ok this is a little long but it has all the answers. Since it is long i proveded a summery of the findings. If you can't stand to read the whole thing just read the abstract then skip to the conclusion at the bottom, but hey someone might have a lot of time on their hands and want to dispute the findings.
A summery of the results is:
Players will have a decreased batting average in the year before free agency (since it has been found batting average has little effect on salary) but will not suffer a decrease in home runs(since it is more directly linked). However, home run ratio was not improved at all in the year before free agency. So i guess all of us who draft players based on contract years were fools and we should instead stay away from such players.
Equity Theory Versus Expectancy Theory
The Case of Major League Baseball Free Agents
Joseph W. Harder
Department of Management, Wharton School of the University of Pennsylvania
ABSTRACT
Equity theory and expectancy theory make different predictions under conditions of perceived underreward coupled with strong performance–outcome expectancies. A synthesis of these theories is proposed: Equity performance effects depend on the strength of the performance–outcome expectancy. Free-agent nonpitchers in the 1977–1980 baseball seasons were compared with a random sample of nonpitchers. These free agents probably felt underrewarded before entering the free-agent market yet probably also had expectations of higher salaries after becoming free agents. These competing motivations were hypothesized to affect individual performance. Two types of performance were assessed. Batting average, which had a weaker relation to salary outcome, declined in the year before free agency, whereas home run ratio, which had a stronger relation with salary outcome, did not decline. These results are consistent with the proposed synthesis.
A number of theories have been proposed to explain individual motivation to perform in organizations. Equity theory and expectancy theory are two approaches that have generated a considerable amount of research, but under some conditions, these two theories produce opposite predictions. One such set of conditions was explored in the current field study, which was designed to test alternative equity and expectancy theory predictions.
According to equity theory (Adams, 1963, 1965; Walster, Walster, & Berscheid, 1978), outcomes will be perceived as fair when the ratio of outcomes to inputs is equal across individuals. Inequity exists when the outcome–input ratios between a focal person and a comparative referent are unequal. Inequity is posited to create tension, which motivates an individual to restore equity. This restoration of equity can be accomplished in a number of ways. Outcomes can be altered, objectively or psychologically; inputs can be altered, objectively or psychologically; comparative referents can be changed; or an individual can leave or psychologically withdraw from the situation. As Greenberg (1989) pointed out, however, equity research offers little guidance as to when psychological adjustments rather than objective adjustments will occur. Complicating the matter further, psychological adjustments are difficult to measure and validate. Thus, this study was focused only on objective changes in inputs to allow for clear operationalization of the dependent variable. In addition, the focus on objective measures allows a more direct comparison with expectancy theory.
According to expectancy theory (Mitchell & Biglan, 1971; Nadler & Lawler, 1977; Porter & Lawler, 1968; Vroom, 1964), individuals will be motivated to perform by two expectancies. The first expectancy is the probability that a given performance will lead to certain desired outcomes. The second expectancy is the probability that effort exerted will lead to the desired performance. These two expectancies interact with each other and with the valence (attractiveness) of outcomes to determine the overall level of motivation.
Previous theorists have addressed the relationship between equity theory and expectancy theory. Lawler (1968, 1973) and Campbell and Pritchard (1976) subsumed equity theory under expectancy theory. They argued that the theories are not really in conflict because of substantial looseness in how both theories are defined and that the expectancy model can explain findings from equity research. In this view, perceptions of equity affect the valence of outcomes and therefore affect motivation.
Mowday (1987), however, argued that, because of the ambiguity in the two theories and the lack of research evidence that perceptions of equity affect the valence of outcomes, it is “perhaps premature to conclude that equity theory can be incorporated into expectancy theory” (Mowday, 1987, p. 106). Instead, Mowday agreed with Adams's (1968) advocacy of research identifying the conditions under which either equity or expectancy theory, predictions hold. Similarly, Pinder (1984) argued that, rather than searching for an all-encompassing motivation theory, researchers should be testing middle-range theories of motivation. In this vein, I delineate one situation in which equity theory and expectancy theory make somewhat different predictions.
