Under The Knife: All's... (09/21)
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September 21, 2006 Schrodinger's BatOn Scorers and Scoring
"I shouldn't get so mad when I think there's been a scoring mistake, but I do. You just want it to be fair to everybody involved, and I understand that's hard. But you can't forget that players in the major leagues should be expected to make major-league-caliber plays." --Hall of Famer turned announcer Tom Seaver On some days official scorers have a tough job. I witnessed one of them from the press box in May of 2004, at a Royals/Twins game at Kauffman Stadium. In the bottom of the fifth, the Royals had loaded the bases with one out. Desi Relaford was perched on third, Angel Berroa on second and Carlos Beltran on first. What came next was a series of events that you'll likely never see again. The batter is Mike Sweeney, and he lofts a short pop-up behind first base. First baseman Doug Mientkiewicz, second baseman Michael Cuddyer and right fielder Jacque Jones all converge on the ball while first-base umpire Jeff Kellogg signals an infield fly. With Mientkiewicz's back turned toward the infield, the ball hits his glove and falls to the ground as he and Cuddyer brush against one another. Kellogg signals that the batter is out. Meanwhile, Beltran has left first and gone halfway to second, and seeing the ball drop, continues to second. However, Berroa hasn't moved from second, so both Beltran and Berroa are now standing within a couple feet of the base. Relaford speeds toward home from third as soon as the ball hits the ground. Back in the outfield Mientkiewicz picks up the ball, whirls and throws it in the general direction of home plate, apparently in an effort to nab Relaford. However, the throw hits Sweeney square in the back as he stands near first base watching the action. Sweeney hits the ground in pain ("I thought I got shot" he said later) as the ball slowly rolls in the direction of the Royals dugout. By this time, Berroa is madly waving Beltran to get back to first, and convinced by Berroa's theatrics, Beltran indeed starts heading that way. Catcher Henry Blanco retrieves the ball by the Royals dugout and rifles it to first, where right fielder Jones catches the ball and just beats a sliding Beltran, tagging him and touching the base for the second out of the play, and the third of the inning. The home-plate umpire signals the press box to indicate that Relaford's run counts. The Twins, slightly confused, trot off the field. Needless to say all of this caused a considerable amount of consternation in the press box for both the scorer and the media, as both the former and the latter scrambled to consult their rule books, and then offered several conflicting opinions as to whether Sweeney should be credited with a sacrifice fly and/or a run batted in, whether Mientkiewicz should be charged with an error, whether the Twins get credit for a double play, whether the run is unearned, and whether Beltran had to retreat to first. In the end, after multiple changed rulings and mediation by the Elias Sports Bureau, the answer to the above questions were no and no on Sweeney's sac fly or RBI (under rule 10.09), yes on Minky's error (the error allowed the run to score), no on the double play (there was a "misplay" involved), yes as to the run being earned (since the run scored on the play with the third out), and no on Beltran's having to retreat to first (he was at liberty to advance "the same as on any fly ball"). While there wasn't a tremendous amount of room for interpretation here, few would argue that the play wasn't difficult to assess and render judgment on. I got to thinking about this play in the wake of an interesting question in last week's chat that went as follows:
Dills (Chicago): How can we account for the differences in local "official" scorers in regards to defensive rankings? Too often, an error in, say, St Louis on a ball hit by a Padre would be a HIT in San Diego or vice versa. How can this possibly be accounted for? The E vs. HIT scoring will always be a subjective decision made in many cases by fairly biased scorers. I'll admit that at first I took issue with the assumption the part of the questioner that scorers were inherently biased. In my experience, the scorers I've worked with have acted professionally and strive to do the best job they possibly can. But of course the general perception among fans and the media alike remains, and although scorers don't have as much influence as they do in at least one hilarious spoof, both players and coaches often get worked up when decisions don't go their way. This question, then, spurred me to thinking how one could measure scorer bias, if indeed it exists. So this week, we'll ruminate a bit on that topic, and hopefully dispel any concerns that all I would write about this year was baserunning. Bias, or