D = 300 + 34 = 334.<\/li>\n<li>Final expected score by rolling from state E = 350 &#8211; 20 = 330.<\/li>\n<li>Final expected score by banking from state E = 350.<\/li>\n<\/ol>\n<p>So, the choice that leads to the highest expected score for the turn is to<br \/>\nbank the 350 points.  From this example, it should be clear that if we can<br \/>\nfind E(s,&nbsp;n) for all possible game states (s,&nbsp;n) we&#8217;ll have the optimal Zilch<br \/>\nturn play strategy.<\/p>\n<p><a name=\"esn\"><\/a><\/p>\n<h3>Finding E(s,n) &#8211; the Zilch strategy function<\/h3>\n<p>Let,<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>T(s, n) = <\/td>\n<td><font size=\"300%\">{<\/font><\/td>\n<td style=\"text-align:left;\">s + max(0, E(s, n))<br \/>s + E(s, n)<\/td>\n<td>&nbsp;for s &ge; 300<br \/>&nbsp;for s &lt; 300<\/td>\n<td width=\"50%\"\/>\n<td>(1)<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>T(s,&nbsp;n) is simply the total expected points for the turn given that<br \/>\nyou are in turn state (s,&nbsp;n) and you follow the optimal strategy.  The<br \/>\nspecial case for s &lt; 300 models the rule that you can&#8217;t bank less than<br \/>\n300 points.  The max function used when s&nbsp;&ge;&nbsp;300 models the<br \/>\nrequirement that you bank when E(s,&nbsp;n) is negative, and roll otherwise.<\/p>\n<p>Suppose we are in some particular state (S,&nbsp;N) then let r<sub>1<\/sub>,<br \/>\nr<sub>2<\/sub>, &hellip; r<sub>R<\/sub> be all possible rolls of N dice that do<br \/>\nnot result in a zilch.  For any given roll r<sub>i<\/sub> you can potentially<br \/>\nenter multiple game states (s<sub>1<\/sub>,&nbsp;n<sub>1<\/sub>),<br \/>\n(s<sub>2<\/sub>,&nbsp;n<sub>2<\/sub>), &hellip;<br \/>\n(s<sub>K<\/sub>,&nbsp;n<sub>K<\/sub>) (depending on which combination of scoring<br \/>\ndice you choose &mdash; just like in the previous example).  Define<br \/>\nC(r<sub>i<\/sub>,&nbsp;S,&nbsp;N) to be the particular scoring combination<br \/>\namong all scoring combinations possible with roll r<sub>i<\/sub> that when applied to turn<br \/>\nstate (S,&nbsp;N) will advance the turn to the new state<br \/>\n(S<sub>i<\/sub>,&nbsp;N<sub>i<\/sub>) that maximizes T.  What could be simpler?<br \/>\nLet C<sub>S<\/sub> be the number of points taken in scoring combination C, and<br \/>\nlet C<sub>N<\/sub> be the number of dice used in scoring combination C.<\/p>\n<p>I also need a simple little function F(n) to reset the state variable n<br \/>\nback to 6 when a score is selected that uses all remaining dice:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>F(n) = <\/td>\n<td><font size=\"+4\">{<\/font><\/td>\n<td>6<br \/>n<\/td>\n<td>&nbsp;for n = 0<br \/>&nbsp;for n &ne; 0<\/td>\n<td width=\"50%\"\/>\n<td>(2)<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>We can now express E(S,&nbsp;N) as a weighted sum of the expected scores of all<br \/>\nstates reachable from (S,&nbsp;N):<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>E(S, N) = -p<sub>N<\/sub>(S+y) + <\/td>\n<td><font size=\"+2\">&sum;<\/font><sub>i<\/sub>&nbsp;<\/td>\n<td>T(S<sub>i<\/sub>, N<sub>i<\/sub>) &#8211; S<\/p>\n<hr noshade=\"noshade\" size=\"1\"\/>6<sup>N<\/sup><\/td>\n<td width=\"50%\"\/>\n<td>(3)<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>where<\/p>\n<div class=\"equation\">\n<center><\/p>\n<table class=\"equationCenter\">\n<tr>\n<td style=\"text-align:right;\">S<sub>i<\/sub><\/td>\n<td>=<\/td>\n<td>S + C<sub>S<\/sub>(r<sub>i<\/sub>, S, N)<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align:right;\">N<sub>i<\/sub><\/td>\n<td>=<\/td>\n<td>F(N &#8211; C<sub>N<\/sub>(r<sub>i<\/sub>, S, N))<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align:right;\">p<sub>N<\/sub><\/td>\n<td>=<\/td>\n<td>probability of zilching when you roll N dice<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align:right;\">y<\/td>\n<td>=<\/td>\n<td>zilch penalty.<\/td>\n<\/tr>\n<\/table>\n<p><\/center>\n<\/div>\n<p>To handle the three zilch rule, I&#8217;ve introduced the constant y which gives<br \/>\nthe additional penalty (beyond loss of all turn points) for rolling a zilch.<br \/>\nSetting y to 0 models turns where you have only zero or one consecutive<br \/>\nzilches.  Setting y to 500 models turns where you are playing with two<br \/>\nconsecutive zilches.  As we shall see, these two cases will lead to two<br \/>\ndifferent turn play strategies.<\/p>\n<p>The term -p<sub>N<\/sub>(S+y) gives the expected decrease in your score due<br \/>\nto the likelihood of a zilch.   The terms<br \/>\n(T(S<sub>i<\/sub>,&nbsp;N<sub>i<\/sub>)&nbsp;&#8211;&nbsp;S) give the expected<br \/>\nincrease in your score given that you throw r<sub>i<\/sub>.  Summing over all<br \/>\npossible r<sub>i<\/sub> and multiplying by the probability of rolling any<br \/>\nparticular r<sub>i<\/sub> gives the appropriate weighted sum.<\/p>\n<p>Equation&nbsp;3 expresses E(S,&nbsp;N) in terms of the T values of all the game<br \/>\nstates reachable from (S,&nbsp;N).  But here&#8217;s the important thing:  any game<br \/>\nstate (s,&nbsp;n) reachable by any roll r from (S,&nbsp;N) has s > S.  (Your<br \/>\nscore can only go up if you don&#8217;t zilch and by definition r is not a zilching<br \/>\nroll.) So, if we already know T(s,&nbsp;n) for all s&nbsp;&gt;&nbsp;S, then we<br \/>\ncan calculate E(S,&nbsp;N) using the above summation.<\/p>\n<p>I claim there exists some large value of accumulated turn points<br \/>\nS<sub>BIG<\/sub> where the optimal turn play strategy is to always bank when<br \/>\nfaced with rolling less than six dice and to always roll when you have six<br \/>\ndice to roll.  If I set S<sub>BIG<\/sub> equal a million points, then I&#8217;m<br \/>\nclaiming that if you&#8217;ve somehow accumulated a million or more points on the<br \/>\ncurrent turn (an absurdly large number of points to be sure) you&#8217;ll want to<br \/>\nbank them if you&#8217;re ever faced with rolling five (or fewer) dice:  the 7%<br \/>\nchance of losing all of your points far outweighs any comparatively meager<br \/>\ngains you might achieve by continuing to roll.  This claim is equivalent to<br \/>\nsaying:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>E(s, n) &lt; 0  for s &ge; S<sub>BIG<\/sub>, 1 &le; n &le; 5<\/td>\n<td width=\"50%\"\/>\n<td>(4)<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>Now if you have six dice to roll, you risk nothing so you might as well<br \/>\nfurther insult your opponent by adding to your million point score.  The<br \/>\nnumber of points you expect to gain in this situation through the end of your<br \/>\nturn is a constant:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>E(s, n) = E<sub>BIG6<\/sub> for s &ge; S<sub>BIG<\/sub>, n = 6<\/td>\n<td width=\"50%\"\/>\n<td>(5)<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>Here&#8217;s how to solve for E<sub>BIG6<\/sub>.  Let<\/p>\n<table>\n<tr>\n<td width=\"20\" rowspan=\"3\"\/>\n<td style=\"vertical-align:top;\">E<sub>B<\/sub><\/td>\n<td style=\"vertical-align:top;\">=<\/td>\n<td style=\"vertical-align:top;\">the expected number of points gained from a single roll of 6 dice given that the roll does not grant another free roll (so you have to bank).<\/td>\n<td width=\"20\" rowspan=\"3\"\/><\/tr>\n<tr>\n<td style=\"vertical-align:top;\">E<sub>F<\/sub><\/td>\n<td style=\"vertical-align:top;\">=<\/td>\n<td style=\"vertical-align:top;\">the expected number of points gained from a single roll of 6 dice given that the roll does grant another free roll.<\/td>\n<\/tr>\n<tr>\n<td style=\"vertical-align:top;\">p<sub>F<\/sub><\/td>\n<td style=\"vertical-align:top;\">=<\/td>\n<td style=\"vertical-align:top;\">probability of a 6 die roll granting another free roll.<\/td>\n<\/tr>\n<\/table>\n<p>These terms are easily calculable by simply enumerating all the six die<br \/>\nrolls and determining the best possible scoring combination in each case.<br \/>\n(There&#8217;s a subtlety here I&#8217;m not going to bore you with regarding how to score<br \/>\na roll of four 1s and a pair of either 2s, 3s, 4s or 6s; I explain this in<br \/>\ndetail in the software comments for the interested reader.)  