Typically when you open a pack of cards, you will flip to the back of each card and see a rather predictable set of stats. There will be batting average, home runs, RBI, runs scored, strikeouts and walks for hitters and W-L, ERA, WHIP, strikeouts and walks for pitchers. Newer cards will feature a player’s social media handles, and recently popular stats such as OPS and WAR. These will show up in newer sets because these are stats that have become heavily ingrained in modern baseball discourse. Turn on MLB Network or any pre-game show and you will hear terms such as WAR, launch angle, FIP and exit velocity mentioned on a fairly regular basis. That’s how much the game has evolved from a data standpoint.
Be prepared for more new terms to appear on the back of your cards though. There are a lot of new developments in the world of advanced stats and analytics that are starting to make their way into the conversation around player evaluation. Front offices are armed with more data than ever before and some new ideas are becoming prevalent considerations in roster construction that were not previously. Let’s check out what some of these are.
Hitting Categories
Average Exit Velocity
You don’t need advanced analytics to tell you that you have a better chance of recording base hits when you’re consistently hitting the ball hard. After all, fielders have that fraction of a second less to react when the ball is hit hard. Therefore, we care a lot about which hitters consistently hit the ball the hardest. Turn on any baseball game and the term ‘exit velocity’ will escape the announcer’s mouth multiple times. Therefore, expect to see this stat on your cards soon.
ISO
Isolated power is meant to reflect the raw power of a player. It works similarly to batting average but only takes into account extra base hits. Formula can be (2B + 2*3B+3*HR)/AB or simply BA - SLG. It is a nice tool but personally not one I am super invested in. (like launch angle) That said, I do like that it is a weighted stat that reflects that not all hits are created equal.
WRC+
What if you had a stat that told you how productive a hitter is in general relative to the rest of his peers in any given season? That would be a rather important piece of information to have on hand right? Well, that is basically what WRC+ is meant to tell you. Furthermore, this stat with a rather elaborate formula takes into account factors such as home ballpark to remove the skew that this can have on hitting stats. It is basically the king of hitting stats and rightly should be on the back of a baseball card.
Pitching Stats
FIP
Fielding Independent Pitching has the stated goal of indicating how a pitcher would perform if we were to strip out the influence that a pitcher’s fielders would have on his performance which simple ERA calculations do not. If every pitcher received the same level of fielding on his behalf, how would he perform? FIP serves to give us a truer indication than ERA ever could. It zeroes in on the true outcomes, strikeouts, base-on-balls and homers to filter out that which a pitcher cannot control. Calculating FIP involves two steps as explained on Fangraphs.
SIERA
Skill Interactive Earned Run Average serves to quantify the performance of a pitcher whilst also taking into account balls put into play, which is a limitation of the similar stats FIP and xFIP. I view this stat as a very powerful holistic assessment tool for pitchers, much like WRC and WRC+ for pitchers. Like those stats for hitters, it performs the highly useful function of removing biases in the data such as ballpark factors and so forth.
If you want the formula, it is this work of art: 6.145 - 16.986(SO/PA) + 11.434(BB/PA) - 1.858((GB-FB-PU)/PA) + 7.653((SO/PA)^2) +/- 6.664(((GB-FB-PU)/PA)^2) + 10.130(SO/PA)((GB-FB-PU)/PA) - 5.195(BB/PA)*((GB-FB-PU)/PA).
Stuff +
We’ve always said something like “he has good stuff” when we evaluate a pitcher. Historically, this has been a purely qualitative assessment. We watch how pitches move and mainly make note of velocity, (especially with fastballs) but up until recently, we had not really gotten around to quantifying how good a pitcher’s stuff is. Now, with the ability to track information such as horizontal and vertical pitch break, extension during pitch delivery and of course, the increasingly talked about spin rate, we can finally quantify how good each pitcher’s pitches are. Better still, we can assess how good those pitches are relative to the league, and that is the purpose of Stuff+. Calculating Stuff+ requires fairly complex mathematical modeling but what you need to know is that like with stats such as OPS+, 100 is considered the baseline. Anything above 100 suggests better than average stuff for that specific pitch and anything lower than 100, below average. For example, a Stuff+ of 140 for your fastball relative to every MLB pitcher is outstanding, like an IQ of 140 makes you effectively a genius. There are varying models, but the most recognizable model is that from Fangraphs.
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