# Elo Ranking Expected Scores

I am implementing an Elo ranking system for fun and came across an example on Wikipedia that I can't follow:

Suppose Player A has a rating of 1613, and plays in a five-round tournament. He or she loses to a player rated 1609, draws with a player rated 1477, defeats a player rated 1388, defeats a player rated 1586, and loses to a player rated 1720. The player's actual score is (0 + 0.5 + 1 + 1 + 0) = 2.5. The expected score, calculated according to the formula above, was (0.51 + 0.76 + 0.88 + 0.56 + 0.28) = 2.99. Therefore, the player's new rating is (1613 + 32(2.5 − 2.99)) = 1597, assuming that a K-factor of 32 is used.

To calculate $E_A$ I am using the following formula $E_A = \frac 1 {1 + 10^{(R_B - R_A)/400}}$ which gives me the described result for the first match ($\frac 1 { 1 + 10^{\frac {(1609 - 1613)} {400}}} \approx 0.51$) but I can't figure out how to determine the expected scores for the following matches (i.e. $0.76$, since $\frac 1 { 1 + 10^{\frac {(1477 - 1613)} {400}}} \approx 0.69$).

$$\frac 1 { 1 + 10^{\frac {(1477 - 1613)} {400}}} \approx 0.69$$
$$\frac 1 { 1 + 10^{\frac {(1388 - 1613)} {400}}} \approx 0.79$$
$$\frac 1 { 1 + 10^{\frac {(1586 - 1613)} {400}}} \approx 0.54$$
$$\frac 1 { 1 + 10^{\frac {(1720 - 1613)} {400}}} \approx 0.35$$