Once found they<br \/>\ncan be used in the following sum:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>\nE<sub>BIG6<\/sub> = (1-p<sub>F<\/sub>) E<sub>B<\/sub> + p<sub>F<\/sub> (E<sub>F<\/sub> + (1-p<sub>F<\/sub>) E<sub>B<\/sub> + p<sub>F<\/sub> (E<sub>F<\/sub> + &#8230; ))\n<\/td>\n<td width=\"50%\"\/>\n<td>(6)<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>This nicely simplifies to,<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>E<sub>BIG6<\/sub>&nbsp;=&nbsp;<\/td>\n<td>E<sub>B<\/sub> + <\/td>\n<td style=\"text-align:center;\">p<sub>F<\/sub><\/p>\n<hr noshade=\"noshade\" size=\"1\"\/>1-p<sub>F<\/sub><\/td>\n<td>E<sub>F<\/sub><\/td>\n<td width=\"50%\"\/>\n<td>(7)<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>Combining Equations&nbsp;1, 4 and 5 give<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>T(s, n) = <\/td>\n<td><font size=\"300%\">{<\/font><\/td>\n<td style=\"text-align:left;\">s + E<sub>BIG6<\/sub><br \/>s<\/td>\n<td style=\"text-align:left;\">&nbsp;for s &ge; S<sub>BIG<\/sub>, n = 6<br \/>&nbsp;for s &ge; S<sub>BIG<\/sub>, 1 &le; n &le; 5<\/td>\n<td width=\"50%\"\/>\n<td>(8)<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>Knowing T(s,&nbsp;n) for s &ge; S<sub>BIG<\/sub>, we can now use<br \/>\nEquation&nbsp;3 to iteratively calculate E(S<sub>BIG<\/sub> &#8211; 50,&nbsp;n),<br \/>\nE(S<sub>BIG<\/sub> &#8211; 100,&nbsp;n),&nbsp;&hellip; E(0,&nbsp;n).  The rest is<br \/>\njust the grunt work of writing the software to implement the curious function<br \/>\nC; solving for E<sub>BIG6<\/sub>; and solving for all E(s,&nbsp;n) for<br \/>\ns&nbsp;&lt;&nbsp;S<sub>BIG<\/sub>.  (Did I just slander my own profession?)  But<br \/>\nbefore we start grunting let&#8217;s see what we can do about the three consecutive<br \/>\nzilch problem.<\/p>\n<p><a name=\"allTurn\"><\/a><\/p>\n<h3>Maximizing expected score across all turns<\/h3>\n<p>There are actually three different types of turns:<\/p>\n<dl>\n<dd>T<sub>0<\/sub>: a turn played with no previous consecutive zilches,<\/dd>\n<dd>T<sub>1<\/sub>: a turn played with one previous consecutive zilch; and<\/dd>\n<dd>T<sub>2<\/sub>: a turn played with two previous consecutive zilches.<\/dd>\n<\/dl>\n<p>Using the technique already described, we can find the strategies that will<br \/>\nmaximize the expected points in each of these turns independently, but what we<br \/>\nreally want is a strategy for each turn that when used together will maximize<br \/>\nthe average score for all of these turn types when weighted by the frequency<br \/>\nof the appearance of the turn type in a game.<\/p>\n<p>If z<sub>i<\/sub> is the probability of zilching while in turn type<br \/>\nT<sub>i<\/sub> (while following some strategy designed specifically for that<br \/>\nturn type) then we have the state transition diagram shown in Figure 1.<\/p>\n<p><a name=\"figure1\"><img decoding=\"async\" src=\"\/images\/zilchstate.png\" class=\"aligncenter\" alt=\"state\ntransition diagram showing transitions between states T0, T1 and T2\"\/><\/a><\/p>\n<div class=\"caption\">\n<span class=\"heading\">Figure 1.  State transition diagram governing the<br \/>\ntransitions between states T<sub>0<\/sub>, T<sub>1<\/sub> and T<sub>2<\/sub>.<\/span>\n<\/div>\n<p>Performing a steady state analysis of this system we can find the<br \/>\nprobability t<sub>i<\/sub> of being in any particular state T<sub>i<\/sub>.<br \/>\n(I.e., we want to find what fraction of our turns will be of each type.)<br \/>\nWe have these flow equations which must balance:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>\nt<sub>0<\/sub> = (1-z<sub>0<\/sub>)t<sub>0<\/sub> + (1-z<sub>1<\/sub>)t<sub>1<\/sub> + t<sub>2<\/sub><br \/>\nt<sub>1<\/sub> = z<sub>0<\/sub>t<sub>0<\/sub><br \/>\nt<sub>2<\/sub> = z<sub>1<\/sub>t<sub>1<\/sub>\n<\/td>\n<td width=\"50%\"\/>\n<\/tr>\n<\/table>\n<\/div>\n<p>Also<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>\nt<sub>0<\/sub> + t<sub>1<\/sub> + t<sub>2<\/sub> = 1\n<\/td>\n<td width=\"50%\"\/>\n<\/tr>\n<\/table>\n<\/div>\n<p>Solving gives<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>\nt<sub>0<\/sub> = 1 \/ (1 + z<sub>0<\/sub> + z<sub>0<\/sub>z<sub>1<\/sub>)<br \/>\nt<sub>1<\/sub> = z<sub>0<\/sub> \/ (1 + z<sub>0<\/sub> + z<sub>0<\/sub>z<sub>1<\/sub>)<br \/>\nt<sub>2<\/sub> = z<sub>0<\/sub>z<sub>1<\/sub> \/ (1 + z<sub>0<\/sub> + z<sub>0<\/sub>z<sub>1<\/sub>)\n<\/td>\n<td width=\"50%\"\/>\n<\/tr>\n<\/table>\n<\/div>\n<p>Define E<sub>i<\/sub> to be the expected points gained for a turn of type<br \/>\nT<sub>i<\/sub>.  Then the average score for all turns is:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>\nE<sub>AVG<\/sub> = t<sub>0<\/sub>E<sub>0<\/sub> + t<sub>1<\/sub>E<sub>1<\/sub> + t<sub>2<\/sub>E<sub>2<\/sub>\n<\/td>\n<td width=\"50%\"\/>\n<\/tr>\n<\/table>\n<\/div>\n<p>or<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>E<sub>AVG<\/sub> =<\/td>\n<td style=\"text-align:center;\">E<sub>0<\/sub> + z<sub>0<\/sub>E<sub>1<\/sub> + z<sub>0<\/sub>z<sub>1<\/sub>E<sub>2<\/sub><\/p>\n<hr\/>\n<p> 1 + z<sub>0<\/sub> + z<sub>0<\/sub>z<sub>1<\/sub>\n<\/td>\n<td width=\"50%\"\/>\n<td>(9)<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>E<sub>AVG<\/sub> is what we want to maximize.  Both E<sub>i<\/sub> and<br \/>\nz<sub>i<\/sub> are just a function of the strategy used to play a turn of type<br \/>\nT<sub>i<\/sub>.  The strategy employed for T<sub>2<\/sub> only affects<br \/>\nE<sub>2<\/sub>, so E<sub>2<\/sub> can be independently maximized &mdash;<br \/>\nsomething we already know how to do.  That leaves the strategies for<br \/>\nT<sub>0<\/sub> and T<sub>1<\/sub>.  E<sub>2<\/sub> is the term that&#8217;s pulling<br \/>\ndown our average score since it&#8217;s the turn played with the 500 point penalty<br \/>\nfor zilching.  Can we modify our strategies for T<sub>0<\/sub> and\/or<br \/>\nT<sub>1<\/sub> in such a way so as to trade off some of our expected gains in<br \/>\nthose turns to reduce the coefficient z<sub>0<\/sub>z<sub>1<\/sub> on<br \/>\nE<sub>2<\/sub> and thereby actually increase E<sub>AVG<\/sub>?<\/p>\n<p>In Equation&nbsp;3, I introduced the variable y to model the penalty for a<br \/>\nzilch in a game.  I said it should be set to 0 normally, but set to 500 if we<br \/>\nare playing a turn where the third consecutive zilch is imminent.  If we<br \/>\nextend this idea and allow y to become a free variable, we can examine<br \/>\ndifferent levels of trade-off between expected score and the probability of<br \/>\nzilching.  For each y value, we&#8217;ll find the optimal strategy given that zilch<br \/>\npenalty; and then find both the expected number of points per turn and the<br \/>\nprobability of zilching on the turn for that strategy.  E<sub>AVG<\/sub> then<br \/>\nbecomes a function of just two variables y<sub>0<\/sub> and y<sub>1<\/sub>.  We<br \/>\nthen need only to find the particular values Y<sub>0<\/sub> and Y<sub>1<\/sub><br \/>\nthat maximize E<sub>AVG<\/sub>.  Piece of cake!<\/p>\n<p>When doing this analysis, it&#8217;s important to understand that the penalties<br \/>\ny<sub>0<\/sub> and y<sub>1<\/sub> are artificial.  The true zilch penalty for<br \/>\nthese turns is of course zero.  Accordingly, the values calculated for E(s,&nbsp;n)<br \/>\nwill not represent the true expected change in points for the turn from state (s,&nbsp;n).<br \/>\nBut the values E(s,&nbsp;n) <i>do<\/i> still define a strategy, dictating that you<br \/>\nroll if E(s,&nbsp;n) is positive, and that you bank when E(s,&nbsp;n) is negative.<br \/>\nLikewise, the E(s,&nbsp;n) values are still used in the normal way to determine<br \/>\nwhich state among the reachable states after a roll is most desirable.<br \/>\nTo get the actual expected increase in score from state<br \/>\n(s,&nbsp;n), you must add back the false zilch penalty times the probability<br \/>\nof zilching for the remainder of the turn.  Although you could calculate this<br \/>\nfor all states (s,&nbsp;n); we only really need to know the true expectation<br \/>\nfor the turn as a whole, which we can get by correcting E(0,&nbsp;6).  This<br \/>\ngives rise to the notion of a corrected expectation for the turn:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\"\/>\n<td>E<sub>C<\/sub> = E(0,6) + yz<\/td>\n<td width=\"50%\"\/>\n<td>(10)<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>Enough analysis!  On to the results!  Now I am become death, destroyer of<br \/>\nZilch.<\/p>\n<p><a name=\"results\"><\/a><\/p>\n<h2>Results<\/h2>\n<p><a name=\"optimal\"><\/a><\/p>\n<h3>The optimal strategies<\/h3>\n<p>I wrote a little java program that solves for E<sub>BIG6<\/sub>; finds E(s,n) for a<br \/>\nsupplied zilch penalty, y; for that strategy, calculates the probability of<br \/>\nzilching, z; and also outputs the corrected expected points for the turn, E<sub>C<\/sub>.<br \/>\nRunning the software for the case y=0 we get:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\" rowspan=\"3\"\/>\n<td style=\"text-align:right;\">E<sub>BIG6<\/sub> = <\/td>\n<td>478.237<\/td>\n<td width=\"50%\" rowspan=\"3\"\/><\/tr>\n<tr>\n<td style=\"text-align:right;\">E<sub>C<\/sub> = E(0, 6) = <\/td>\n<td>623.017<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align:right;\">z =<\/td>\n<td nowrap=\"nowrap\">.193326<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>So the best you can do for a single turn is to rack up an average of about<br \/>\n623 points, and zilch about 1 time in 5.  