Just Home Cookin'? Over the past few years the performance-analysis community has made great strides in evaluating the contribution that fielders make. Augmenting simple counting statistics like putouts, assists and errors with considerations for opportunities has revolutionized the way in which we can evaluate the differences between a Derek Jeter and an Adam Everett. Be that as it may, controversies over errors persist. Too often, the mainstream media uses errors as the sole basis by which fielders are judged. Since that is still the unhappy case (barring the completion of the Kuhnian revolution in baseball) the topic of bias and the assignment of errors by official scorers also remains problematic. As many readers know, the official scorer for each game is a local person, often a retired sportswriter or sports information director from a nearby college, whose duties are defined in the last section (10.00) of the official rule book. What you may not know, and what was shared in a very informative article by Nationals scorer and SABR member David Vincent, is that up until 1980 the position was held by a newspaper writer. In a move to make the position less susceptible to conflicts of interest MLB began hiring independent contractors. That move has seemingly done little to quash the oft-heard complaints of scorer bias. These fall into basically two categories revolving around the notion that, being from the home team's metropolitan area, the scorer will inevitably make rulings and interpretations that benefit the home team. As a first pass we can define those categories as follows:
It should be noted that in the case of VTH, one might speculate that there is also a mitigating bias in play where official scorers may shy away from crediting home-team pitchers with earned runs, and therefore in some cases award the home-team fielder with an error. One might assume, however, that giving errors to the home team would have the greater resonance because of its immediate consequence--after all, earned runs aren't always counted immediately, so the potential exists to get out of the inning without giving up any earned runs in cases where a close play went in favor of giving the opponent a hit. Keep in mind though that it also complicates things when you consider that the home team probably should field better in the park with which they are the most familiar rather than on the road, and so would naturally commit fewer errors, thereby blurring any evidence of VTH, even if it exists. You'll notice that these two categories put us in the unfortunate position of not being able to easily quantify bias. In the case of HTH, we'll see more hits for the home team, and in the case of VTH we'll see more for the visitors. In other words, ceteris paribus, the two may cancel each other out by suppressing errors across the board, making it difficult to detect bias. The consequence is that if both HTH and VTH biases exist, then in effect what we actually have is a bias against pitchers, and in favor of fielders and hitters. In my opinion, that is often the situation. Many are the times when I'll assume a play will be ruled an error (invoking the "ordinary effort" clause of rule 10.13 in my mind's eye while channeling Mr. Seaver), only to see the hit designation flash on the scoreboard. Announcers and team personnel also invoke a form of this argument when, as I witnessed recently, a member of a team's public relations department pleaded his case to the official scorer by repeatedly citing the phrase "but this is supposed to be the Major Leagues!" But still, we'd like to see what--if anything--the actual data tell us. To look at this question I examined the number of errors credited to the home and visiting team for each team and season from 2000 through 2006 (through games through September 15th of this season). In an effort to detect HTH and VTH I calculated the number of errors per game credited to each team at home and on the road and converted them into percentages. (It's an imperfect method, I know, because the number of innings is not the same for both teams.) For example, to try to detect VTH, I found that the Los Angeles Angels of Anaheim at home were charged with 9% more errors than on the road, while visitors in Angels games were charged with 14% fewer errors than when in their own home parks--possibly reflecting HTH. Overall, either because VTH is stronger than HTH or the fact that home teams simply play better defense in their own parks, or perhaps a combination of both, teams were charged with 3% fewer errors at home over the seven season sample. This difference would be larger if we had used innings rather than games to calculate our rate, since visiting teams play fewer innings in the field. From a team perspective then, here are the 31 teams (Montreal is included for 2000-2004) ordered by our VTH column.