Previous discussions of equity theory predictions of performance have centered on two types of pay systems, piecework and hourly (e.g., Campbell & Pritchard, 1976; Greenberg, 1982; Lawler, 1973; Mowday, 1987). Implicit in these discussions is the assumption that piecework pay systems link pay to performance, but hourly pay systems do not. This view limits the comparability between equity and expectancy theories because, under pay systems with no link to performance, expectancy theory predicts no motivation from pay. In more complex pay systems, the possibility of varying degrees of pay for performance exist. Salaried employees, in particular, encounter pay systems that might contain elements of both hourly and piecework pay. Relatively fixed pay rates are analogous to hourly pay systems, but to the extent that these infrequent pay adjustments are linked to performance, there are similarities to piecework pay systems. This more complex pay system presents situations in which the two theories make different predictions.
One such situation arises when individuals perceive themselves as underrewarded with relatively fixed pay while still perceiving strong performance–outcome contingencies. If an individual perceives underreward, equity theory posits that he or she will be motivated to decrease the inequity. One way to do so is to decrease performance. However, expectancy theory posits that an individual will increase performance if he or she perceives a strong performance–outcome expectancy. Under these conditions, then, the theories suggest different performance motivations.
Prior Research
Equity theory predictions about reactions to inequity have been tested primarily in laboratory experiments. The typical experiment involves (a) subjects performing a task, (b) distribution of a monetary reward and performance feedback, and (c) measurement of performance on a subsequent iteration of the task. Situations of inequity are set up through the manipulation of rewards and performance feedback, and individual responses to these inequitable situations are measured. As reviews of equity research have pointed out (Goodman & Friedman, 1971; Greenberg, 1982, 1987; Walster et al., 1978), these laboratory studies have shown that equity perceptions can significantly alter individuals' performances. However, these studies have been largely “one-shot affairs” (Homans, 1982, p. xv) and have typically not allowed time for performance–outcome expectancies to develop among subjects. Subjects who decrease their performance when faced with perceived underreward probably do not view this decrease in performance as leading to decreased future rewards.
Lord and Hohenfeld (1979) performed a field study to test the equity theory hypothesis that perceived underreward leads to lowered performance. They analyzed the performance statistics of major league baseball players who entered the 1976 season without reaching contractual agreement with their teams, and who were thus free agents who were deemed to be playing out their option. This was possible because of a landmark arbitration case in December 1975, which ruled that baseball's reserve clause (which had bound players to a particular team) was valid for only one year. The 1976 collective bargaining agreement between baseball owners and players allowed for a player to play out his option after six years in the major leagues (for a review of this and other baseball labor history, see Dworkin, 1981).
Lord and Hohenfeld (1979) argued that because these players chose not to sign contracts for the 1976 season, they were not satisfied with what the owners were offering for their services. Exacerbating this dissatisfaction was the fact that 83% of the players in the sample had received pay decreases from their 1975 contracts. These were generally 20% decreases because players choosing to play out their option were guaranteed at least 80% of their previous year's contract value. Finally, two previous cases of free agency had occurred in 1975 and had been widely publicized, thus providing players with clear external referents. The fact that these two cases had both resulted in free-agent, multiyear contracts in excess of $1,000,000 also could have contributed to players' feeling underrewarded. Lord and Hohenfeld argued that these facts suggested perceptions of inequitable underreward on the part of players choosing to play out their options and would therefore result in substantial performance decrements.
Lord and Hohenfeld (1979) reported performance decrements in batting average (base hits divided by number of official times at bat), home run ratio (home runs divided by the number of official times at bat), and runs batted in (the group means of free agents were compared with their previous three seasons' performances and the performances of non-free-agent teammates). Lord and Hohenfeld concluded that these performance decrements, under conditions of inequitable underreward, confirmed equity theory predictions. Lord and Hohenfeld focused their analysis only on nonpitchers because pitchers' less frequent performances made performance statistics more variable. The analysis in this paper follows the same reasoning.