I&#8217;ll get to the actual strategy<br \/>\ntables shortly, but first let&#8217;s solve for the optimal strategies required for<br \/>\nthe three zilch rule for turn types T<sub>0<\/sub>, T<sub>1<\/sub> and<br \/>\nT<sub>2<\/sub>.<\/p>\n<p>Finding the best strategy for T<sub>2<\/sub> is easy:  just set y=500 and<br \/>\nyou get these results:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\" class=\"equationCenter\">\n<tr>\n<td width=\"50%\" rowspan=\"3\"\/>\n<td style=\"text-align:right;\">E<sub>2<\/sub> = E(0, 6) = <\/td>\n<td>547.157<\/td>\n<td width=\"50%\" rowspan=\"3\"\/><\/tr>\n<tr>\n<td style=\"text-align:right;\">z<sub>2<\/sub> = <\/td>\n<td>.132148<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>You don&#8217;t use E<sub>C<\/sub> here since the 500 point zilch penalty is not<br \/>\nartificial but real.  This penalty reduces the maximum expected points per<br \/>\nturn by about 12%.  The more conservative play required here also reduces the<br \/>\nzilch probability by about a third.<\/p>\n<p>To find the best strategies for T<sub>0<\/sub> and T<sub>1<\/sub> we need to<br \/>\nlet the zilch penalty for those two turn types (y<sub>0<\/sub> and<br \/>\ny<sub>1<\/sub>) vary and then maximize E<sub>AVG<\/sub> as given by<br \/>\nEquation&nbsp;9.  Table&nbsp;1 shows how varying the penalty for zilching (y)<br \/>\naffects the probability of zilching (z) and the corrected expected points per<br \/>\nturn (E<sub>C<\/sub>).  Due to the integral nature of the problem, there are<br \/>\nfairly large ranges of y that have no affect on the strategy.  I&#8217;m only<br \/>\nlisting y values among those tried that produced a strategy change:<\/p>\n<div class=\"caption\">\n<span class=\"heading\">Table&nbsp;1.  Probability of zilching for the turn, z, and<br \/>\ncorrected expected score, E<sub>C<\/sub>, as a function of the zilch penalty,<br \/>\ny.<\/span>\n<\/div>\n<table class=\"data\">\n<tr>\n<th>y<\/th>\n<th>z<\/th>\n<th>E<sub>C<\/sub><\/th>\n<\/tr>\n<tr class=\"datashaded\">\n<td>0<\/td>\n<td>0.193326<\/td>\n<td>623.017489<\/td>\n<\/tr>\n<tr>\n<td>10<\/td>\n<td>0.193326<\/td>\n<td>623.017488<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>15<\/td>\n<td>0.193302<\/td>\n<td>623.017141<\/td>\n<\/tr>\n<tr>\n<td>17<\/td>\n<td>0.193296<\/td>\n<td>623.017049<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>22<\/td>\n<td>0.190399<\/td>\n<td>622.955542<\/td>\n<\/tr>\n<tr>\n<td>24<\/td>\n<td>0.182110<\/td>\n<td>622.759187<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>26<\/td>\n<td>0.178151<\/td>\n<td>622.657753<\/td>\n<\/tr>\n<tr>\n<td>27<\/td>\n<td>0.177759<\/td>\n<td>622.647306<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>30<\/td>\n<td>0.177757<\/td>\n<td>622.647238<\/td>\n<\/tr>\n<tr>\n<td>38<\/td>\n<td>0.177723<\/td>\n<td>622.645977<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>42<\/td>\n<td>0.177619<\/td>\n<td>622.641662<\/td>\n<\/tr>\n<tr>\n<td>44<\/td>\n<td>0.174575<\/td>\n<td>622.509618<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>65<\/td>\n<td>0.174551<\/td>\n<td>622.508057<\/td>\n<\/tr>\n<tr>\n<td>67<\/td>\n<td>0.174543<\/td>\n<td>622.507569<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>68<\/td>\n<td>0.170991<\/td>\n<td>622.268940<\/td>\n<\/tr>\n<tr>\n<td>72<\/td>\n<td>0.170988<\/td>\n<td>622.268745<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>77<\/td>\n<td>0.170631<\/td>\n<td>622.241338<\/td>\n<\/tr>\n<tr>\n<td>80<\/td>\n<td>0.170620<\/td>\n<td>622.240487<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>88<\/td>\n<td>0.170484<\/td>\n<td>622.228569<\/td>\n<\/tr>\n<tr>\n<td>92<\/td>\n<td>0.170389<\/td>\n<td>622.219825<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>115<\/td>\n<td>0.170387<\/td>\n<td>622.219696<\/td>\n<\/tr>\n<tr>\n<td>117<\/td>\n<td>0.170383<\/td>\n<td>622.219130<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>122<\/td>\n<td>0.157678<\/td>\n<td>620.678963<\/td>\n<\/tr>\n<tr>\n<td>127<\/td>\n<td>0.157507<\/td>\n<td>620.657322<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>130<\/td>\n<td>0.157498<\/td>\n<td>620.656168<\/td>\n<\/tr>\n<tr>\n<td>138<\/td>\n<td>0.157427<\/td>\n<td>620.646349<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>142<\/td>\n<td>0.157364<\/td>\n<td>620.637441<\/td>\n<\/tr>\n<tr>\n<td>165<\/td>\n<td>0.157362<\/td>\n<td>620.637123<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>167<\/td>\n<td>0.157357<\/td>\n<td>620.636297<\/td>\n<\/tr>\n<tr>\n<td>172<\/td>\n<td>0.157356<\/td>\n<td>620.636150<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>177<\/td>\n<td>0.157286<\/td>\n<td>620.623706<\/td>\n<\/tr>\n<tr>\n<td>180<\/td>\n<td>0.157271<\/td>\n<td>620.620945<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>188<\/td>\n<td>0.157239<\/td>\n<td>620.615023<\/td>\n<\/tr>\n<tr>\n<td>192<\/td>\n<td>0.157171<\/td>\n<td>620.602036<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>203<\/td>\n<td>0.144131<\/td>\n<td>617.962533<\/td>\n<\/tr>\n<tr>\n<td>215<\/td>\n<td>0.144129<\/td>\n<td>617.962108<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>217<\/td>\n<td>0.144120<\/td>\n<td>617.960165<\/td>\n<\/tr>\n<tr>\n<td>222<\/td>\n<td>0.143469<\/td>\n<td>617.816023<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>227<\/td>\n<td>0.143448<\/td>\n<td>617.811242<\/td>\n<\/tr>\n<tr>\n<td>230<\/td>\n<td>0.143424<\/td>\n<td>617.805798<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>231<\/td>\n<td>0.142245<\/td>\n<td>617.534058<\/td>\n<\/tr>\n<tr>\n<td>235<\/td>\n<td>0.140672<\/td>\n<td>617.165031<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>238<\/td>\n<td>0.140661<\/td>\n<td>617.162252<\/td>\n<\/tr>\n<tr>\n<td>242<\/td>\n<td>0.140573<\/td>\n<td>617.141121<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>265<\/td>\n<td>0.140572<\/td>\n<td>617.140733<\/td>\n<\/tr>\n<tr>\n<td>267<\/td>\n<td>0.140558<\/td>\n<td>617.137106<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>272<\/td>\n<td>0.140556<\/td>\n<td>617.136678<\/td>\n<\/tr>\n<tr>\n<td>277<\/td>\n<td>0.140553<\/td>\n<td>617.135694<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>280<\/td>\n<td>0.140521<\/td>\n<td>617.126870<\/td>\n<\/tr>\n<tr>\n<td>288<\/td>\n<td>0.140519<\/td>\n<td>617.126208<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>292<\/td>\n<td>0.140413<\/td>\n<td>617.095273<\/td>\n<\/tr>\n<tr>\n<td>315<\/td>\n<td>0.140411<\/td>\n<td>617.094663<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>317<\/td>\n<td>0.140401<\/td>\n<td>617.091542<\/td>\n<\/tr>\n<tr>\n<td>322<\/td>\n<td>0.140391<\/td>\n<td>617.088225<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>327<\/td>\n<td>0.140390<\/td>\n<td>617.088121<\/td>\n<\/tr>\n<tr>\n<td>330<\/td>\n<td>0.140376<\/td>\n<td>617.083493<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>338<\/td>\n<td>0.140376<\/td>\n<td>617.083407<\/td>\n<\/tr>\n<tr>\n<td>340<\/td>\n<td>0.140343<\/td>\n<td>617.072035<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>342<\/td>\n<td>0.140031<\/td>\n<td>616.965512<\/td>\n<\/tr>\n<tr>\n<td>365<\/td>\n<td>0.140029<\/td>\n<td>616.964776<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>367<\/td>\n<td>0.139995<\/td>\n<td>616.952543<\/td>\n<\/tr>\n<tr>\n<td>372<\/td>\n<td>0.139981<\/td>\n<td>616.947224<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>380<\/td>\n<td>0.139967<\/td>\n<td>616.942009<\/td>\n<\/tr>\n<tr>\n<td>392<\/td>\n<td>0.139576<\/td>\n<td>616.788919<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>415<\/td>\n<td>0.139575<\/td>\n<td>616.788296<\/td>\n<\/tr>\n<tr>\n<td>417<\/td>\n<td>0.139555<\/td>\n<td>616.780056<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>422<\/td>\n<td>0.139544<\/td>\n<td>616.775513<\/td>\n<\/tr>\n<tr>\n<td>430<\/td>\n<td>0.139522<\/td>\n<td>616.765914<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>442<\/td>\n<td>0.139326<\/td>\n<td>616.679483<\/td>\n<\/tr>\n<tr>\n<td>465<\/td>\n<td>0.139325<\/td>\n<td>616.678925<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>467<\/td>\n<td>0.139318<\/td>\n<td>616.675611<\/td>\n<\/tr>\n<tr>\n<td>472<\/td>\n<td>0.139308<\/td>\n<td>616.670956<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>480<\/td>\n<td>0.139279<\/td>\n<td>616.657114<\/td>\n<\/tr>\n<tr>\n<td>481<\/td>\n<td>0.132230<\/td>\n<td>613.270797<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>492<\/td>\n<td>0.132148<\/td>\n<td>613.230640<\/td>\n<\/tr>\n<\/table>\n<p>Pumping this table through a little awk script (which I hacked out at a<br \/>\ncommand prompt and didn&#8217;t save for you), I found that E<sub>AVG<\/sub> is<br \/>\nmaximized when Y<sub>0<\/sub>&nbsp;=&nbsp;0 and Y<sub>1<\/sub>&nbsp;=&nbsp;72.  