2000-2006 Error Percentages Team VTH HTH CHA -22% 0% FLO -20% -4% WAS -16% 13% MIN -15% 0% PHI -13% -15% CIN -12% -5% SEA -10% -5% ARI -10% -7% OAK -9% 7% KCA -9% 1% DET -5% 10% CLE -5% 22% SFN -5% 4% MON -5% 1% TOR -5% 12% TBA -4% 10% NYA -2% 8% BAL -2% -3% CHN 1% 1% TEX 2% 1% COL 2% 27% ATL 3% 12% SLN 3% -3% MIL 3% 11% PIT 4% 9% HOU 5% -4% SDN 6% -17% LAN 7% -3% ANA 9% -14% BOS 9% 14% NYN 18% -2% To reiterate, what this table records is that the White Sox were charged with 22% fewer errors at home than on the road, while their opponents were charged with errors at the same rate both in Chicago and in their home parks when playing the Sox. This could be interpreted as indicating that there is some VTH bias in play. In fact, the Sox were the only team where the percentage of errors at home was negative for all seven seasons. On the other hand, the Mets were charged with 18% more errors at home, while their opponents were charged with 2% fewer when playing in New York. In terms of detecting VTH, had we reordered the above list we'd find that Padres opponents were charged with 17% fewer errors in San Diego than when playing in their own parks. Obviously, we're not dealing with a huge sample size, and complicating factors such as scorer turnover, scorers sharing responsibilities and home park influences all conspire to skew the numbers, making this effort somewhat dubious. To give you a feel for the number of scorers and an inkling as to their differences (I'm making no value judgments here about individual scorers because of the variability in the data and team defensive quality which this analysis doesn't account for), the following table lists the scorers who have worked games in 2005 and 2006 for each team, along with a simple calculation of errors per game for both home and visitors:
Scorer Team G HE VE H E/G V E/G Ed Munson ANA 148 102 101 0.69 0.68 Mel Franks ANA 7 3 1 0.43 0.14 -------------------------------------------------------------------------- Rodney Johnson ARI 72 40 40 0.56 0.56 Gary Rausch ARI 69 30 46 0.43 0.67 Tyler Barnes ARI 15 15 6 1.00 0.40 -------------------------------------------------------------------------- Mark Frederickson ATL 77 34 52 0.44 0.68 Mike Stamus ATL 75 48 49 0.64 0.65 Tony Schiavone ATL 1 0 0 0.00 0.00 Paul Newberry ATL 1 1 0 1.00 0.00 -------------------------------------------------------------------------- Jim Henneman BAL 118 71 72 0.60 0.61 Mark Jacobson BAL 40 20 26 0.50 0.65 -------------------------------------------------------------------------- Charlie Scoggins BOS 60 27 43 0.45 0.72 Mike Shalin BOS 41 22 24 0.54 0.59 Joe Giuliotti BOS 35 15 28 0.43 0.80 Ed Carpenter BOS 13 6 8 0.46 0.62 Bob Ellis BOS 4 4 5 1.00 1.25 Tony Massarotti BOS 1 1 2 1.00 2.00 -------------------------------------------------------------------------- Bob Rosenberg CHA 100 40 71 0.40 0.71 Don Friske CHA 39 19 18 0.49 0.46 Scott Reed CHA 16 12 8 0.75 0.50 -------------------------------------------------------------------------- Don Friske CHN 71 56 41 0.79 0.58 Bob Rosenberg CHN 57 42 41 0.74 0.72 Allan Spear CHN 27 12 17 0.44 0.63 -------------------------------------------------------------------------- Glenn Sample CIN 123 75 61 0.61 0.50 Ronald Roth CIN 36 23 20 0.64 0.56 -------------------------------------------------------------------------- Chad Broski CLE 47 27 35 0.57 0.74 Chuck Murr CLE 47 46 29 0.98 0.62 Hank Kozloski CLE 45 25 23 0.56 0.51 Bob Maver CLE 8 7 8 0.88 1.00 Bob Price CLE 6 3 2 0.50 0.33 -------------------------------------------------------------------------- Dave Einspahr COL 108 63 86 0.58 0.80 Dave Plati COL 42 30 35 0.71 0.83 Dave Moore COL 2 2 2 1.00 1.00 -------------------------------------------------------------------------- Chuck Klonke DET 75 46 56 0.61 0.75 Steve Lysogorski DET 72 49 48 0.68 0.67 Ron Kleinfelter DET 7 3 4 0.43 0.57 -------------------------------------------------------------------------- Ron Jernick FLO 135 89 84 0.66 0.62 Doug Pett FLO 21 9 18 0.43 0.86 -------------------------------------------------------------------------- Trey Wilkinson HOU 43 31 18 0.72 0.42 Dave Matheson HOU 39 18 24 0.46 0.62 Ivy McLemore HOU 36 19 22 0.53 0.61 Rick Blount HOU 35 22 20 0.63 0.57 -------------------------------------------------------------------------- Del Black KCA 92 65 66 0.71 0.72 Will Rudd KCA 52 34 37 0.65 0.71 Alan Eskew KCA 11 8 6 0.73 0.55 -------------------------------------------------------------------------- Don Hartack LAN 81 51 52 0.63 0.64 Ed Munson LAN 72 50 49 0.69 0.68 -------------------------------------------------------------------------- Tim