When Winning Really Matters…

A while back, I was involved in a fun discussion on the Tabletop Baseball+ Facebook group page about baseball game mechanics when a friend of mine posted the following: “When I’ve got a player who will ultimately hit .220, I will use him as much as I have to but certainly not in clutch situations, even though he was used that way during the season.”

It’s an intriguing point. As a kid playing replays in the late seventies and early eighties, I didn’t much care if the lineups for the teams I was playing were optimized to score the maximum number of runs, just as I didn’t care if the relief pitcher I called in from the bullpen was particularly skilled at his craft. My goal was not to win— I was managing both teams, after all— but rather to faithfully recreate games from that season. Indeed, without cable television (much less the Internet and Baseball Reference or Retrosheet to guide me), trying to settle on a lineup was hard enough!

That all changes when you’re playing to win. All of a sudden that .220 hitter who was relied on to perform in the clutch and didn’t (he did, after all, bat just .220) is no longer a viable option in those situations. Indeed, unless his defense is extraordinary, he is probably not the best choice to start, either.

In this article, I’ll consider position players who either started and put up rotten numbers as well as position players who did not start and put up extraordinary numbers and discuss ways to handle both.

For the most part, this discussion will be limited to dealing with these situations as they apply to one-offs or a short series of games (like you might encounter when playing in a tournament, for example), not an entire season.

We’ll start with the player whose playing time was limited but nonetheless put up monster numbers, a situation I like to refer to as “The Oscar Gamble Problem” because it first came to my attention when I was a kid playing Strat-O-Matic baseball with the 1979 card set.

The Oscar Gamble Problem: The Hot Hitting Reserve

For those too young to remember, Oscar Gamble was a journeyman outfielder who played for seven different teams during a 17-year major league career. By most accounts, Gamble, a lifetime .265 hitter, enjoyed his best year in the majors playing for the Chicago White Sox in 1977, when he finished 29th in the voting for American League MVP. But I can assure you his best season actually occurred two years later when he split time between Texas and New York and didn’t receive a single MVP vote.

Don’t take my word for it; check out the stats. In 64 games for Texas, Gamble managed to hit a career-best .335 (his previous best was .297 during the aforementioned 1977 season) and compiled enough extra-base hits to record a .522 slugging percentage. But even these gaudy statistics paled in comparison to those he compiled during his brief stint in The Big Apple later that same year, where he batted an incredible .389 and belted 11 homeruns in just 113 at bats*. His slugging percentage was .735 and his OPS a dazzling 1.187, stratospheric numbers shared by players named Ruth, Williams and Bonds.

For players of tabletop games at the time, this presented a real problem. Gamble wasn’t just a good backup outfielder for New York, he was easily their best player. If Jackson was, as he once claimed, “the straw that stirred the drink” in New York, Gamble was the drink. His statistics were clearly superior to Jackson’s and anyone else on the team for that matter. The decision to play him in left field over Piniella was a no-brainer, despite Piniella’s solid stats: .297 BA, 137 hits, and 69 RBI (third best on the team behind Jackson and Nettles).

In my experience, there are a couple of ways to deal with situations like this. One technique is to divide position players into three groups: starters, bench players, and emergency players and refer to the table below.

Pct. Games Played* Description
60% to 100% Starters. No restrictions on how they are used.
40% to less than 60% Bench Players. Can be used as pinch-hitters and defensive replacements.
Less than 40% Should be relegated to emergency situations only!

* You should feel free to adjust these percentages as you see fit.

Since Gamble played only 36 games for New York (22%), he will only be available in emergency situations (e.g., if and when Piniella is injured, etc.). Of course, you can play around with these percentages as you see fit but it’s a good idea to place at least some restrictions on these sorts of players. While less effective for Texas, in the game I created, Baseball Trivia Challenge, Gamble is worth more than 0.5 runs per game to the New York lineup, a figure that could result in as many as 10 additional wins over the course of a 162 game season or a critical victory in a 7-game series.

A second approach is to simply divide the number of games the player played by the number of games his team played during the season, convert that number to a d20 dice roll, and roll to see if the player is available before each game. For example, using this approach, Gamble would need to roll a 4 or less to be eligible to play.

While this approach will generally work to assure each player appears in the appropriate number of games, it isn’t particularly realistic, as players aren’t often shuffled in and out of the lineup every other game for no apparent  reason. Also, in the case of Oscar Gamble the main reason he missed so many games is because he wasn’t with the team until early October. As we’ll see throughout this discussion, there are no perfect solutions.

Next, we’ll consider the starter who compiled unimpressive numbers at the plate. For this example, we may as well consider the standard-bearer in this regard.

The Mendoza Line: What to do about Poor Hitting Starters

Mario Mendoza was a slick-fielding shortshop who struggled at the plate, compiling a lifetime .215 batting average. The term “Mendoza Line” was coined by his Mariner teammates, Tom Paciorek and Bruce Bochte, and was intended as a harmless joke. Today, it is frequently used to define the threshold of mediocre hitting, which is generally defined as a .200 average. If you’re below the Mendoza Line, you’re not long for “The Bigs”, or so the saying goes.

This is a harder case. The rules we discussed earlier to deal with hot-hitting reserves assures they are unlikely to be available to start in place of a weak-hitting starter, but do not prevent other players who played at least 60% of their team’s games from starting in his stead. For example, Larry Milbourne, who played 65 games at shortstop and was a better hitter, could be used to replace Mendoza for the ’79 M’s.

One approach to prevent this from happening is to assign starters and backups at each position based on games played.

In the case of Menoza and Milbourne, this approach would work well, since Mendoza played in 148 games and Milbourne only 65; however, in cases when the difference between the starter and backup is much smaller, it may not work as well if it works at all. For example, Leon Roberts played 67 games in left field for Seattle in 1979, but Tom Paciorek (47 games), John Hale (34), Dan Meyer (31) and Joe Simpson (27) all saw significant time at the position.

A second approach— to create d20 ranges for each player and roll to see who plays that game— has all the drawbacks mentioned earlier. In addition, it is not only a work intensive solution, it takes control away from the manager.

A third approach would be to utilize the d20 ranges described for “hot” players but instead of rolling to see who will play that game, roll to see who is “available” to play during the series or tournament. You could eliminate those players deemed “unavailable” entirely. Thus, it would be quite likely that Gamble would not only be unavailable to start, he would be unavailable period!

This situation is precisely the case described by my friend and is very difficult to deal with. In cases when the player is clearly in the lineup due to his defensive prowess, it is not unreasonable to conclude he is more valuable than other players at that position as a result. It isn’t unreasonable, but it may not be true. Indeed, I don’t believe it to be true in the game I created, where Mendoza is a much better fielder than Milbourne but fielding plays are relatively rare.

Part of the problem get’s to the heart of the issue my friend described: managers in a tabletop baseball game not only know the statistics each player compiled that year, but exactly how good they are according to the ratings in the game. For example, tabletop baseball game managers know that George Brett, who led the American League with a .329 average in 1990, batted just .255 the following year, but managers John Wathan and Hal McRae, who played with Brett and witnessed his brilliance, would have had no idea. Even if they assumed Brett wasn’t the .305 hitter he was over his lifetime, they might at least assume he was a .290 hitter or, at worst, a .280 hitter. But .255? Never!

If anyone has a great way of handling situations like this, post your ideas below!

* Starting in about 1973, Gamble consistently showed good power leading to above average slugging percentages. Near the end in his career in 1984, Gamble still managed to slug 10 homeruns in just 125 at bats despite hitting just .184.


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