Here are the summary<br \/>\nstatistics:<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\">\n<tr>\n<td width=\"50%\" rowspan=\"11\"\/>\n<td nowrap=\"nowrap\">y<sub>0<\/sub> =<\/td>\n<td>0<\/td>\n<td width=\"50%\" rowspan=\"11\"\/><\/tr>\n<tr>\n<td nowrap=\"nowrap\">z<sub>0<\/sub> =<\/td>\n<td>.193326<\/td>\n<\/tr>\n<tr>\n<td nowrap=\"nowrap\">E<sub>0<\/sub> =<\/td>\n<td>623.017<\/td>\n<\/tr>\n<tr>\n<td nowrap=\"nowrap\">&nbsp;<\/td>\n<\/tr>\n<tr>\n<td nowrap=\"nowrap\">y<sub>1<\/sub> =<\/td>\n<td>72<\/td>\n<\/tr>\n<tr>\n<td nowrap=\"nowrap\">z<sub>1<\/sub> =<\/td>\n<td>.170988<\/td>\n<\/tr>\n<tr>\n<td nowrap=\"nowrap\">E<sub>1<\/sub> =<\/td>\n<td>622.269<\/td>\n<\/tr>\n<tr>\n<td nowrap=\"nowrap\">&nbsp;<\/td>\n<\/tr>\n<tr>\n<td nowrap=\"nowrap\">y<sub>2<\/sub> =<\/td>\n<td>500<\/td>\n<\/tr>\n<tr>\n<td nowrap=\"nowrap\">z<sub>2<\/sub> =<\/td>\n<td>.132148<\/td>\n<\/tr>\n<tr>\n<td nowrap=\"nowrap\">E<sub>2<\/sub> =<\/td>\n<td>547.157<\/td>\n<\/tr>\n<\/table>\n<\/div>\n<p>This gives<\/p>\n<div class=\"equation\">\n<table align=\"center\" width=\"100%\">\n<tr>\n<td width=\"50%\"\/>\n<td nowrap=\"nowrap\">E<sub>AVG<\/sub> = 620.855<\/td>\n<td width=\"50%\"\/>\n<\/tr>\n<\/table>\n<\/div>\n<p>For turn type T<sub>0<\/sub>, you&#8217;re best off just going for the maximum<br \/>\nexpected points possible:  trying to play more conservatively doesn&#8217;t reduce<br \/>\nyour zilch probability (or the probability of entering state T<sub>2<\/sub>)<br \/>\nenough to offset the corresponding loss in expected points for turns of type<br \/>\nT<sub>0<\/sub>.<\/p>\n<p>For turn type T<sub>1<\/sub> (when you&#8217;ve got one consecutive zilch) you&#8217;re<br \/>\nbest off pretending you will be penalized an extra 72 points if you zilch.<br \/>\nThis reduces your expected score by only 0.2% but reduces your probability of<br \/>\nzilching by about 10%.  This little extra protection against your third<br \/>\nconsecutive zilch slightly increases your overall average turn scores.<\/p>\n<p>Let&#8217;s move on to the actual strategies.<\/p>\n<p><a name=\"T0\"><\/a><\/p>\n<h3>Strategy T<sub>0<\/sub>: playing with no consecutive zilches<\/h3>\n<p>Table&nbsp;2 below gives E(s,&nbsp;n) for all s &le; 3200 for the case y&nbsp;=&nbsp;0.  This is<br \/>\nthe strategy achieving the maximum expected points for a turn and is the best<br \/>\nstrategy to use if you didn&#8217;t zilch on your previous turn.  The first table<br \/>\nentry is E<sub>BIG6<\/sub>&nbsp;=&nbsp;478.237.  The last table entry gives the total<br \/>\nexpected points for the turn:  E<sub>0<\/sub>&nbsp;=&nbsp;623.017.  The probability of<br \/>\nzilching for the entire turn (not shown in the table) is z<sub>0<\/sub>&nbsp;=&nbsp;.193326.<\/p>\n<div class=\"caption\">\n<span class=\"heading\">Table&nbsp;2.  E(s,n) for turn type T<sub>0<\/sub>.<\/span>\n<\/div>\n<table class=\"data\">\n<tr>\n<th style=\"background-color:#ccc\"><\/th>\n<th colspan=\"6\">n<\/th>\n<\/tr>\n<tr>\n<th>s<\/th>\n<th width=\"15%\">6<\/th>\n<th width=\"15%\">5<\/th>\n<th width=\"15%\">4<\/th>\n<th width=\"15%\">3<\/th>\n<th width=\"15%\">2<\/th>\n<th width=\"15%\">1<\/th>\n<\/tr>\n<tr class=\"datashaded\">\n<td>3200<\/td>\n<td>478.237<\/td>\n<td>-6.608<\/td>\n<td>-340.997<\/td>\n<td>-775.515<\/td>\n<td>-1319.085<\/td>\n<td>-1948.921<\/td>\n<\/tr>\n<tr>\n<td>3150<\/td>\n<td>478.237<\/td>\n<td>-2.750<\/td>\n<td>-333.126<\/td>\n<td>-761.626<\/td>\n<td>-1296.863<\/td>\n<td>-1915.588<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>3100<\/td>\n<td>478.237<\/td>\n<td>1.108<\/td>\n<td>-325.256<\/td>\n<td>-747.737<\/td>\n<td>-1274.640<\/td>\n<td>-1882.254<\/td>\n<\/tr>\n<tr>\n<td>3050<\/td>\n<td>478.323<\/td>\n<td>4.966<\/td>\n<td>-317.386<\/td>\n<td>-733.848<\/td>\n<td>-1252.418<\/td>\n<td>-1848.921<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>3000<\/td>\n<td>478.706<\/td>\n<td>8.824<\/td>\n<td>-309.515<\/td>\n<td>-719.959<\/td>\n<td>-1230.196<\/td>\n<td>-1815.573<\/td>\n<\/tr>\n<tr>\n<td>2950<\/td>\n<td>479.301<\/td>\n<td>12.682<\/td>\n<td>-301.645<\/td>\n<td>-706.070<\/td>\n<td>-1207.971<\/td>\n<td>-1782.162<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2900<\/td>\n<td>479.897<\/td>\n<td>16.540<\/td>\n<td>-293.774<\/td>\n<td>-692.181<\/td>\n<td>-1185.734<\/td>\n<td>-1748.665<\/td>\n<\/tr>\n<tr>\n<td>2850<\/td>\n<td>480.492<\/td>\n<td>20.398<\/td>\n<td>-285.904<\/td>\n<td>-678.291<\/td>\n<td>-1163.471<\/td>\n<td>-1715.134<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2800<\/td>\n<td>481.088<\/td>\n<td>24.256<\/td>\n<td>-278.033<\/td>\n<td>-664.394<\/td>\n<td>-1141.189<\/td>\n<td>-1681.602<\/td>\n<\/tr>\n<tr>\n<td>2750<\/td>\n<td>481.683<\/td>\n<td>28.114<\/td>\n<td>-270.161<\/td>\n<td>-650.488<\/td>\n<td>-1118.900<\/td>\n<td>-1648.070<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2700<\/td>\n<td>482.278<\/td>\n<td>31.973<\/td>\n<td>-262.286<\/td>\n<td>-636.578<\/td>\n<td>-1096.612<\/td>\n<td>-1614.538<\/td>\n<\/tr>\n<tr>\n<td>2650<\/td>\n<td>482.874<\/td>\n<td>35.833<\/td>\n<td>-254.407<\/td>\n<td>-622.667<\/td>\n<td>-1074.324<\/td>\n<td>-1581.006<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2600<\/td>\n<td>483.470<\/td>\n<td>39.694<\/td>\n<td>-246.527<\/td>\n<td>-608.754<\/td>\n<td>-1052.035<\/td>\n<td>-1547.475<\/td>\n<\/tr>\n<tr>\n<td>2550<\/td>\n<td>484.069<\/td>\n<td>43.558<\/td>\n<td>-238.645<\/td>\n<td>-594.840<\/td>\n<td>-1029.747<\/td>\n<td>-1513.943<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2500<\/td>\n<td>484.677<\/td>\n<td>47.423<\/td>\n<td>-230.761<\/td>\n<td>-580.924<\/td>\n<td>-1007.458<\/td>\n<td>-1480.410<\/td>\n<\/tr>\n<tr>\n<td>2450<\/td>\n<td>485.290<\/td>\n<td>51.290<\/td>\n<td>-222.876<\/td>\n<td>-567.008<\/td>\n<td> -985.170<\/td>\n<td>-1446.876<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2400<\/td>\n<td>485.975<\/td>\n<td>55.157<\/td>\n<td>-214.989<\/td>\n<td>-553.089<\/td>\n<td> -962.881<\/td>\n<td>-1413.339<\/td>\n<\/tr>\n<tr>\n<td>2350<\/td>\n<td>486.949<\/td>\n<td>59.026<\/td>\n<td>-207.101<\/td>\n<td>-539.170<\/td>\n<td> -940.591<\/td>\n<td>-1379.789<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2300<\/td>\n<td>488.222<\/td>\n<td>62.896<\/td>\n<td>-199.211<\/td>\n<td>-525.251<\/td>\n<td> -918.299<\/td>\n<td>-1346.179<\/td>\n<\/tr>\n<tr>\n<td>2250<\/td>\n<td>489.496<\/td>\n<td>66.767<\/td>\n<td>-191.320<\/td>\n<td>-511.331<\/td>\n<td> -895.995<\/td>\n<td>-1312.472<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2200<\/td>\n<td>490.771<\/td>\n<td>70.640<\/td>\n<td>-183.429<\/td>\n<td>-497.410<\/td>\n<td> -873.664<\/td>\n<td>-1278.714<\/td>\n<\/tr>\n<tr>\n<td>2150<\/td>\n<td>492.048<\/td>\n<td>74.513<\/td>\n<td>-175.538<\/td>\n<td>-483.482<\/td>\n<td> -851.309<\/td>\n<td>-1244.955<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2100<\/td>\n<td>493.326<\/td>\n<td>78.386<\/td>\n<td>-167.645<\/td>\n<td>-469.545<\/td>\n<td> -828.945<\/td>\n<td>-1211.197<\/td>\n<\/tr>\n<tr>\n<td>2050<\/td>\n<td>494.604<\/td>\n<td>82.260<\/td>\n<td>-159.748<\/td>\n<td>-455.601<\/td>\n<td> -806.581<\/td>\n<td>-1177.438<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2000<\/td>\n<td>495.884<\/td>\n<td>86.136<\/td>\n<td>-151.848<\/td>\n<td>-441.655<\/td>\n<td> -784.217<\/td>\n<td>-1143.678<\/td>\n<\/tr>\n<tr>\n<td>1950<\/td>\n<td>497.164<\/td>\n<td>90.013<\/td>\n<td>-143.944<\/td>\n<td>-427.706<\/td>\n<td> -761.853<\/td>\n<td>-1109.919<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1900<\/td>\n<td>498.448<\/td>\n<td>93.894<\/td>\n<td>-136.037<\/td>\n<td>-413.755<\/td>\n<td> -739.488<\/td>\n<td>-1076.159<\/td>\n<\/tr>\n<tr>\n<td>1850<\/td>\n<td>499.740<\/td>\n<td>97.776<\/td>\n<td>-128.128<\/td>\n<td>-399.802<\/td>\n<td> -717.124<\/td>\n<td>-1042.398<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1800<\/td>\n<td>501.041<\/td>\n<td>101.661<\/td>\n<td>-120.218<\/td>\n<td>-385.848<\/td>\n<td> -694.759<\/td>\n<td>-1008.635<\/td>\n<\/tr>\n<tr>\n<td>1750<\/td>\n<td>502.344<\/td>\n<td>105.547<\/td>\n<td>-112.306<\/td>\n<td>-371.893<\/td>\n<td> -672.394<\/td>\n<td> -974.870<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1700<\/td>\n<td>503.867<\/td>\n<td>109.434<\/td>\n<td>-104.392<\/td>\n<td>-357.936<\/td>\n<td> -650.029<\/td>\n<td> -941.102<\/td>\n<\/tr>\n<tr>\n<td>1650<\/td>\n<td>505.684<\/td>\n<td>113.323<\/td>\n<td>-96.476<\/td>\n<td>-343.979<\/td>\n<td> -627.662<\/td>\n<td> -907.298<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1600<\/td>\n<td>507.502<\/td>\n<td>117.213<\/td>\n<td>-88.558<\/td>\n<td>-330.022<\/td>\n<td> -605.289<\/td>\n<td> -873.408<\/td>\n<\/tr>\n<tr>\n<td>1550<\/td>\n<td>509.327<\/td>\n<td>121.105<\/td>\n<td>-80.641<\/td>\n<td>-316.064<\/td>\n<td> -582.895<\/td>\n<td> -839.469<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1500<\/td>\n<td>511.172<\/td>\n<td>124.998<\/td>\n<td>-72.723<\/td>\n<td>-302.102<\/td>\n<td> -560.480<\/td>\n<td> -805.529<\/td>\n<\/tr>\n<tr>\n<td>1450<\/td>\n<td>513.033<\/td>\n<td>128.891<\/td>\n<td>-64.805<\/td>\n<td>-288.132<\/td>\n<td> -538.055<\/td>\n<td> -771.583<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