New Contributor Mike on the Highest Value Players in Showdown

Hey! My name’s Mike and I am going to start writing my own articles for the site, however first I wanted to introduce myself, my background with showdown, and what my articles will be like in the future.

I’m originally from New Jersey and so needless to say, growing up in the 90s, I am a diehard Yankees fan. One of, if not my earliest memory, is the Yankees winning in ‘96. I was undoubtedly spoiled. 

Andy Pettitte was always my guy (fun fact: he had the most wins in the majors from ’00-’09). 

My best friend and I started playing Showdown in 2000 after his cousin introduced him to the game. Fast forward about a decade and a half, and we lived together after college. Being employed individuals we were able to live out our childhood dreams and managed to complete the OG sets. He got 2000 and I got 2001, and let me tell you, 10 year old Mike would be super jealous. Like many of you, when the 2002 (etc.) sets came out, we were reluctant to embrace them as we liked the simplicity of the original game. When we played we would go all in and just pick the best players we had at every position. At a young age it was clearly biased towards the teams and players we liked. However now that we’re “adults” we turned to our excel knowledge to get a little more in-depth to figure out who really is the best player at each position. So kind of in a compare and contrast evaluation to Matt’s posts of the highest point players at each position, these are the highest value players at each position based on my calculations.

The purpose was strictly to figure out what the best offensive players were at each position. Defense mattered less since we normally were having a drink while playing and so we kept it simple most of the time. I have some defensive calculations but I’m not as fully behind them as I am the offensive metrics and maybe I’ll do some more posts in the future that adds that in. However, trying to properly weight it alongside the hitting created some problems that I figured would be easier to ignore.

I chose to use the wOBA, and more specifically, weighted runs created. It allowed me to connect major league stats to the charts in the easiest manner (instead of calculating the weighted runs in showdown which would open wormholes and too much statistical extrapolation). Here Fangraph explains the mindset behind wOBA and here is the actual value of each outcome per year. I debated taking each card and matching it to the year’s data-however in the Showdown universe, all runs are created equal and that was the whole purpose behind making these cards in the 2000/2001 style. So I averaged these results to come up with the actual weighted run value of each outcomes (for 1B+ I averaged 1B and 2B). One of the biggest short comings in this data is that all Outs are created equal. Similarly to fielding, trying to calculate the probabilities of different outs occurring and their results created a lot more problems than solutions, so I chose to ignore it. Eventually I’ll go back and break down the outs and the likelihood they advance runners, but right now that data isn’t in my spreadsheet. I did however include speed against the average catcher’s arm since in the hyperlink there is a value for SB vs CS.

From here on out when I refer to AP it is the statistical average pitcher of all MLB Showdown cards ever created in the ’00 and ’01 style from here and the OG sets. This data will change as time goes on depending on the cards that are made, however there are a lot of data points now and it shouldn’t change too much going forward. AB is the average batter, done in the same way as above.

In order to get the probability of each chart I compared them to the AP. So I took the probability of them getting the advantage (OB-C/20) and multiplied that by their chart’s weighted runs created and added it to the average weighted runs created against the AP’s chart to get the total expected runs created for each batter. Similarly this can be done in reverse for pitchers, although the math isn’t quite as clean but I got it to work. Since I know this is hard to understand even when talking in person, I’ll walk you through what the “average” MLB Showdown Hitter and Pitcher looks like and the math behind creating this rating.

This is the AB:

Average	HR	2.50
Batter	3B	0.51
On-Base	2B	2.49
7.99	1B+	0.62
Speed	1B	6.05
15.40	BB	4.02
290.55 Points	Out	3.81

 

To Give you a visual idea, the closest person (I had a few to choose that were close but I’m gonna stick with my Yankees) is:

 Do you think someone else deserves to be here? Let me know-I might have missed someone!

For the AP I broke them down into Starters and relievers and then combined those over 9 innings for my calculations.

Average	HR	0.05	Average	HR	0.06
RP	3B	-	SP	3B	-
Control	2B	0.05	Control	2B	0.78
3.86	1B+	-	3.68	1B+	-
IP	1B	1.69	IP	1B	1.84
1.17	BB	1.20	6.29	BB	1.18
155.71 Points	Out	16.35	405.24 Points	Out	16.14

So for Pitchers there’s a lot more options that are close to the numbers, but I’ll broaden my horizons with these guys:

                So now that you have an idea of what I’m working with:

 I multiplied the AB chart against the average expected runs by the amount of each result (ie .7059*4.02, 1.0935*0.62, etc as said in the link) and so you get the average expected runs for the AB of 18.26 per chart. However it won’t always be his advantage (really only ~1/5^th of the time) so you need to multiply those (18.26*.2). Then you need to do the same thing for the AP’s chart and multiply that by 4/5ths and add those together and you get the expected outcome of about 3.95 runs. If you double this it’s just shy of 8 runs a game, which isn’t too far off of what the actual average runs a game is for the MLB over the past ~70 years.

Obviously it’s not perfect, but I think it does a good job of getting an idea of what the best cards are from an offensive stand point. Let me know in the comments what the pros/cons are for doing it this way, or if you want it explained further I’m more than happy to discuss. Would also love to hear who you guys think will be the top players for each position based on this calculation method!