Duchon and Jago (1981), in an extension of Lord and Hohenfeld's (1979) analysis, included players participating in the first three years of baseball's free-agent reentry draft. They also reported group means and in their overall analysis found no significant performance decrements in the option year. When Duchon and Jago split their analysis into first-year versus second-and third-year free agents, however, they found significant differences in group means. Their analysis of first-year free agents mirrored the results that Lord and Hohenfeld found, namely, performance decrements consistent with equity theory predictions. However, in the second and third years, group means increased for most performance statistics.
Duchon and Jago's (1981) results seem to contradict equity theory predictions. They cast their analysis in an expectancy theory framework as follows: Players preparing to enter the free-agent reentry draft expected that good performance would lead to higher financial rewards through more intense and spirited bidding for their services. First-year free-agent batters faced a great deal of uncertainty about what kind of rewards they could receive because the only two previous cases of free agency had been pitchers. In addition, these cases had arisen from specific court rulings rather than from a general change in the labor agreement. Second- and third-year free agents, however, saw the large rewards that first-year free agents received, and this strengthened their performance–outcome expectancy. Duchon and Jago also claimed that this explanation was consistent with equity theory, if altering future outcomes (i.e., free-agent salaries) rather than present inputs (i.e., performance in the option year) was the chosen equity-restoring strategy.
There have been relatively few studies in which equity theory and expectancy theory predictions have been tested simultaneously. Klein (1973) compared equity theory, expectancy theory, and reinforcement theory as predictors of satisfaction. He found that equity and expectancy variables were significant predictors of satisfaction, with equity variables being somewhat more powerful. He did not compare the theories' predictions of performance, however.
Vecchio (1981) compared competing predictions of equity theory and expectancy theory on performance for conditions of piecework overpayment. He found that individual degree of moral development was an important moderator of inequity resolution via performance changes. Individuals high on moral maturity were more likely to conform to equity theory predictions of increased performance than were individuals low on moral maturity.
Competing predictions of equity and expectancy theory have not been explicitly compared for conditions of salaried under-payment with varying degrees of pay for performance. In this article, the results of an analysis of the first five years of major league baseball free agents are presented, and a synthesis of the two theories is proposed, as follows: An individual who perceives underreward will be motivated to decrease performance to an extent dependent on the strength of the performance–outcome expectancy.
The specific research hypotheses were
Hypothesis 1. If the performance–outcome expectancy is weak, performance will decrease.
Hypothesis 2. If the performance–outcome expectancy is strong, performance will increase.
Free agents in their option year were anticipating going through the reentry draft and having their services bid for in an open auction. Prior performance would certainly be expected to affect the market value of specific players. The interesting question for this analysis was whether all types of performance affected free-agent salaries equally. For example, did batting average have the same effect as home runs on free-agent salaries? If not, there might be different performance effects under conditions of underreward.
Many studies of salary determination in baseball have been performed (e.g., Chelius & Dworkin, 1980, 1982; Hill & Spellman, 1983, 1984; Pascal & Rapping, 1972; Scully, 1974a, 1974b, 1989), and lifetime and previous season's performance were generally found to significantly predict salaries for major league baseball players. Because of problems of multicollinearity among various baseball performance statistics, researchers have generally selected the one measure of performance that was most predictive of salaries. For baseball nonpitchers, this measure has most often been a player's slugging percentage, which is defined as the total sum of bases attained by a player with his base hits, divided by his total official times at bat.1 This finding indicates that hitting for power is more rewarded than merely a high batting average. However, these studies were not focused only on free agents, so it is unclear whether similar patterns of reward prevail for free agents. Hill and Spellman (1984) found that a dummy variable for the free agents in their sample was a significant positive predictor of salaries, which suggests that free agents made higher salaries, other things equal, than did non-free agents. Hill and Spellman did not address whether returns to different performance types (e.g., batting average versus home runs) were different for free agents than for non-free agents. Thus, it was necessary in this study to assess the strength of the performance–outcome expectancy for each type of performance.
If results for free agents are similar to results from previous studies of all players, then the hypotheses can be specified more precisely. That is, if hitting for power is more strongly linked to salary, expectancy theory predictions of increased performance should hold for the home run ratio. If high batting average is less strongly linked to salary, equity theory predictions of decreased performance should hold.