1400<\/td>\n<td>514.894<\/td>\n<td>132.784<\/td>\n<td>-56.883<\/td>\n<td>-274.156<\/td>\n<td> -515.630<\/td>\n<td> -737.633<\/td>\n<\/tr>\n<tr>\n<td>1350<\/td>\n<td>516.756<\/td>\n<td>136.679<\/td>\n<td>-48.958<\/td>\n<td>-260.177<\/td>\n<td> -493.203<\/td>\n<td> -703.679<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1300<\/td>\n<td>518.619<\/td>\n<td>140.575<\/td>\n<td>-41.030<\/td>\n<td>-246.196<\/td>\n<td> -470.774<\/td>\n<td> -669.725<\/td>\n<\/tr>\n<tr>\n<td>1250<\/td>\n<td>520.484<\/td>\n<td>144.474<\/td>\n<td>-33.100<\/td>\n<td>-232.212<\/td>\n<td> -448.345<\/td>\n<td> -635.771<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1200<\/td>\n<td>522.356<\/td>\n<td>148.374<\/td>\n<td>-25.167<\/td>\n<td>-218.227<\/td>\n<td> -425.916<\/td>\n<td> -601.816<\/td>\n<\/tr>\n<tr>\n<td>1150<\/td>\n<td>524.236<\/td>\n<td>152.277<\/td>\n<td>-17.233<\/td>\n<td>-204.240<\/td>\n<td> -403.487<\/td>\n<td> -567.860<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1100<\/td>\n<td>526.119<\/td>\n<td>156.180<\/td>\n<td>-9.297<\/td>\n<td>-190.252<\/td>\n<td> -381.057<\/td>\n<td> -533.901<\/td>\n<\/tr>\n<tr>\n<td>1050<\/td>\n<td>528.180<\/td>\n<td>160.085<\/td>\n<td>-1.360<\/td>\n<td>-176.263<\/td>\n<td> -358.627<\/td>\n<td> -499.941<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1000<\/td>\n<td>530.368<\/td>\n<td>163.992<\/td>\n<td>6.579<\/td>\n<td>-162.273<\/td>\n<td> -336.196<\/td>\n<td> -465.950<\/td>\n<\/tr>\n<tr>\n<td>950<\/td>\n<td>532.560<\/td>\n<td>168.763<\/td>\n<td>14.520<\/td>\n<td>-148.283<\/td>\n<td> -313.760<\/td>\n<td> -431.909<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>900<\/td>\n<td>534.870<\/td>\n<td>174.577<\/td>\n<td>22.461<\/td>\n<td>-134.293<\/td>\n<td> -291.310<\/td>\n<td> -397.845<\/td>\n<\/tr>\n<tr>\n<td>850<\/td>\n<td>537.684<\/td>\n<td>180.570<\/td>\n<td>30.403<\/td>\n<td>-120.299<\/td>\n<td> -268.848<\/td>\n<td> -363.762<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>800<\/td>\n<td>540.959<\/td>\n<td>186.564<\/td>\n<td>38.345<\/td>\n<td>-106.301<\/td>\n<td> -246.379<\/td>\n<td> -329.574<\/td>\n<\/tr>\n<tr>\n<td>750<\/td>\n<td>544.307<\/td>\n<td>192.559<\/td>\n<td>46.289<\/td>\n<td>-92.299<\/td>\n<td> -223.889<\/td>\n<td> -295.226<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>700<\/td>\n<td>547.655<\/td>\n<td>198.555<\/td>\n<td>54.235<\/td>\n<td>-78.294<\/td>\n<td> -201.356<\/td>\n<td> -260.789<\/td>\n<\/tr>\n<tr>\n<td>650<\/td>\n<td>551.006<\/td>\n<td>204.879<\/td>\n<td>62.183<\/td>\n<td>-64.276<\/td>\n<td> -178.780<\/td>\n<td> -226.340<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>600<\/td>\n<td>554.457<\/td>\n<td>212.146<\/td>\n<td>70.136<\/td>\n<td>-50.240<\/td>\n<td> -156.188<\/td>\n<td> -191.890<\/td>\n<\/tr>\n<tr>\n<td>550<\/td>\n<td>558.365<\/td>\n<td>219.989<\/td>\n<td>78.096<\/td>\n<td>-36.194<\/td>\n<td> -133.594<\/td>\n<td> -157.423<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>500<\/td>\n<td>562.820<\/td>\n<td>227.838<\/td>\n<td>86.062<\/td>\n<td>-22.143<\/td>\n<td> -110.997<\/td>\n<td> -122.863<\/td>\n<\/tr>\n<tr>\n<td>450<\/td>\n<td>567.530<\/td>\n<td>235.694<\/td>\n<td>94.033<\/td>\n<td>-8.089<\/td>\n<td>-88.381<\/td>\n<td>-88.136<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>400<\/td>\n<td>572.248<\/td>\n<td>243.557<\/td>\n<td>102.010<\/td>\n<td>5.970<\/td>\n<td>-65.722<\/td>\n<td>-53.275<\/td>\n<\/tr>\n<tr>\n<td>350<\/td>\n<td>576.985<\/td>\n<td>251.428<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>-43.013<\/td>\n<td>-18.370<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>300<\/td>\n<td>581.746<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>34.134<\/td>\n<td>-20.274<\/td>\n<td>16.539<\/td>\n<\/tr>\n<tr>\n<td>250<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>48.243<\/td>\n<td>6.148<\/td>\n<td>51.455<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>200<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>149.232<\/td>\n<td>64.645<\/td>\n<td>40.331<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr>\n<td>150<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>163.981<\/td>\n<td>91.507<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>100<\/td>\n<td>&#8211;<\/td>\n<td>306.667<\/td>\n<td>184.939<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr>\n<td>50<\/td>\n<td>&#8211;<\/td>\n<td>322.318<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>0<\/td>\n<td>623.017<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<\/table>\n<p>Using this table, you can easily figure out what to do in any turn play<br \/>\nsituation.  Consider these examples.<\/p>\n<ul>\n<li>With 300 points and 3 dice to roll, you should roll.<\/li>\n<li>With 300 points and 2 dice to roll, you should bank.<\/li>\n<li>With 300 points and 1 die to roll, you should roll.<\/li>\n<li>With an opening roll of (3, 3, 3, 5, 2, 6) you should take the 5 and roll five dice.<\/li>\n<li>With an opening roll of (1, 1, 1, 1, 4, 4), you should score it as three pair for 1500 and take a free roll.<\/li>\n<li>If you already have 500 points and then roll (1, 1, 1, 1, 4, 4), you should score it as a set of four 1s for 2000 and bank.<\/li>\n<\/ul>\n<p><a name=\"T1\"><\/a><\/p>\n<h3>Strategy T<sub>1<\/sub>: playing with one consecutive zilch<\/h3>\n<p>Table&nbsp;3 below gives E(s,&nbsp;n) for all s &le; 3200 for the case y&nbsp;=&nbsp;72.  This is<br \/>\nthe optimal strategy for turns of type T<sub>1<\/sub> (when you&#8217;re playing with<br \/>\none consecutive zilch).  The corrected expected points for the turn is:<br \/>\nE<sub>1<\/sub>&nbsp;=&nbsp;622.269.  The probability of zilching for the entire turn is<br \/>\nz<sub>1<\/sub>&nbsp;=&nbsp;.170988.<\/p>\n<div class=\"caption\">\n<span class=\"heading\">Table&nbsp;3.  E(s,n) for turn type T<sub>1<\/sub>.<\/span>\n<\/div>\n<table class=\"data\">\n<tr>\n<th style=\"background-color:#ccc\"><\/th>\n<th colspan=\"6\">n<\/th>\n<\/tr>\n<tr>\n<th>s<\/th>\n<th width=\"15%\">6<\/th>\n<th width=\"15%\">5<\/th>\n<th width=\"15%\">4<\/th>\n<th width=\"15%\">3<\/th>\n<th width=\"15%\">2<\/th>\n<th width=\"15%\">1<\/th>\n<\/tr>\n<tr class=\"datashaded\">\n<td>3200<\/td>\n<td>478.237<\/td>\n<td>-12.164<\/td>\n<td>-352.330<\/td>\n<td>-795.515<\/td>\n<td>-1351.085<\/td>\n<td>-1996.921<\/td>\n<\/tr>\n<tr>\n<td>3150<\/td>\n<td>478.237<\/td>\n<td>-8.306<\/td>\n<td>-344.460<\/td>\n<td>-781.626<\/td>\n<td>-1328.863<\/td>\n<td>-1963.588<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>3100<\/td>\n<td>478.237<\/td>\n<td>-4.448<\/td>\n<td>-336.589<\/td>\n<td>-767.737<\/td>\n<td>-1306.640<\/td>\n<td>-1930.254<\/td>\n<\/tr>\n<tr>\n<td>3050<\/td>\n<td>478.237<\/td>\n<td>-0.590<\/td>\n<td>-328.719<\/td>\n<td>-753.848<\/td>\n<td>-1284.418<\/td>\n<td>-1896.921<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>3000<\/td>\n<td>478.237<\/td>\n<td>3.268<\/td>\n<td>-320.848<\/td>\n<td>-739.959<\/td>\n<td>-1262.196<\/td>\n<td>-1863.588<\/td>\n<\/tr>\n<tr>\n<td>2950<\/td>\n<td>478.490<\/td>\n<td>7.126<\/td>\n<td>-312.978<\/td>\n<td>-726.070<\/td>\n<td>-1239.974<\/td>\n<td>-1830.254<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2900<\/td>\n<td>479.039<\/td>\n<td>10.984<\/td>\n<td>-305.108<\/td>\n<td>-712.181<\/td>\n<td>-1217.751<\/td>\n<td>-1796.879<\/td>\n<\/tr>\n<tr>\n<td>2850<\/td>\n<td>479.635<\/td>\n<td>14.842<\/td>\n<td>-297.237<\/td>\n<td>-698.292<\/td>\n<td>-1195.522<\/td>\n<td>-1763.412<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2800<\/td>\n<td>480.230<\/td>\n<td>18.700<\/td>\n<td>-289.367<\/td>\n<td>-684.403<\/td>\n<td>-1173.271<\/td>\n<td>-1729.888<\/td>\n<\/tr>\n<tr>\n<td>2750<\/td>\n<td>480.826<\/td>\n<td>22.558<\/td>\n<td>-281.497<\/td>\n<td>-670.510<\/td>\n<td>-1150.994<\/td>\n<td>-1696.356<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2700<\/td>\n<td>481.421<\/td>\n<td>26.416<\/td>\n<td>-273.625<\/td>\n<td>-656.607<\/td>\n<td>-1128.707<\/td>\n<td>-1662.824<\/td>\n<\/tr>\n<tr>\n<td>2650<\/td>\n<td>482.016<\/td>\n<td>30.275<\/td>\n<td>-265.751<\/td>\n<td>-642.699<\/td>\n<td>-1106.419<\/td>\n<td>-1629.292<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2600<\/td>\n<td>482.612<\/td>\n<td>34.134<\/td>\n<td>-257.874<\/td>\n<td>-628.788<\/td>\n<td>-1084.130<\/td>\n<td>-1595.760<\/td>\n<\/tr>\n<tr>\n<td>2550<\/td>\n<td>483.208<\/td>\n<td>37.995<\/td>\n<td>-249.995<\/td>\n<td>-614.876<\/td>\n<td>-1061.842<\/td>\n<td>-1562.229<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2500<\/td>\n<td>483.804<\/td>\n<td>41.858<\/td>\n<td>-242.113<\/td>\n<td>-600.962<\/td>\n<td>-1039.554<\/td>\n<td>-1528.697<\/td>\n<\/tr>\n<tr>\n<td>2450<\/td>\n<td>484.408<\/td>\n<td>45.722<\/td>\n<td>-234.230<\/td>\n<td>-587.047<\/td>\n<td>-1017.265<\/td>\n<td>-1495.165<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2400<\/td>\n<td>485.020<\/td>\n<td>49.588<\/td>\n<td>-226.345<\/td>\n<td>-573.131<\/td>\n<td>-994.977<\