Why are stochastic processes with decreasing expected value called supermartingales? I am curious to know why a process which has decreasing expected value is called a supermartingale.
From a beginners perspective it would seem reasonable to have the following picture:
                ________ (increasing) above ==> super
            ___/
       ____/
      /
E[X]: ------------------ (constant) martingale
      ___
         \_____________
                       \ (decreasing) below ==> sub

Is there a reason why the names where choosen the way they are?

Edit: here is an additional reference:

Snell: Your book established martingales as one of the small number of important types of > stochastic processes. How do you get interested in martingales?
Doob: [... ] The martingale definition led at once
to the idea of sub and super martingales, and it was clear that these
were the appropriate names but, as I remarked in my 1984 book
((Classical Potential Theory and Its Probabilistic Counterpart,
Springer-Verlag 1984), the name supermartingale was spoiled for me by
the fact that every evening the exploits of "Superman" were played on
the radio by one of my children. If I had been doing my work at the
university rather than at home I am sure I would not have used the
ridiculous names semi- and lower semimartingales for sub- and
supermartingales in my 1953 book. Perhaps I should have noted that one
reason for the success of that book is the prestigious sounding title,
a translation of a name in a German Khintchine paper.

 A: As far as I know, this naming has its origin in the connection between Brownian motion and harmonic functions. Let $B$ be a $d$-dimensional Brownian motion. Let $f:\mathbb{R}^d\to\mathbb{R}$ be twice continuously differentiable. By Ito's formula, we have
$$
  f(B_t) = f(0) + \sum_{i=1}^d\int_0^t \frac{\partial f}{\partial x_i}(B_s) dB^i_s + \frac{1}{2}\sum_{i=1}^d \int_0^t \frac{\partial^2 f}{\partial x_i^2}(B_s) ds.
$$
Here, the sum of the first two terms is a local martingale, but let's just think of it as a martingale, call it $M$. Also introduce the Laplace operator as
$$
  \Delta f = \sum_{i=1}^d \frac{\partial^2 f}{\partial x_i^2}.
$$
We then have
$$
  f(B_t) = M_t + \frac{1}{2} \int_0^t \Delta f(B_s) ds.
$$
Now, a function $f$ is called harmonic when $\Delta f = 0$, subharmonic when $\Delta f\ge0$ and superharmonic when $\Delta f\le 0$.
From the above, we then see that $f(B_t)$ is a martingale when $f$ is harmonic, a supermartingale when $f$ is superharmonic and a submartingale when $f$ is subharmonic. This shows the benefit of the definitions of supermartingale and submartingale: It allows for a notational correspondence to superharmonic and subharmonic functions. Of course, why functions are called "subharmonic" and "superharmonic" in the way that they are is then a different question...
A: There is a quote on this point from page 808 in J.L. Doob's Classical Potential Theory and Its
Probabilistic Counterpart.  

Before martingales had been formally christened, Lévy [1, 1935; 2, 1937],
  Bernstein [1, 1937], and other mathematicians had analyzed some of their properties in 
  special contexts; usually the martingales in question arose as partial sums $n\mapsto \sum_0^n y_j$ of a sequence $y$ of random variables under the condition $\mathbb{E}(y_j\mid y_0,\dots, y_{j-1})=0$ so that the sums arose as generalizations of sums of 
  independent random variables with zero means. Ville [1, 1939] defined a martingale very nearly as a positive martingale is now defined but tied it to a sequence of independent 
  random variables under analysis. His fundamental tool, a fact he proved, was that almost 
  every sample sequence of a  positive martingale is bounded (see Theorem 9). Doob [1, 1940] discussed martingales and proved the basic convergence properties under the name 
  "family of random variables with the property $E$." ("$E$" was chosen not as the initial letter of "expectation" but as the first letter in the alphabet following "$D$".) 
  Under the respective names "semimartingale" and "lower semimartingale," submartingales and supermartingales were introduced in [Snell 1, 1952] and [Doob 4, 1953]. This obviously inappropriate nomenclature was chosen under the 
  malign influence of the noise level of radio's SUPERman program,
  a favorite supper-time program of Doob's son during the writing of
  [Doob 4, 1953]"

Bernstein [1] = Serge Bernstein, On some transformations of the Chebyshev inequality.
(Russian) Dokl. Akad. Nauk. SSSR 17 (1937), 275-277.
Doob [1] =
Doob, J. L., Regularity properties of certain families of chance variables. 
Trans. Amer. Math. Soc. 47, (1940). 455–486. 
Doob [4] =
Doob, J. L., Stochastic processes. John Wiley & Sons, Inc., New York; Chapman & Hall, Limited, London, 1953. viii+654 pp. 
Lévy [1] = Paul Lévy, Propriétés asymptotiques des sommes de variables aléatoires enchainées, Bull. Soc. Math. Fr. 59, (1935), 1-32.
Lévy [2] = Paul Lévy, Théorie de l'Addition des Variables Aléatoires. Paris, Gauthier-Villars, 1937.
Snell [1] = Snell, J. L. Applications of martingale system theorems. Trans. Amer. Math. Soc. 73, (1952). 293–312. 
Ville [1] = Jean Ville, Etude Critique de la Notion de Collectif. Paris, Gauthier-Villars, 1939.