Method
Sample
A listing of major league baseball players who became free agents in the years 1976–1980 was obtained from Dworkin (1981). As in the studies of Lord and Hohenfeld (1979) and Duchon and Jago (1981), only nonpitchers were included in this analysis.
Free-agent salary data were available for 17 nonpitchers from the first year of free agency (1976). The salaries of these 17 players were used to assess the strength of the performance–outcome expectancy for subsequent free agents.
Complete performance data were available for 106 nonpitchers who participated in Years 2 through 5 (1977–1980) of the free-agent reentry draft. Career performance statistics for each player were obtained from the Official Baseball Register (Sporting News, 1977, 1978, 1979, 1980, 1981). In addition, a random sample of 40 non-free-agent nonpitchers who had played two consecutive years in the major leagues was drawn for use as a comparison group; career statistics for these players were also collected from the Official Baseball Register. 2 Thus, the total sample for the analyses of performance consisted of 146 players. Results of t tests showing that the random sample did not differ significantly from the free agents on either performance measure are presented in Table 1.
Performance–Outcome Expectancy
It is likely that batting average and home run ratio lead to different performance–outcome expectancies for free agents. This was assessed in two ways. First, a simple multiple regression of free-agent salary on the two performance statistics was run for the first year of free agency (1976), the only year for which complete salary figures were available (see Dworkin, 1981).
The variables were annual salary (S) after free agency, in thousands ( S t+1 ) ; batting average (BA; hits divided by official at bats) in option year ( BA t ) ; and home run ratio (HR; home runs divided by official at bats) in option year ( HR t ) .
The t subscript denotes that the variable is for a player's option year. Recall that the option year is the year preceding free agency for players, not the year after going through the free-agent reentry draft. Because the performance–outcome expectancy involves future salary, this variable has the subscript t + 1, signifying that salary is in the year following the free-agent reentry draft.
The regression equation was
This operationalization of the performance–outcome expectancy assessed the effect of each performance measure on first-year free-agent salaries, controlling for the effect of the other performance measure. Because the measures may be correlated with each other, it was important to discern their independent effects. However, it is perhaps unreasonable to expect players' perceptions of performance–outcome expectancies to take partial correlations into account. Thus, the second method of operationalizing the performance–outcome expectancy was to obtain simple correlations of batting average and home run ratio in the option year with first-year free-agent salaries.
Synthesized Performance Model
The analysis in this study differs from the previous studies of free agents in the use of multiple regression; results reported are at the individual level of analysis rather than at the group level. This allows an explicit control for each player's prior performance. Also, the analysis includes data for four years of free agency, which increases the sample size considerably over earlier studies. Finally, this analysis diverges from Lord and Hohenfeld's (1979) and Duchon and Jago' (1981) studies in that only batting average (base hits divided by official times at bat) and home run ratio (home runs divided by official times at bat) were analyzed. As Lord and Hohenfeld pointed out, these two measures of performance are most independent of teammates' efforts or team strategy. Because equity theory and expectancy theory performance predictions are made at the individual level, it is desirable to maximize the independence of players' efforts.
For each player in the sample, the following variables were collected or compiled: Batting average (hits divided by official at bats) in year prior to option year ( BA t−1 ) ; career batting average prior to option year ( BA career ) ; batting average in option year ( BA t ) ; home run ratio (home runs divided by official at bats) in year prior to option year ( HR t−1 ) ; career home run ratio prior to option year ( HR career ) ; home run ratio in option year ( HR t ) ; and contract status (C; this was a dummy variable taking the value 1 if the player was a free agent and 0 if the player was part of the random comparison sample). The means, standard deviations, and correlation matrix for these variables are presented in Table 2
Ordinary least squares models of batting average and home run ratio were computed. Two sets of models were tested. In the first, BA t−1 and HR t−1 (previous season's performance) were used as control variables, and in the second, BA career and HR career (prior career performance) were used as control variables to better assess changes from baseline performance measures. Previous season's performance is a better indicator of recent performance, but career performance is a better indicator of ability level. All control variables could not be used in the same model because of problems of multicollinearity.
If the link between free-agent salaries and power hitting is indeed stronger than the link between salaries and batting average, then the relationship between free agency and batting average tests the first research hypothesis: Given a weak performance–outcome expectancy, performance will decline. The relationship between free agency and home run ratio tests the second hypothesis: Given a strong performance–outcome expectancy, performance will increase.