O'Driscoll MIL 125 96 78 0.77 0.62 Wayne Franke MIL 30 22 17 0.73 0.57 -------------------------------------------------------------------------- Tom Mee MIN 147 81 105 0.55 0.71 Barry Fritz MIN 4 1 3 0.25 0.75 Gregg Wong MIN 4 5 0 1.25 0.00 -------------------------------------------------------------------------- Howie Karpin NYA 68 49 52 0.72 0.76 Bill Shannon NYA 58 36 36 0.62 0.62 Jordan Sprechman NYA 22 11 15 0.50 0.68 Billy Altman NYA 2 1 0 0.50 0.00 Dave Freeman NYA 2 1 0 0.50 0.00 -------------------------------------------------------------------------- Howie Karpin NYN 52 34 36 0.65 0.69 Bill Shannon NYN 52 40 32 0.77 0.62 Joe Donnelly NYN 25 13 19 0.52 0.76 Jordan Sprechman NYN 21 19 19 0.90 0.90 Billy Altman NYN 2 2 3 1.00 1.50 Dave Freeman NYN 2 1 1 0.50 0.50 -------------------------------------------------------------------------- David Feldman OAK 75 32 43 0.43 0.57 Chuck Dybdal OAK 43 26 25 0.60 0.58 Al Talboy OAK 34 15 19 0.44 0.56 Art Santo Domingo OAK 1 0 0 0.00 0.00 -------------------------------------------------------------------------- Bob Kenney PHI 88 48 66 0.55 0.75 Jay Dunn PHI 34 23 18 0.68 0.53 Mike Maconi PHI 28 16 16 0.57 0.57 John McAdams PHI 5 2 3 0.40 0.60 -------------------------------------------------------------------------- Bob Hertzel PIT 40 36 20 0.90 0.50 Bob Webb PIT 39 26 34 0.67 0.87 Tony Krizmanich PIT 38 23 25 0.61 0.66 Evan Pattak PIT 37 19 21 0.51 0.57 -------------------------------------------------------------------------- Bill Zavestoski SDN 94 64 54 0.68 0.57 Dennis Smythe SDN 62 30 26 0.48 0.42 -------------------------------------------------------------------------- Eric Radovich SEA 73 30 48 0.41 0.66 Dan Peterson SEA 45 24 33 0.53 0.73 Darin Padur SEA 36 22 21 0.61 0.58 Vinnie Richichi SEA 2 1 2 0.50 1.00 -------------------------------------------------------------------------- Art Santo Domingo SFN 77 40 51 0.52 0.66 Chuck Dybdal SFN 32 22 9 0.69 0.28 Al Talboy SFN 27 15 25 0.56 0.93 Michael Duca SFN 20 10 10 0.50 0.50 -------------------------------------------------------------------------- Mike Smith SLN 67 47 50 0.70 0.75 Gary Mueller SLN 66 43 51 0.65 0.77 Jeff Durbin SLN 20 18 13 0.90 0.65 -------------------------------------------------------------------------- Rick Martin TBA 81 63 40 0.78 0.49 Jim Ferguson TBA 72 53 51 0.74 0.71 Bill Mathews TBA 2 1 1 0.50 0.50 -------------------------------------------------------------------------- Steve Weller TEX 65 45 43 0.69 0.66 John Mocek TEX 46 25 16 0.54 0.35 Dan Schimek TEX 43 29 21 0.67 0.49 -------------------------------------------------------------------------- Doug Hobbs TOR 55 39 27 0.71 0.49 Louis Cauz TOR 53 31 35 0.58 0.66 Joe Sawchuck TOR 25 13 22 0.52 0.88 Stephen Utter TOR 19 9 7 0.47 0.37 Howard Starkman TOR 1 1 0 1.00 0.00 -------------------------------------------------------------------------- David Vincent WAS 90 52 51 0.58 0.57 Benjamin Trittipoe WAS 61 44 40 0.72 0.66 As you can see, in the case of the White Sox, Bob Rosenberg has credited the team with fewer errors per game than either of his co-workers, and at a rate that is low by comparison to other scorers who have worked a similar number of games. Interestingly, he's also worked a significant number of Cubs games. Other Options? I'm sure all readers will remember the controversy surrounding last year's postseason with regards to umpiring. What stood out in that context appears to be the same issue that ruffles feathers with regards to scoring decisions--essentially a lack of uniformity and standardization. Just as fans have no desire to endure umpires using different mechanics for strike, ball and out calls, there is no place in scoring for divergent interpretations of the rule book or the introduction of bias. Two of the proposed solutions, which both seem reasonable, are to increase the standardization through better or additional training for scorers, or to complete the move started in 1980 and scrap the idea of local scorers altogether by increasing the umpiring crews to five men, with one serving as the scorer. The more radical solution among the performance-analysis community would like to get rid of errors altogether. Despite my respect for those who do the job today, I'll admit some sympathy for either of the former solutions. You won't find in me in the more radical camp; while there may be problems in some quarters, the information we get from designation of errors is more valuable than not having that information at all.
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