/td>\n<td>-1461.631<\/td>\n<\/tr>\n<tr>\n<td>2350<\/td>\n<td>485.634<\/td>\n<td>53.456<\/td>\n<td>-218.460<\/td>\n<td>-559.214<\/td>\n<td>-972.688<\/td>\n<td>-1428.095<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2300<\/td>\n<td>486.436<\/td>\n<td>57.324<\/td>\n<td>-210.572<\/td>\n<td>-545.295<\/td>\n<td>-950.399<\/td>\n<td>-1394.558<\/td>\n<\/tr>\n<tr>\n<td>2250<\/td>\n<td>487.662<\/td>\n<td>61.193<\/td>\n<td>-202.683<\/td>\n<td>-531.375<\/td>\n<td>-928.109<\/td>\n<td>-1360.988<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2200<\/td>\n<td>488.935<\/td>\n<td>65.064<\/td>\n<td>-194.792<\/td>\n<td>-517.456<\/td>\n<td>-905.813<\/td>\n<td>-1327.317<\/td>\n<\/tr>\n<tr>\n<td>2150<\/td>\n<td>490.210<\/td>\n<td>68.936<\/td>\n<td>-186.901<\/td>\n<td>-503.536<\/td>\n<td>-883.495<\/td>\n<td>-1293.567<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2100<\/td>\n<td>491.486<\/td>\n<td>72.808<\/td>\n<td>-179.010<\/td>\n<td>-489.612<\/td>\n<td>-861.147<\/td>\n<td>-1259.809<\/td>\n<\/tr>\n<tr>\n<td>2050<\/td>\n<td>492.764<\/td>\n<td>76.682<\/td>\n<td>-171.118<\/td>\n<td>-475.678<\/td>\n<td>-838.785<\/td>\n<td>-1226.051<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2000<\/td>\n<td>494.042<\/td>\n<td>80.555<\/td>\n<td>-163.224<\/td>\n<td>-461.737<\/td>\n<td>-816.421<\/td>\n<td>-1192.292<\/td>\n<\/tr>\n<tr>\n<td>1950<\/td>\n<td>495.321<\/td>\n<td>84.430<\/td>\n<td>-155.325<\/td>\n<td>-447.791<\/td>\n<td>-794.057<\/td>\n<td>-1158.532<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1900<\/td>\n<td>496.600<\/td>\n<td>88.307<\/td>\n<td>-147.422<\/td>\n<td>-433.843<\/td>\n<td>-771.693<\/td>\n<td>-1124.773<\/td>\n<\/tr>\n<tr>\n<td>1850<\/td>\n<td>497.882<\/td>\n<td>92.186<\/td>\n<td>-139.516<\/td>\n<td>-419.893<\/td>\n<td>-749.329<\/td>\n<td>-1091.013<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1800<\/td>\n<td>499.169<\/td>\n<td>96.067<\/td>\n<td>-131.608<\/td>\n<td>-405.942<\/td>\n<td>-726.964<\/td>\n<td>-1057.253<\/td>\n<\/tr>\n<tr>\n<td>1750<\/td>\n<td>500.468<\/td>\n<td>99.951<\/td>\n<td>-123.698<\/td>\n<td>-391.988<\/td>\n<td>-704.600<\/td>\n<td>-1023.492<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1700<\/td>\n<td>501.770<\/td>\n<td>103.837<\/td>\n<td>-115.788<\/td>\n<td>-378.034<\/td>\n<td>-682.235<\/td>\n<td>-989.727<\/td>\n<\/tr>\n<tr>\n<td>1650<\/td>\n<td>503.075<\/td>\n<td>107.723<\/td>\n<td>-107.874<\/td>\n<td>-364.077<\/td>\n<td>-659.870<\/td>\n<td>-955.960<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1600<\/td>\n<td>504.884<\/td>\n<td>111.611<\/td>\n<td>-99.959<\/td>\n<td>-350.120<\/td>\n<td>-637.503<\/td>\n<td>-922.192<\/td>\n<\/tr>\n<tr>\n<td>1550<\/td>\n<td>506.702<\/td>\n<td>115.501<\/td>\n<td>-92.042<\/td>\n<td>-336.163<\/td>\n<td>-615.137<\/td>\n<td>-888.340<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1500<\/td>\n<td>508.520<\/td>\n<td>119.393<\/td>\n<td>-84.125<\/td>\n<td>-322.206<\/td>\n<td>-592.755<\/td>\n<td>-854.402<\/td>\n<\/tr>\n<tr>\n<td>1450<\/td>\n<td>510.357<\/td>\n<td>123.285<\/td>\n<td>-76.207<\/td>\n<td>-308.248<\/td>\n<td>-570.346<\/td>\n<td>-820.463<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1400<\/td>\n<td>512.214<\/td>\n<td>127.178<\/td>\n<td>-68.289<\/td>\n<td>-294.281<\/td>\n<td>-547.922<\/td>\n<td>-786.520<\/td>\n<\/tr>\n<tr>\n<td>1350<\/td>\n<td>514.075<\/td>\n<td>131.071<\/td>\n<td>-60.370<\/td>\n<td>-280.306<\/td>\n<td>-525.497<\/td>\n<td>-752.572<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1300<\/td>\n<td>515.936<\/td>\n<td>134.965<\/td>\n<td>-52.446<\/td>\n<td>-266.328<\/td>\n<td>-503.071<\/td>\n<td>-718.619<\/td>\n<\/tr>\n<tr>\n<td>1250<\/td>\n<td>517.799<\/td>\n<td>138.861<\/td>\n<td>-44.519<\/td>\n<td>-252.348<\/td>\n<td>-480.643<\/td>\n<td>-684.665<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1200<\/td>\n<td>519.663<\/td>\n<td>142.758<\/td>\n<td>-36.590<\/td>\n<td>-238.365<\/td>\n<td>-458.214<\/td>\n<td>-650.711<\/td>\n<\/tr>\n<tr>\n<td>1150<\/td>\n<td>521.529<\/td>\n<td>146.658<\/td>\n<td>-28.658<\/td>\n<td>-224.381<\/td>\n<td>-435.785<\/td>\n<td>-616.756<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1100<\/td>\n<td>523.408<\/td>\n<td>150.559<\/td>\n<td>-20.724<\/td>\n<td>-210.394<\/td>\n<td>-413.356<\/td>\n<td>-582.801<\/td>\n<\/tr>\n<tr>\n<td>1050<\/td>\n<td>525.290<\/td>\n<td>154.463<\/td>\n<td>-12.789<\/td>\n<td>-196.408<\/td>\n<td>-390.926<\/td>\n<td>-548.844<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1000<\/td>\n<td>527.217<\/td>\n<td>158.367<\/td>\n<td>-4.853<\/td>\n<td>-182.418<\/td>\n<td>-368.496<\/td>\n<td>-514.884<\/td>\n<\/tr>\n<tr>\n<td>950<\/td>\n<td>529.405<\/td>\n<td>162.273<\/td>\n<td>3.086<\/td>\n<td>-168.429<\/td>\n<td>-346.066<\/td>\n<td>-480.915<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>900<\/td>\n<td>531.595<\/td>\n<td>166.585<\/td>\n<td>11.026<\/td>\n<td>-154.439<\/td>\n<td>-323.633<\/td>\n<td>-446.896<\/td>\n<\/tr>\n<tr>\n<td>850<\/td>\n<td>533.840<\/td>\n<td>171.940<\/td>\n<td>18.967<\/td>\n<td>-140.449<\/td>\n<td>-301.191<\/td>\n<td>-412.833<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>800<\/td>\n<td>536.398<\/td>\n<td>177.933<\/td>\n<td>26.908<\/td>\n<td>-126.458<\/td>\n<td>-278.733<\/td>\n<td>-378.761<\/td>\n<\/tr>\n<tr>\n<td>750<\/td>\n<td>539.486<\/td>\n<td>183.927<\/td>\n<td>34.850<\/td>\n<td>-112.461<\/td>\n<td>-256.266<\/td>\n<td>-344.627<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>700<\/td>\n<td>542.833<\/td>\n<td>189.921<\/td>\n<td>42.793<\/td>\n<td>-98.460<\/td>\n<td>-233.787<\/td>\n<td>-310.353<\/td>\n<\/tr>\n<tr>\n<td>650<\/td>\n<td>546.182<\/td>\n<td>195.917<\/td>\n<td>50.738<\/td>\n<td>-84.457<\/td>\n<td>-211.274<\/td>\n<td>-275.947<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>600<\/td>\n<td>549.531<\/td>\n<td>201.970<\/td>\n<td>58.685<\/td>\n<td>-70.445<\/td>\n<td>-188.717<\/td>\n<td>-241.498<\/td>\n<\/tr>\n<tr>\n<td>550<\/td>\n<td>552.913<\/td>\n<td>208.696<\/td>\n<td>66.637<\/td>\n<td>-56.417<\/td>\n<td>-166.130<\/td>\n<td>-207.048<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>500<\/td>\n<td>556.531<\/td>\n<td>216.537<\/td>\n<td>74.593<\/td>\n<td>-42.375<\/td>\n<td>-143.535<\/td>\n<td>-172.593<\/td>\n<\/tr>\n<tr>\n<td>450<\/td>\n<td>560.750<\/td>\n<td>224.384<\/td>\n<td>82.556<\/td>\n<td>-28.326<\/td>\n<td>-120.940<\/td>\n<td>-138.093<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>400<\/td>\n<td>565.457<\/td>\n<td>232.237<\/td>\n<td>90.525<\/td>\n<td>-14.273<\/td>\n<td>-98.336<\/td>\n<td>-103.453<\/td>\n<\/tr>\n<tr>\n<td>350<\/td>\n<td>570.171<\/td>\n<td>240.097<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>-75.702<\/td>\n<td>-68.632<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>300<\/td>\n<td>574.899<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>13.848<\/td>\n<td>-53.014<\/td>\n<td>-33.729<\/td>\n<\/tr>\n<tr>\n<td>250<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>27.930<\/td>\n<td>-30.282<\/td>\n<td>1.178<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>200<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>130.189<\/td>\n<td>35.303<\/td>\n<td>-7.274<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr>\n<td>150<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>141.074<\/td>\n<td>47.867<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>100<\/td>\n<td>&#8211;<\/td>\n<td>288.116<\/td>\n<td>151.530<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr>\n<td>50<\/td>\n<td>&#8211;<\/td>\n<td>298.518<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>0<\/td>\n<td>609.958<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<\/table>\n<p><a name=\"T2\"><\/a><\/p>\n<h3>Strategy T<sub>2<\/sub>: playing with two consecutive zilches<\/h3>\n<p>Table&nbsp;4 below gives E(s,&nbsp;n) for all s &le; 3200 for the case y&nbsp;=&nbsp;500.  This<br \/>\nis the optimal strategy for turns of type T<sub>2<\/sub> (when you&#8217;re playing<br \/>\nwith two consecutive zilches).  The expected points for the turn is:<br \/>\nE<sub>2<\/sub>&nbsp;=&nbsp;547.157.  The probability of zilching for the entire<br \/>\nturn is z<sub>2<\/sub>&nbsp;=&nbsp;.132148.<\/p>\n<div class=\"caption\">\n<span class=\"heading\">Table&nbsp;4.  E(s,n) for turn type T<sub>2<\/sub>.