The equations for the models using previous season's performance are as follows:
and
The equations for the models using career performance are as follows:
and
Results
Performance–Outcome Expectancy
Both operationalizations of the performance–outcome expectancy revealed that first-year free agents were rewarded more for hitting home runs than for batting average. The regression results and correlations are presented in Tables 3 and 4. Home run ratio in the option year significantly affected freeagent salary, t (14) = 2.309, p < .05, two-tailed, but batting average did not, t (14) = 1.362, ns . Because 1976 was the first year of structural free agency, these results can be used to operationalize the performance–outcome expectancies. Subsequent free agents probably perceived a strong performance–outcome expectancy for home run ratio but a weak performance–outcome expectancy for batting average.3
The simple correlation coefficients also show that home run power was more strongly linked to first-year free-agent salaries than was batting average. The correlation between home run ratio and free-agent salary was positive and significant, r = .57, p < .01, two-tailed.4 The correlation between batting average and free-agent salary was both smaller in magnitude and less significant, r = .42, p < .05, two-tailed. Furthermore, for these 17 free agents, batting average and home run ratio were not significantly correlated, r = .26, ns . This provides further evidence that second- through fourth-year free agents perceived home runs as more rewarded than batting average in the free-agent marketplace.
These results allow further specification of the hypotheses. Because batting average was relatively weakly linked to free-agent salaries, equity effects were expected in the form of lowered performance. Because home run ratio was relatively strongly linked to free-agent salaries, expectancy theory effects were expected in the form of increased performance.
Synthesized Performance Model
The regression results from both sets of models support the proposition that inequity-reducing performance effects will occur only if performance–outcome expectancies are weak. In the equations using previous season's performance (presented in Table 5), free agency had a significant negative effect on batting average in the option year, t (143) = – 1.701, p < .05, one-tailed, as predicted in Hypothesis 1. Contrary to the prediction of Hypothesis 2, free agency had no significant effect on home run ratio in the option year, t (143) = 0.004, ns .
Similarly, in the equations using career performance as an explanatory variable (presented in Table 6), free agency had a significant negative effect on batting average in the option year, t (143) = –2.002, p < .05, one-tailed, but no significant effect on home run ratio, t (143) = –0.365, ns .
These results are consistent with the proposed integration of equity theory and expectancy theory. A person will not decrease his or her performance in response to perceived underreward if doing so is expected to lead to a loss of future desired outcomes. For baseball players in their option year, home run ratio was strongly linked to free-agent salaries, but batting average was not. Thus, these players could allow their batting averages to decline without future rewards suffering significantly. However, they could not allow their home run ratios to decline without negatively affecting their salary after free agency.
Both expectancy and equity theory predictions must be moderated in this case. According to expectancy theory, performance increases in home run ratio would be expected because this aspect of performance was significantly linked to free-agent salary. According to equity theory, performance decreases in home run ratio would be expected in response to financial underreward. Lord and Hohenfeld (1979) reported that home run ratio among free agents decreased in the option year, whereas Duchon and Jago (1981) reported that home run ratio increased. However, both of these analyses were at the group level. In this analysis, at the individual level, there were no significant effects of free agency on home run ratio. At the group level, batting average in the option year for free agents was significantly lower than batting average in the second year for players in the random sample, t (144) = –1.97, p < .05, one-tailed, but there was no significant difference in home run ratio, t (144) = 0.18, ns . Overall, these results can be interpreted as the outcome of two conflicting motivations for free agents.
Discussion
The results reported in this article lead to some important managerial implications. Types of performance that were strongly linked to future salaries (i.e., home run ratios for free agents) did not decrease even though equity theory suggests that they should have. Thus, the expectancy effect appears to be powerful enough to mitigate the equity effect. This result provides evidence for strengthening performance–outcome expectancies for desired performances.
At the same time, types of performance that were not strongly related to salaries (i.e., batting average) did decline under conditions of inequitable underreward. This provides some evidence that equity effects on performance will occur if there are not strong performance–outcome expectancies.
