for RMD version: https://rpubs.com/chadgordon09/step9

**1. Expected Value Added (eV+) is simply: Results minus Expectations.**

2. Building on the logic from the last two posts (Step 7 – Expected Value in Attacking, Step 8 – Expected Value of Input Situations) we merely combine the two to determine the value of each touch. Output eV comes from kills, errors, blocks, or the value of the non-terminal outcome of the attack. Input eV (in this case, but the concept is wildly flexible) comes from whether you’re hitting In-Sys/OOS + the number of blockers you’re facing. These specific values are laid out in previous posts.

3. Above, we take a look at the 2019 National Championship match. We take the average Input eV that each attacker faced – as well as the the average Output eV they created and simply find the difference: **Results minus Expectations.**

4. As you can see Plummer, McClure, and Haggerty all had *relatively low Input eVs* meaning they were put in situations where the *expectations were lower* – this makes sense as these 3 are frequently asked to hit OOS sets against multiple blockers, which we know from Step 8 has a lower expectation of scoring.

5. Not surprisingly, Gates and Campbell saw a lot of good situations with high expectations (high Input eV values) – but they also performed above and beyond, creating Output eV values (good results) of over 0.500.

6. Kathryn Plummer. I suppose it’s no longer hype is it’s real, but she was yet again at her best when her best was needed. Despite having the lowest Input Expected Value on average (meaning she dealt with the toughest situations of any player) – she was above to generate maximum value given those opportunities. **She was able to hit 0.329 points above expectation. ***That is absurd.*

6.1 Just to reiterate. Given the cards she was dealt, Plummer was expected to hit 0.146 – and she found a way to hit 0.475 (in eV). That’s nuts. In traditional hitting efficiency she hit 0.459, for those who are curious. Which is also nuts – in a national championship, against 2 massive middles, and a team that prides itself on defense – that’s insane.

7. This example is more of a proof of concept. My advice would be to create Expected Values for the specific team/opponent you’re working with – and fiddle around with how you calculate Expected Value. In my example, I have chosen a specific way to do this, but it is not the only, nor possibly the best way to create these calculations.

8. Expected Value Added (eV+) again is simply: **Results minus Expectations**. Given the situations a hitter faced, how well did she perform based on how other hitters have performed historically in that situation. When taken in the aggregate, eV+ can also serve as a way to *monitor training, chart longitudinally if a player is performing better over time, and can be integrated with sport science/athlete monitoring data to better understand how those factors affect performance*. All these avenues benefit from an improved, more complete metric of player performance, rooted in how a player’s action helps or hinders your ability to win the rally: **Expected Value Added (eV+)**.