# The Contract Year Effect: Fact or Fiction?

Anurag Bose, Nicholas Gould, Lucas Kunsman

In sports, the conventional wisdom is that a player’s performance in the last year of their contract is inflated because they are trying to increase their value as a free agent.  This is commonly referred to as the “contract year effect.”  However, does this supposed effect hold merit or is it based on solely the eye test and not backed up by numbers?

Major League Baseball provides an ideal platform to answer this question.  Since Bill James published his first Abstract in 1985, the sport has evolved to judge a player’s offensive and defensive performance with more advanced statistics than batting average and errors.  We propose using one of these measures, FanGraphs WAR (Wins Above Replacement), in testing the contract year effect.  The idea behind WAR is fairly similar to its name; it values the wins gained by a team if a player played a full season for them as opposed to if a “replacement level” player played the season for them.  It is a plus/minus statistic, where a replacement level player has a value of zero, and the further a value is from zero on the positive side, the more value a player provided his team in that year.  This statistic was chosen because it looks at all aspects of a player’s game in determining their value, as opposed to only their ability to hit for power or only their ability to steal bases, and is a measure of worth that can be applied to both pitchers and batters. (1)

We propose gathering WAR data from fangraphs.com (2) 10 random free agents from ESPN.com for the free agent signing periods of 2009, 2010, and 2011 (3). We will use a random number generator and the list of free agents from ESPN to generate a sample of 30 players.  We will compare their established average WAR over each players’ careers up until their contract year to their WAR from their contract year. We will use a hypothesis test with the null hypothesis that there is no contract year effect, and that the WAR of the contract year will match the players’ established career average WAR.  The alternative hypothesis will be that the WAR does not equal the established career average WAR, so that we may investigate whether any contract year effect, positive or negative, exists.

Potential limitations in this project include the varying performance of a player over their career; WAR from season to season can change dramatically. To counteract this we will consider all seasons of the player’s career as our baseline, and the contract year as the sample that we are testing the null and alternative hypotheses with.  Once these tests have been completed, we can construct confidence intervals of different significance levels. If the player’s WAR in their contract year falls outside of the confidence interval then the null hypothesis can be rejected for the alternative hypothesis. We can then look at individual players who have a statistically significant contract year and determine if there are any cases that interest us especially.

Works Cited

(1) Slowinski, S. (2010, February 15). What is WAR? Retrieved from http://www.fangraphs.com/library/index.php/misc/war/

(2) Fangraphs. (2011). Baseball Player Search. Retrieved from http://www.fangraphs.com/players.aspx?lastname=

(3) ESPN. (2012). 2011 MLB Free Agents. Retrieved from http://espn.go.com/mlb/freeagents/_/type/ranked.