Most interesting, however, might be the finding that performance types for which there were strong performance–outcome expectancies (i.e., home run ratios) did not increase under conditions of inequitable underreward. This evidence suggests that inequity might lead to subtle performance effects, preventing performance increases rather than resulting in performance decreases.
In summary, both direct and indirect inequity effects arose. Individuals faced with inequitable underreward decreased their performance if that performance was not strongly linked to future rewards and failed to increase performance if that performance was strongly linked to future rewards.
Some questions remain unanswered by these analyses. The results reported may be due in part to the fact that home run ratio exhibits greater year-to-year stability than does batting average. Indeed, the stability of home run ratio from year to year (measured by the square of the simple correlation coefficient between HR t−1 and HR t ) was .444, whereas the stability of batting average (measured by the square of the correlation between BA t−1 and BA t ) was only .100. Consequently, the R 2 values of the equations differed markedly. In the set of models using previous season's performances as the control variables, the equation for HR t achieved an R 2 of .444, whereas the equation for BA t attained an R 2 of only .118. In the set of models using career performances as the control variables, the comparable figures were .473 and .150, respectively. Thus, much of the variance in batting average remained unexplained. Nevertheless, the relationship between free agency and batting average was statistically significant in both models. The stability argument is also refuted by evidence that in the third year of data (the year following free agency for free agents) home run ratio did decline significantly for free agents compared with the random sample, t (126) = –2.016, p < .05, two-tailed. Thus, there is evidence that significant changes in home run ratio can occur from year to year.
It seems doubtful that the results obtained in this study are due to regression to mean performance levels. There was a decline in batting average, which might be consistent with regression to the mean, but there was no change in home run ratio. If regression to the mean were the cause of the performance decline in batting average, some change in the home run ratio would be likely. This is especially true in light of the fact that home run ratio did decline significantly in the third year of data, as discussed previously.
A final alternative explanation for these results is that the decrease in batting average exhibited by free agents in their option year was a by-product of players' attempts to increase home run output because of their strong expectancy about the link between home run ratio and free-agent salaries. This explanation suggests that there might be a trade-off between home run power and batting average and that attempting to increase one might lead to a decline in the other. However, as seen in Table 2, there is evidence contrary to this explanation. There was a significant positive correlation of .283 between BA t−1 and HR t−1 , a significant positive correlation of .230 between BA career and HR career , and a significant positive correlation of .160 between BA t and HR t . This suggests that there is a small complementary effect rather than a trade-off between batting average and home run ratio across players.
Conclusion
The results presented here suggest that individuals faced with inequitable underreward will choose the avenue of decreased performance to the extent that it does not affect future rewards. If decreasing performance will adversely affect future rewards, then alternative avenues for restoring equity will be undertaken. This analysis tested only one avenue for equity restoration, performance changes. As mentioned earlier, inequity resolution can take many forms. Assessing any of these other forms cannot be accomplished using the existing data with the current methods. Qualitative data about perceptions of underreward or selection of comparative referents would help in assessing whether these other avenues are used.
Conceptually, this analysis is limited because the focus was only on monetary rewards. As Mowday (1987) pointed out, expectancy theory and equity theory both allow for a wide variety of rewards. Although this article contributes to motivation research by explicitly comparing the two theories, future research could benefit by including a broad range of rewards.
The focus on professional baseball players limits the generalizability of the findings. In particular, performance statistics for this sample are widely distributed in newspapers, year-books, etc. The publicness of performance records might make performance decreases less likely as an inequity reducing strategy because any decreases would be readily apparent to a number of observers. Different patterns of performance effects might arise in cases in which performance is not well known or highly quantifiable.
Finally, the analysis in this article, along with the previous studies of free agents, was based on the assumption that free agents perceived themselves as underrewarded in their option year. Although this assumption seems reasonable, an attempt to quantify the degree of objective underreward or to assess perceptions of underreward would be a positive step for future research.
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An earlier version of this article was presented at the April 1987 annual meeting of the Western Academy of Management, Hollywood, California. Barry Posner's encouragement in that endeavor was greatly appreciated.
