D. The Law of Large Numbers
The law of large numbers is a fundamental theorem of the theory of probability that indicates that if we repeat many times (tending to infinity) the same experiment, the frequency of a certain event happening tends to be a constant.
The law of large numbers indicates that if the same experiment is carried out repeatedly (for example, throwing a coin, throwing a roulette wheel, etc.), the frequency with which a certain event will be repeated (if the face or seal comes out, the black number 3, etc.) will approach a constant. This constant will be the probability that this event will occur.
Suppose the following experiment: roll a common dice. Now consider the event that the number 1 comes out. As we know, the probability of the number 1 is 1/6 (the dice has 6 faces, one of them is the one).
What does the Law of Large Numbers tell us? It tells us that as we increase the number of repetitions of our experiment (we roll more dice), the frequency with which the event will be repeated (we get 1) is will bring each one closer to a constant, which will have a value equal to its probability (1/6 or 16.66%).
Possibly at the first 10 or 20 pitches, the frequency with which we get 1 will not be 16% but another number 5% or 30%. But as we make more and more releases (say 10,000), the frequency at which 1 appears will be very close to 16.66%.
As the Law of large numbers indicates, in the first throws the frequency is unstable but as we increase the number of throws, the frequency tends to stabilize to a certain number that is the probability that the event will occur (in this case numbers from 1 to 6 since this is the roll of a dice).