re eck vs rickey was re rickey s whining again in article blue cis pitt edu genetic pitt edu david m tate writes i ve read all of the followups to this but i thought i d go back to the original article to make specific comments about the method jao megatest com john oswalt said he has obtained the play by play records in computer readable form for every major league baseball game for the past several years he devised an algorithm which i call sum over situations and wrote a computer program to calculate every major league players contribution using it it works like this look at every situation in every game in a baseball season a situation is determined by inning score where the baserunners are and how many outs there are for each situation count how many times the team eventually won the game that the situation occured in and divide by the number of times the situation came up to come up with a value for that situation this was first done by george lindsey in the late s early s and reported in article an investigation of strategies in baseball author george r lindsey journal operations research issue volume july august pp later pete palmer did the same thing using simulated seasons to generate a larger set of data to avoid the kind of small sample anomalies that other people have worried about he reported this in the hidden game of baseball with john thorn gary skoog modified the method a bit and did some work on what he called a value added measure based on these situational values his were based directly on marginal runs though not on win probabilities these results as applied to the season were reported in one of the bill james baseball abstract books help me out here somebody for example a situation might be inning score runner on second and no outs there were regular season major league games last year with the rockies and marlins there will be more this year say this situation came up in of those and the team ahead won of them then the value of this situation is description of method look at change in win probability based on the at bat plus any baserunning and credit debit the player by that amount each time he gets a plate appearance now for each player sum up all his at bat and base running values for the season to obtain an overall value for that player obviously the sum of all players values for each game and for the season as a whole will be that s only because you always credit x to the batter and x to the pitcher there s no validation involved ok there s a very big problem here that nobody has yet commented on you re adding probabilities and probabilities don t add runs you can add the total team runs breaks down into how many runs joe contributed plus how many runs fred contributed etc but probabilities don t work that way if bob increases his team s chance of winning by in each of pas that does not mean that bob increased his team s chance of winning by in fact it doesn t mean anything because the units are screwy i agree and disagree john is saying that the batters efforts will result in more wins then losses while you are probably correct that does not mean more wins then losses it means something i would rather have a player who increased my teams chances of winning by in each of pas then i would a player who increased my chances of winning by in each of pas thus there appears to me to be an obvious positive association between john s statistic and winning games thus before you disregard this stat it appears to me that further study must go into what sort of relationship there is consider an example bob hits a out solo hr in the bottom of the first about on your scale he does the same thing again in the fourth with the score tied for another and again in the seventh with the score tied for another and finally in the ninth to win the game by a score of for a value of bob hit solo hr in plate appearances and was credited by your method with but what does that mean was bob responsible for the win certainly not the defense is always responsible if you include pitching in that and bob wasn t pitching in fact bob was only of the offense which is a lot but not even close to furthermore what about the other team runs say they all came on solo hr by fred then fred was hitting hr to tie up the game which are just as valuable as hr to take the lead see lindsey and fred will himself have accrued a good rating or so so fred and bob combined have amassed of a win in one game there s clearly a problem here the only problem here is an insistance that these number mean exactly how many wins the team has first we are using averages over many seasons and applying them to one game second remember some players performance take away from the chance of you winning that is a player who gets an out gets a negative probability in most cases thus i m not sure in any given game when you add up all the numbers for a team who won that they will add up to in that game sometimes they will add up to more then one sometime less than one also the pitchers bad performances giving up runs may have given them a large negative percentage for that game also any batter that pulled an night would give large negatives greg thinking about the right things but his intuition is off the mark closers are enormously important the total number of runs value is outweighed by when they come or are prevented from comming the doubling which greg allows is not enough in another article i proposed a test of this we can predict a team s won lost record quite accurately by looking at how many runs total they score and allow without regard to when those runs score in the game if late runs are really more important than early runs then looking only at late runs should lead to a better predictor right no but really only because you have a smaller sample size i would think however that the number of runs you score in the first inning would be just as good as a prediction as how many runs you score in the last inning and realize something else a closer usually comes in in a close situation not a blow out it is hard to argue that any runs that a closer gives up in a game have equal importance to those given up in the first inning look a closer giving up runs often means a team will lose many games on the other hand a starter who gives up runs often still leaves his team a chance to win the offence has many more outs to do something about but i am not saying all late inning situations are equally important either if i am down runs in the ninth it really does not matter how many runs my pitcher gives up in the ninth here s another thought experiment apply this method to basketball what you find is that points scored in the first half of the game have almost exactly no value because no lead is safe with an entire half yet to play furthermore the sub in off the bench who sinks the winning free throws with no time on the clock gets a for the game while the star forward who scored points in the first half before spraining his ankle gets a zero does this make sense no but why would you assume that the teams probability of winning would be before the possesion in which the free throws were made look if you are down point with seconds left there is a fairly high probability that you will win the game if you are in possesion of the ball and do not forget that somebody elses missed shots turnovers fouls bad defense etc caused a negative chance that the team would win from reading all of the discussion on this statistic i feel that those who critisize it to a certain extent are doing so out of an agenda at first look this statistic valadates clutchness but it really does not cluthness revolves around the idea that certain players in crucial situation elevate their performance and others performance goes down i ve never seen convincing proof that this really happens so if you assume there is no clutchness then that means that except for a lot of noice this statistic has a positive association to player performance there is a way to get rid of the noice if you do not believe in clutchness certainly we could find out what the average value of a home run is for example we may find for instance that a home run increases your chance of winning by on average while a strikeout decreases your chance of winning by i bet if this were done we would find that this statistic was just as good as other statistics we have for predicting wins and losses how do we evaluate relief pitchers say john and sam have the exact same pitching statistics runs earned runs k s bb s etc both had exceptional numbers john however only pitched in closer situations while sam was a mop up man who was more valuble to their team probably john who was the better pitcher they were probably about the same brian smith