I gratefully acknowledge the comments of Jeffrey Pfeffer, Jerald Greenberg, James Baron, Rod Kramer, Jerry Porras, Joseph Schwartz, Gerald Davis, Sarah Corse, three anonymous reviewers from the Western Academy of Management, and two anonymous reviewers from the Journal of Applied Psychology.
Correspondence concerning this article should be addressed to Joseph W. Harder, Department of Management, Wharton School of the University of Pennsylvania, 3620 Locust Walk, Suite 2015, Philadelphia, Pennsylvania 19104.
Last edited by thedude on Wed Feb 09, 2005 11:32 pm, edited 2 times in total.
"I do not think baseball of today is any better than it was 30 years ago... I still think Radbourne is the greatest of the pitchers." John Sullivan 1914-Old athletes never change.
Pedantic wrote::-S Maybe I'll read the whole thing when I can set aside a day...or two.
i'm sure your mommy will let you say up past your bedtime and help you with any tough words if you ask her really, really nicely...
JK. Just read the abstract and last 2 sections and you will get the point of the whole study. Feel bad for me, do you have any idea how many of these i had to read when i was in a Pysch class? this one is relativly short.
"I do not think baseball of today is any better than it was 30 years ago... I still think Radbourne is the greatest of the pitchers." John Sullivan 1914-Old athletes never change.
Pedantic wrote::-S Maybe I'll read the whole thing when I can set aside a day...or two.
i'm sure your mommy will let you say up past your bedtime and help you with any tough words if you ask her really, really nicely...
JK. Just read the abstract and last 2 sections and you will get the point of the whole study. Feel bad for me, do you have any idea how many of these i had to read when i was in a Pysch class? this one is relativly short.
It's not the vocabulary -- it's the fact that I have a difficult time reading long articles or papers on a computer screen, especially in that font. And, no, I don't feel bad for you.
Pedantic wrote::-S Maybe I'll read the whole thing when I can set aside a day...or two.
i'm sure your mommy will let you say up past your bedtime and help you with any tough words if you ask her really, really nicely...
JK. Just read the abstract and last 2 sections and you will get the point of the whole study. Feel bad for me, do you have any idea how many of these i had to read when i was in a Pysch class? this one is relativly short.
It's not the vocabulary -- it's the fact that I have a difficult time reading long articles or papers on a computer screen, especially in that font. And, no, I don't feel bad for you.
i included a summary of the findings for you.
"I do not think baseball of today is any better than it was 30 years ago... I still think Radbourne is the greatest of the pitchers." John Sullivan 1914-Old athletes never change.
Players will have a decreased batting average in the year before free agency (since it has been found batting average has little effect on salary) but will not suffer a decrease in home runs(since it is more directly linked). However, home run ratio was not improved at all in the year before free agency. So i guess all of us who draft players based on contract years were fools and we should instead stay away from such players."
ok. Do we have some evidence, like a list of say 50 recent free agents w/ stats to back it up? If someone was doing some sort of scientific study, surely they had some evidence beyond the theory to back it up. I don't personally play that much attention to contract years when drafting but it seems to figure into quite a bit of discussion. Jeez, Maggs did ok contractually and he hardly played at all last year...
While I don't prescribe to the contract year theory, the results are faulty or currently irrelevant for any number of reasons.
First, the article was published in June 1991. Assuming that the researching/writing/editing process took at least a month, and to hit publication another month. We're looking at salaries from 1990. That's 15 years ago. The average salary in 1990 was $578,930. A hefty some for Willie Loman, but a pitance to today's player. Without looking too hard, in 2003 the average salary topped $2.5 million. That's a near 500% increase. More importantly, the league minimum is $316,000, that's almost the average salary in 1990. The increase in big money means an increase in motivation, and before big money, I'm pretty sure no one was taking "contract year." The term is an invention beginning in the mid-90s, comingling with the salary boom. That's problem one, increased incentive.
Problem two, also has to do with increased incentive. Carlos Beltran has more incentive to have a big season than Travis Lee or Mike DeJean. In 1990, Robin Yount made $3.2 million. More than any other player. In 2004, Manny Ramirez made $22.5 million. The best players have another $15-$20 million a year on the line. That's incentive.