<\/span>\n<\/div>\n<table class=\"data\">\n<tr>\n<th style=\"background-color:#ccc\"><\/th>\n<th colspan=\"6\">n<\/th>\n<\/tr>\n<tr>\n<th>s<\/th>\n<th width=\"15%\">6<\/th>\n<th width=\"15%\">5<\/th>\n<th width=\"15%\">4<\/th>\n<th width=\"15%\">3<\/th>\n<th width=\"15%\">2<\/th>\n<th width=\"15%\">1<\/th>\n<\/tr>\n<tr class=\"datashaded\">\n<td>3200<\/td>\n<td>478.237<\/td>\n<td>-45.189<\/td>\n<td>-419.700<\/td>\n<td>-914.403<\/td>\n<td>-1541.307<\/td>\n<td>-2282.254<\/td>\n<\/tr>\n<tr>\n<td>3150<\/td>\n<td>478.237<\/td>\n<td>-41.331<\/td>\n<td>-411.830<\/td>\n<td>-900.515<\/td>\n<td>-1519.085<\/td>\n<td>-2248.921<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>3100<\/td>\n<td>478.237<\/td>\n<td>-37.472<\/td>\n<td>-403.960<\/td>\n<td>-886.626<\/td>\n<td>-1496.863<\/td>\n<td>-2215.588<\/td>\n<\/tr>\n<tr>\n<td>3050<\/td>\n<td>478.237<\/td>\n<td>-33.614<\/td>\n<td>-396.089<\/td>\n<td>-872.737<\/td>\n<td>-1474.640<\/td>\n<td>-2182.254<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>3000<\/td>\n<td>478.237<\/td>\n<td>-29.756<\/td>\n<td>-388.219<\/td>\n<td>-858.848<\/td>\n<td>-1452.418<\/td>\n<td>-2148.921<\/td>\n<\/tr>\n<tr>\n<td>2950<\/td>\n<td>478.237<\/td>\n<td>-25.898<\/td>\n<td>-380.348<\/td>\n<td>-844.959<\/td>\n<td>-1430.196<\/td>\n<td>-2115.588<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2900<\/td>\n<td>478.237<\/td>\n<td>-22.040<\/td>\n<td>-372.478<\/td>\n<td>-831.070<\/td>\n<td>-1407.974<\/td>\n<td>-2082.254<\/td>\n<\/tr>\n<tr>\n<td>2850<\/td>\n<td>478.237<\/td>\n<td>-18.182<\/td>\n<td>-364.608<\/td>\n<td>-817.181<\/td>\n<td>-1385.751<\/td>\n<td>-2048.921<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2800<\/td>\n<td>478.237<\/td>\n<td>-14.324<\/td>\n<td>-356.737<\/td>\n<td>-803.292<\/td>\n<td>-1363.529<\/td>\n<td>-2015.588<\/td>\n<\/tr>\n<tr>\n<td>2750<\/td>\n<td>478.237<\/td>\n<td>-10.466<\/td>\n<td>-348.867<\/td>\n<td>-789.403<\/td>\n<td>-1341.307<\/td>\n<td>-1982.254<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2700<\/td>\n<td>478.237<\/td>\n<td>-6.608<\/td>\n<td>-340.997<\/td>\n<td>-775.515<\/td>\n<td>-1319.085<\/td>\n<td>-1948.921<\/td>\n<\/tr>\n<tr>\n<td>2650<\/td>\n<td>478.237<\/td>\n<td>-2.750<\/td>\n<td>-333.126<\/td>\n<td>-761.626<\/td>\n<td>-1296.863<\/td>\n<td>-1915.588<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2600<\/td>\n<td>478.237<\/td>\n<td>1.108<\/td>\n<td>-325.256<\/td>\n<td>-747.737<\/td>\n<td>-1274.640<\/td>\n<td>-1882.254<\/td>\n<\/tr>\n<tr>\n<td>2550<\/td>\n<td>478.323<\/td>\n<td>4.966<\/td>\n<td>-317.386<\/td>\n<td>-733.848<\/td>\n<td>-1252.418<\/td>\n<td>-1848.921<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2500<\/td>\n<td>478.706<\/td>\n<td>8.824<\/td>\n<td>-309.515<\/td>\n<td>-719.959<\/td>\n<td>-1230.196<\/td>\n<td>-1815.573<\/td>\n<\/tr>\n<tr>\n<td>2450<\/td>\n<td>479.301<\/td>\n<td>12.682<\/td>\n<td>-301.645<\/td>\n<td>-706.070<\/td>\n<td>-1207.971<\/td>\n<td>-1782.162<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2400<\/td>\n<td>479.897<\/td>\n<td>16.540<\/td>\n<td>-293.774<\/td>\n<td>-692.181<\/td>\n<td>-1185.734<\/td>\n<td>-1748.665<\/td>\n<\/tr>\n<tr>\n<td>2350<\/td>\n<td>480.492<\/td>\n<td>20.398<\/td>\n<td>-285.904<\/td>\n<td>-678.291<\/td>\n<td>-1163.471<\/td>\n<td>-1715.134<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2300<\/td>\n<td>481.088<\/td>\n<td>24.256<\/td>\n<td>-278.033<\/td>\n<td>-664.394<\/td>\n<td>-1141.189<\/td>\n<td>-1681.602<\/td>\n<\/tr>\n<tr>\n<td>2250<\/td>\n<td>481.683<\/td>\n<td>28.114<\/td>\n<td>-270.161<\/td>\n<td>-650.488<\/td>\n<td>-1118.900<\/td>\n<td>-1648.070<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2200<\/td>\n<td>482.278<\/td>\n<td>31.973<\/td>\n<td>-262.286<\/td>\n<td>-636.578<\/td>\n<td>-1096.612<\/td>\n<td>-1614.538<\/td>\n<\/tr>\n<tr>\n<td>2150<\/td>\n<td>482.874<\/td>\n<td>35.833<\/td>\n<td>-254.407<\/td>\n<td>-622.667<\/td>\n<td>-1074.324<\/td>\n<td>-1581.006<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2100<\/td>\n<td>483.470<\/td>\n<td>39.694<\/td>\n<td>-246.527<\/td>\n<td>-608.754<\/td>\n<td>-1052.035<\/td>\n<td>-1547.475<\/td>\n<\/tr>\n<tr>\n<td>2050<\/td>\n<td>484.069<\/td>\n<td>43.558<\/td>\n<td>-238.645<\/td>\n<td>-594.840<\/td>\n<td>-1029.747<\/td>\n<td>-1513.943<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>2000<\/td>\n<td>484.677<\/td>\n<td>47.423<\/td>\n<td>-230.761<\/td>\n<td>-580.924<\/td>\n<td>-1007.458<\/td>\n<td>-1480.410<\/td>\n<\/tr>\n<tr>\n<td>1950<\/td>\n<td>485.290<\/td>\n<td>51.290<\/td>\n<td>-222.876<\/td>\n<td>-567.008<\/td>\n<td>-985.170<\/td>\n<td>-1446.876<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1900<\/td>\n<td>485.975<\/td>\n<td>55.157<\/td>\n<td>-214.989<\/td>\n<td>-553.089<\/td>\n<td>-962.881<\/td>\n<td>-1413.339<\/td>\n<\/tr>\n<tr>\n<td>1850<\/td>\n<td>486.949<\/td>\n<td>59.026<\/td>\n<td>-207.101<\/td>\n<td>-539.170<\/td>\n<td>-940.591<\/td>\n<td>-1379.789<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1800<\/td>\n<td>488.222<\/td>\n<td>62.896<\/td>\n<td>-199.211<\/td>\n<td>-525.251<\/td>\n<td>-918.299<\/td>\n<td>-1346.179<\/td>\n<\/tr>\n<tr>\n<td>1750<\/td>\n<td>489.496<\/td>\n<td>66.767<\/td>\n<td>-191.320<\/td>\n<td>-511.331<\/td>\n<td>-895.995<\/td>\n<td>-1312.472<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1700<\/td>\n<td>490.771<\/td>\n<td>70.640<\/td>\n<td>-183.429<\/td>\n<td>-497.410<\/td>\n<td>-873.664<\/td>\n<td>-1278.714<\/td>\n<\/tr>\n<tr>\n<td>1650<\/td>\n<td>492.048<\/td>\n<td>74.513<\/td>\n<td>-175.538<\/td>\n<td>-483.482<\/td>\n<td>-851.309<\/td>\n<td>-1244.955<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1600<\/td>\n<td>493.326<\/td>\n<td>78.386<\/td>\n<td>-167.645<\/td>\n<td>-469.545<\/td>\n<td>-828.945<\/td>\n<td>-1211.197<\/td>\n<\/tr>\n<tr>\n<td>1550<\/td>\n<td>494.604<\/td>\n<td>82.260<\/td>\n<td>-159.748<\/td>\n<td>-455.601<\/td>\n<td>-806.581<\/td>\n<td>-1177.438<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1500<\/td>\n<td>495.884<\/td>\n<td>86.136<\/td>\n<td>-151.848<\/td>\n<td>-441.655<\/td>\n<td>-784.217<\/td>\n<td>-1143.678<\/td>\n<\/tr>\n<tr>\n<td>1450<\/td>\n<td>497.164<\/td>\n<td>90.013<\/td>\n<td>-143.944<\/td>\n<td>-427.706<\/td>\n<td>-761.853<\/td>\n<td>-1109.919<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1400<\/td>\n<td>498.448<\/td>\n<td>93.894<\/td>\n<td>-136.037<\/td>\n<td>-413.755<\/td>\n<td>-739.488<\/td>\n<td>-1076.159<\/td>\n<\/tr>\n<tr>\n<td>1350<\/td>\n<td>499.740<\/td>\n<td>97.776<\/td>\n<td>-128.128<\/td>\n<td>-399.802<\/td>\n<td>-717.124<\/td>\n<td>-1042.398<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1300<\/td>\n<td>501.041<\/td>\n<td>101.661<\/td>\n<td>-120.218<\/td>\n<td>-385.848<\/td>\n<td>-694.759<\/td>\n<td>-1008.635<\/td>\n<\/tr>\n<tr>\n<td>1250<\/td>\n<td>502.344<\/td>\n<td>105.547<\/td>\n<td>-112.306<\/td>\n<td>-371.893<\/td>\n<td>-672.394<\/td>\n<td>-974.870<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1200<\/td>\n<td>503.867<\/td>\n<td>109.434<\/td>\n<td>-104.392<\/td>\n<td>-357.936<\/td>\n<td>-650.029<\/td>\n<td>-941.102<\/td>\n<\/tr>\n<tr>\n<td>1150<\/td>\n<td>505.684<\/td>\n<td>113.323<\/td>\n<td>-96.476<\/td>\n<td>-343.979<\/td>\n<td>-627.662<\/td>\n<td>-907.298<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1100<\/td>\n<td>507.502<\/td>\n<td>117.213<\/td>\n<td>-88.558<\/td>\n<td>-330.022<\/td>\n<td>-605.289<\/td>\n<td>-873.408<\/td>\n<\/tr>\n<tr>\n<td>1050<\/td>\n<td>509.327<\/td>\n<td>121.105<\/td>\n<td>-80.641<\/td>\n<td>-316.064<\/td>\n<td>-582.895<\/td>\n<td>-839.469<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>1000<\/td>\n<td>511.172<\/td>\n<td>124.998<\/td>\n<td>-72.723<\/td>\n<td>-302.102<\/td>\n<td>-560.480<\/td>\n<td>-805.529<\/td>\n<\/tr>\n<tr>\n<td>950<\/td>\n<td>513.033<\/td>\n<td>128.891<\/td>\n<td>-64.805<\/td>\n<td>-288.132<\/td>\n<td>-538.055<\/td>\n<td>-771.583<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>900<\/td>\n<td>514.894<\/td>\n<td>132.784<\/td>\n<td>-56.883<\/td>\n<td>-274.156<\/td>\n<td>-515.630<\/td>\n<td>-737.633<\/td>\n<\/tr>\n<tr>\n<td>850<\/td>\n<td>516.756<\/td>\n<td>136.679<\/td>\n<td>-48.958<\/td>\n<td>-260.177<\/td>\n<td>-493.203<\/td>\n<td>-703.679<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>800<\/td>\n<td>518.619<\/td>\n<td>140.575<\/td>\n<td>-41.030<\/td>\n<td>-246.196<\/td>\n<td>-470.774<\/td>\n<td>-669.725<\/td>\n<\/tr>\n<tr>\n<td>750<\/td>\n<td>520.484<\/td>\n<td>144.474<\/td>\n<td>-33.100<\/td>\n<td>-232.212<\/td>\n<td>-448.345<\/td>\n<td>-635.771<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>700<\/td>\n<td>522.356<\/td>\n<td>148.374<\/td>\n<td>-25.167<\/td>\n<td>-218.227<\/td>\n<td>-425.916<\/td>\n<td>-601.816<\/td>\n<\/tr>\n<tr>\n<td>650<\/td>\n<td>524.236<\/td>\n<td>152.277<\/td>\n<td>-17.233<\/td>\n<td>-204.240<\/td>\n<td>-403.487<\/td>\n<td>-567.860<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>600<\/td>\n<td>526.119<\/td>\n<td>156.180<\/td>\n<td>-9.297<\/td>\n<td>-190.252<\/td>\n<td>-381.057<\/td>\n<td>-533.901<\/td>\n<\/tr>\n<tr>\n<td>550<\/td>\n<td>528.180<\/td>\n<td>160.085<\/td>\n<td>-1.360<\/td>\n<td>-176.263<\/td>\n<td>-358.627<\/td>\n<td>-499.941<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>500<\/td>\n<td>530.368<\/td>\n<td>163.992<\/td>\n<td>6.579<\/td>\n<td>-162.273<\/td>\n<td>-336.196<\/td>\n<td>-465.950<\/td>\n<\/tr>\n<tr>\n<td>450<\/td>\n<td>532.560<\/td>\n<td>168.763<\/td>\n<td>14.520<\/td>\n<td>-148.283<\/td>\n<td>-313.760<\/td>\n<td>-431.909<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>400<\/td>\n<td>534.870<\/td>\n<td>174.577<\/td>\n<td>22.461<\/td>\n<td>-134.293<\/td>\n<td>-291.310<\/td>\n<td>-397.845<\/td>\n<\/tr>\n<tr>\n<td>350<\/td>\n<td>537.684<\/td>\n<td>180.570<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>-268.848<\/td>\n<td>-363.762<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>300<\/td>\n<td>540.959<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>-106.301<\/td>\n<td>-246.379<\/td>\n<td>-329.574<\/td>\n<\/tr>\n<tr>\n<td>250<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>-92.299<\/td>\n<td>-223.889<\/td>\n<td>-295.226<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>200<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>37.142<\/td>\n<td>-128.047<\/td>\n<td>-266.961<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr>\n<td>150<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>8.190<\/td>\n<td>-189.755<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>100<\/td>\n<td>&#8211;<\/td>\n<td>196.017<\/td>\n<td>-32.853<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr>\n<td>50<\/td>\n<td>&#8211;<\/td>\n<td>167.775<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr class=\"datashaded\">\n<td>0<\/td>\n<td>547.157<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<\/table>\n<p>Comparing Table&nbsp;4 with Table&nbsp;2 you can see that playing with two<br \/>\nconsecutive zilches is almost identical to playing without any consecutive<br \/>\nzilches while pretending you have 500 more points for the turn than you really<br \/>\ndo.  To see this compare the 500 point line in Table&nbsp;4 with the 1000 point<br \/>\nline in the Table&nbsp;2.  They are identical.  This remains true until you get<br \/>\ndown to point values below 300 at which time the 300 point minimum bank rule<br \/>\nforces you to roll even though rolling gives a negative expected change in<br \/>\nyour score.<\/p>\n<p><a name=\"software\"><\/a><\/p>\n<h2><span class=\"h2\">Software<\/span><\/h2>\n<p>The software I wrote to find optimized Zilch strategies is 718 lines of<br \/>\njava code (or 322 lines comments stripped).  Please observe the GNU public<br \/>\nlicense copyright protection or I may have to introduce you to my friend<br \/>\nGuido. You can download with either zip or tgz compression as convenient:<\/p>\n<p><span style=\"font-weight:bold\">Downloads:<\/span> <a href=\"\/downloads\/zilch.zip\">zilch.zip<\/a> OR <a href=\"\/downloads\/zilch.zip\">zilch.tgz<\/a><\/p>\n<p>The compile command is simply:<\/p>\n<p><code style=\"margin-left:30px\">javac Zilch.java<\/code><\/p>\n<p>Then to run it type:<\/p>\n<p><code style=\"margin-left:30px\">java Zilch<\/code><\/p>\n<p>You can optionally add a zilch penalty to the command line.  For example,<br \/>\nto run the program with y&nbsp;=&nbsp;500 type:<\/p>\n<p><code style=\"margin-left:30px\">java Zilch 500<\/code><\/p>\n<p>To find the best strategy for variations of the game that use<br \/>\ndifferent scoring rules, just change the scoring constants at the top of<br \/>\nthe file.  If you set a score to zero, then that score combination is<br \/>\neffectively eliminated from the game and is instead treated as a zilch.<br \/>\nSo if in your Farkle variant, the six-die <i>nothing<\/i> roll is just<br \/>\na zilch, you need only set NOTHING_SCORE = 0.  The software will then<br \/>\ninterpret this as a zilching roll.<\/p>\n<p>E<sub>BIG6<\/sub> is calculated for you.  If you set the NOTHING_SCORE to 0,<br \/>\n(giving you a non-zero chance of zilching on a 6 die roll) then<br \/>\nE<sub>BIG6<\/sub> will be correctly initialized to 0.  There&#8217;s a<br \/>\nchicken-and-egg problem associated with the calculation of E<sub>BIG6<\/sub><br \/>\nwhich required a bit of finger work to resolve reliably in the face of various<br \/>\npossible scoring changes.  Check out the comments for method initEBIG6 if<br \/>\nyou&#8217;re interested.<\/p>\n<p>The smallest valid value for S<sub>BIG<\/sub> is also determined through a<br \/>\nbinary search, so you need not worry about changing that for different scoring<br \/>\noptions.<\/p>\n<p>On my 10 year old home computer, the strategy for Zilch is determined in<br \/>\nabout 7 seconds.  Farkle strategies take about 30 seconds.  (Farkle is much<br \/>\nslower because S<sub>BIG<\/sub> has to be set big enough that the<br \/>\nchance of a 6 die farkle out-weighs the potential gains of a 6 die roll.)  No<br \/>\ndoubt you could solve these same problems in a tiny fraction of a second<br \/>\nwith appropriate optimizations, but I personally don&#8217;t have a need for<br \/>\nbetter performance.<\/p>\n<p><a name=\"conclusions\"><\/a><\/p>\n<h2>Conclusions<\/h2>\n<p>This was a fun problem.  The trick is to work the problem backwards:<br \/>\nfinding the expected scores for high point states first, and then working your<br \/>\nway back down to lower and lower scores until finally you get the expected<br \/>\nscore from the starting state.  Everything else is just details (which hopefully<br \/>\nI&#8217;ve gotten correct).<\/p>\n<p>One thing I found surprising about the results is just how incredibly<br \/>\ninsensitive the corrected expected turn score is to the zilch penalty.<br \/>\nThe optimal strategy for the case of an infinite zilch penalty drops the<br \/>\nprobability of zilching from .193326 down to .126959 (the minimum zilch<br \/>\nprobability you can achieve for a turn).  Playing that same strategy<br \/>\non a turn where the zilch penalty is actually zero drops your expected<br \/>\nscore from 623.017 down to 605.851 &mdash; it only costs you 17<br \/>\npoints per turn!  That&#8217;s less than 300 points over the course of a typical<br \/>\ngame, and that&#8217;s nothing in a game of Zilch.  I think this is true because<br \/>\nalmost all the big points in Zilch come from 6 die rolls where there&#8217;s no<br \/>\nchance to zilch.  So, playing to reach 300 points as reliably as you<br \/>\ncan and then banking as soon as you face a roll of less than six dice<br \/>\nreduces your expected scores very little compared to playing for<br \/>\nmaximum expected points.  I found this very surprising and somehow<br \/>\nunsatisfying.<\/p>\n<p>I&#8217;d be pleased to know if you found this document comprehensible;<br \/>\nor if you found any errors in the analysis or the software.  Leave a comment<br \/>\nor send me an email.  If you&#8217;re lucky, you might even meet me masquerading<br \/>\nas <i>pips<\/i> in a game of<br \/>\n<a href=\"http:\/\/zilch.playr.co.uk\">Zilch<\/a>. Just don&#8217;t expect to win.<\/p>\n<p><a name=\"references\"><\/a><\/p>\n<h2><span class=\"h2\">References<\/span><\/h2>\n<ol>\n<li><a name=\"R1\"><\/a><a href=\"http:\/\/en.wikipedia.org\/wiki\/Farkle\">FARKLE<\/a>, Wikipedia.<\/li>\n<li><a name=\"R2\"><\/a><a href=\"http:\/\/notaboutapples.wordpress.com\/2009\/07\/27\/multinomial-coefficients-and-farkle\/\">Multinomial Coefficients and Farkle<\/a>, Cap Khoury, Jul. 2009.<\/li>\n<li><a name=\"R3\"><\/a><a href=\"http:\/\/graciesdad.wordpress.com\/2009\/08\/30\/farkle-odds\/\">Farkle Odds<\/a>, Gregory Graham, August 2009.<\/li>\n<li><a name=\"R4\"><\/a><a href=\"http:\/\/viviomancy.blogspot.com\/2008\/11\/study-of-game-zilch-part-1.html\">Study of the game Zilch part 1<\/a>, Leadhyena Inrandomtan, November 2008.<\/li>\n<li><a name=\"R5\"><\/a><a href=\"http:\/\/notaboutapples.wordpress.com\/2009\/08\/22\/farkle-expectation-and-knowing-what-you-want\/\">FARKLE, Expectation, and Knowing What You Want<\/a>, Cap Khoury, August 2009.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>Image by Thunderchild7 Zilch is a fun little dice game codified into an online game by Gaby Vanhegan that can be played at http:\/\/playr.co.uk\/. Zilch is actually a variation of the game Farkle which goes by several other names including &hellip; <a href=\"https:\/\/www.mattbusche.org\/blog\/article\/zilch\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/www.mattbusche.org\/blog\/wp-json\/wp\/v2\/posts\/15"}],"collection":[{"href":"https:\/\/www.mattbusche.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.mattbusche.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.mattbusche.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mattbusche.org\/blog\/wp-json\/wp\/v2\/comments?post=15"}],"version-history":[{"count":2,"href":"https:\/\/www.mattbusche.org\/blog\/wp-json\/wp\/v2\/posts\/15\/revisions"}],"predecessor-version":[{"id":17,"href":"https:\/\/www.mattbusche.org\/blog\/wp-json\/wp\/v2\/posts\/15\/revisions\/17"}],"wp:attachment":[{"href":"https:\/\/www.mattbusche.org\/blog\/wp-json\/wp\/v2\/media?parent=15"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.mattbusche.org\/blog\/wp-json\/wp\/v2\/categories?post=15"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.mattbusche.org\/blog\/wp-json\/wp\/v2\/tags?post=15"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}