Problem three, there is some credence to a contract year today. Looking at the top 11 FA this off-season, five had what can be considered career-years or their best year of their career: Beltran, Beltre, Pavano, Varitek, and JD Drew. Four others were proven names that were injured for most or a significant portion of the year: Magglio, Sexson, Glaus, and Delgado. The other two are Pedro and Renteria. Pedro's getting old and probably just got his last contract. He knew he was going to get paid one way or the other. I think his context here is outside the scope. Therefore, Renteria is the anomoly. Food for thought.
In the long run, I think a "contract year" is bogus. I think most "contract years" coincide with the magical ages of 27-29, or peak years.
I think that the guys who play professional baseball are players first and professionals second. They do the best they can pretty much of the time. Sure, you see guys get 'issues' here and there but, at least in most of the games I've seen, you see guys trying to win. Not punch the clock and avoid screwing up.
Any kind of heated batter pitcher matchup looks intense but, if you watch closely, MOST of the matchups are one on one, one guy pitching and one guy trying to hit. I have seen few times where somebody 'gives up' at the plate, even pitchers!!
Sure, maybe here and there, the thought of "damn, ARod gets 62 MILLION DOLLARS A YEAR, HIT THE DAMN BALL" probably crosses people's minds as a distraction but, when you are playing whatever, softball, tennis, golf, cage matches, are you playing to win or to score points for some guy's fantasy team or your agent? I'd have to say that winning is the first thing that's on most of their minds. Whatever Budweiser spokesperson 'Leon' may say!!
joshheines wrote:While I don't prescribe to the contract year theory, the results are faulty or currently irrelevant for any number of reasons.
First, the article was published in June 1991. Assuming that the researching/writing/editing process took at least a month, and to hit publication another month. We're looking at salaries from 1990. That's 15 years ago. The average salary in 1990 was $578,930. A hefty some for Willie Loman, but a pitance to today's player. Without looking too hard, in 2003 the average salary topped $2.5 million. That's a near 500% increase. More importantly, the league minimum is $316,000, that's almost the average salary in 1990. The increase in big money means an increase in motivation, and before big money, I'm pretty sure no one was taking "contract year." The term is an invention beginning in the mid-90s, comingling with the salary boom. That's problem one, increased incentive.
Problem two, also has to do with increased incentive. Carlos Beltran has more incentive to have a big season than Travis Lee or Mike DeJean. In 1990, Robin Yount made $3.2 million. More than any other player. In 2004, Manny Ramirez made $22.5 million. The best players have another $15-$20 million a year on the line. That's incentive.
Problem three, there is some credence to a contract year today. Looking at the top 11 FA this off-season, five had what can be considered career-years or their best year of their career: Beltran, Beltre, Pavano, Varitek, and JD Drew. Four others were proven names that were injured for most or a significant portion of the year: Magglio, Sexson, Glaus, and Delgado. The other two are Pedro and Renteria. Pedro's getting old and probably just got his last contract. He knew he was going to get paid one way or the other. I think his context here is outside the scope. Therefore, Renteria is the anomoly. Food for thought.
In the long run, I think a "contract year" is bogus. I think most "contract years" coincide with the magical ages of 27-29, or peak years.
Just something else to think about.
it is true the study was published 15 years ago, but at the time they used numbers from the first 15 years of free agency and were able to come up with trends. I don't think the amount of salary that a player is making effects him psychologically. he still wants to prefrom well enough to get the best contract possible no matter when he was playing. I think the point was players concentrate upon the stats which will earn them money in 1990 it was homeruns and not batting average upon which players were valued, and i think this is still true today. if so you can expect a drop in batting average in the average slugger (since prespective teams care more about home runs). But if the player is a say a lead off guy and power is not his game he will expreice a drop off in power as he tries to hit for a better average.
"I do not think baseball of today is any better than it was 30 years ago... I still think Radbourne is the greatest of the pitchers." John Sullivan 1914-Old athletes never change.
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by thedude » Wed Feb 09, 2005 8:52 pm 
Maybe I'll read the whole thing when I can set aside a day...or two.
And, no, I don't feel bad for you.
