Look who’s back! That’s right, The Lineup Builder (but you can call me “TLB” since we’re friends) is back. Grey and I avoided arbitration, and my contract was renewed for another year of fantasy baseball analysis. For those who followed my work here last season, thanks for rejoining the group. For those of you who are new, let me briefly tell you what “Analytics Anonymous” is all about.
(Editor’s Note: Be sure to check out our Razzball Commenter Leagues where you can face off against, TLB, Keelin, MattTruss, & all your favorite Razzball writers. Head HERE, scan the sheet for a date that works and click “Link” to join!)
Much like the other “AA”, everyone affiliated with Analytics Anonymous is part of a vast group of addicts providing love and support for one another. Of course, our addiction is fantasy baseball. More specifically though, our “TRUE” addiction is the underlying numbers associated with fantasy baseball. Say it with me, “My name is ______ and I’m an Analyt…holic!”
This season, Analytics Anonymous will be your bi-weekly (generally) journey through baseball’s analytics. Our focus will be solely on unearthing information and trends to help you successfully win your leagues – whichever format you play.
Sorting through the vast sea of numbers can be a daunting task for anyone. If Analytics Anonymous is successful, we’ll not only learn many of these acronyms together but even come to appreciate some of the information that’s literally at our fingertips.
One thing you’ll find with me is I usually start with the raw data (I love me some spreadsheets) and start analyzing to see where it takes me. Sometimes it reveals interesting correlations that we don’t typically look at. Other times, we find there’s nothing there at all. Don’t get discouraged, this can be useful information too. You’ll see what I mean as we go.
Power
For our maiden voyage, we’re going to look at Power. I hear what some of you are saying, “TLB, we count HRs, not Power. I’m only interested in hitting my mark in the HR category and you want to talk Power instead. What the…?” Fear not, young grasshopper, we have the same goal. We’re just going to come at it a little differently.
Last season, I did a couple of articles on this topic of power. I won’t regurgitate them here, but you may see a familiar theme if you read them before. If you want a gold star for our first session, you can go back and read them Did You Say…More Power? and More Fun Than A Barrel of Monkeys.
Now that we’re on the same page, we’re ready to get started. Grab your snacks and take a seat. We’re about to start looking at power.
Today’s session is also about trust. Specifically, do we trust the HR projections being thrust upon us from every direction? First of all, let me send a shoutout to all the projections analysts out there. It’s a tough, thankless, job putting together projected stats for the upcoming year.
Of course, some projections are always better than others in hindsight. Trust me, if I had a crystal ball to tell you which ones are going to lead you to the promised land, we’d both be rich. But I don’t and I’m not. The next best thing then is to put the ones we like best through an “analytical smell test” and see which makes the most sense.
In the end, everyone has their own recipe and it’s really up to our individual taste buds to determine which we want to consume. You’ll get to see what’s brewing in my kitchen here. Likewise, feel free to invite me into yours by commenting below.
For today’s hypothetical exercise, I’m going to use HR projections provided by THE BAT. Why THE BAT and not Razzball or ATC or any of the others? No real reason other than I generally found the HR projections here to be a little higher than the others (through a highly “unscientific” analysis). My goal today is not to prove or disprove the projections, but rather to share a method I use to see if a hitter’s projections pass my “analytical smell test”. Some will and some won’t, that’s just the nature of the beast.
To peel back this onion, here are the seven power-related analytics I’m going to use today:
HR/FB
“Home Runs per Fly Ball” is a self-explanatory analytic and seems to be used more and more as a primary justification for HR projections. I generally like this analytic but have come to realize we need a little more information than just HR/FB alone (remember, we’re peeling back the onion…).
As a general rule, the higher the HR/FB rate, the more HRs are hit. That makes sense, right? One of the problems I have with relying on HR/FB alone – there are too many other variables at play. Such as: park factors, launch angle, weather conditions, etc. Each player establishes their own HR/FB rate over a period of a few seasons, but we should be able to identify trends to help our analysis.
In 2023, a sampling of batters with > 250 PA identified Shohei Ohtani with the highest HR/FB rate at 31.2%. For the purposes of this analysis, I set a threshold of 20.0% as an indicator of “elite” HR/FB rates. Why 20.0%? Honestly, it’s purely subjective on my part because I’m looking for “elite” not just “above average” power producers.
HR/PA
“Home Runs per Plate Appearance” is not an often used analytic but a logical one to think about. In fact, it might be hard for you to find anyone including it in their projections. The beauty of spreadsheets though is that it’s very easy to calculate. Similar to HR/FB, we’re simply taking a measure of how many HRs are being hit each time a batter steps up to the plate. HR/PA also brings in many of the same issues identified before so I wouldn’t recommend relying on it alone. As part of a subset of analytics though, perfectly fine to look at.
Again, since this is not a mainstream analytic, you’re not likely to find experts telling you what an average vs. elite HR/PA rate is. That’s ok, we don’t need experts, remember we’re a support group… I think we can agree hitters like Aaron Judge, Matt Olson, and Shohei Ohtani were among the top power hitters in the game last year (hint: they were!). In fact, these fine players were amongst the top four in HR/PA rate, all above 7.35%. NOTE: I’m sure we’ll get to the fourth player later.
So, for me, I set the HR/PA bar at 5.50%. A total of 28 hitters surpassed that rate in 2023, the 28th ranked player being Ronald Acuna Jr. If I’m measuring elite, I think he’s a great place to draw the line. Don’t you?
EV
“Exit Velocity” is a relatively new “Statcast” metric in baseball but very important to consider. The increased speed at which the baseball comes off the bat has a direct correlation to favorable outcomes for a batter – no matter if the ball is a ground ball, line drive, or fly ball.
The league-wide average EV in 2023 was 89 mph and top batters tend to average above 90 mph. For my analysis of “elite” EV, I set my threshold at 92 mph.
LA
“Launch Angle” is another of the Statcast metrics used in baseball to describe the vertical angle of the baseball when it leaves the bat. The four widely used trajectories to describe batted balls include Groundball (less than 10 degrees), Line Drive (between 10-25 degrees), Flyball (between 25-50 degrees), and Pop-up (greater than 50 degrees).
The league-wide average LA in 2023 was 12.8 degrees. There’s no magic LA number that translates directly to a HR, but we can estimate a range that makes a HR more likely. For analysis’s sake, I tend to use a player’s average LA of greater than 15 degrees.
Why 15 degrees? I came upon this wonderful figure last year and dusted it off for this discussion. I really think you’ll like it too.
This figure illustrates how EV and LA work together to identify what’s called the “Barrel Zone” that leads to a higher probability of a favorable outcome (i.e., HR). As you can see in this figure, the “Barrel Zone” generally correlates with the Line Drive and Flyball trajectories discussed above. Looking at 2023 data, I found the absolute top average LA is greater than 25 degrees, but two-thirds of the top HR hitters were above 15 degrees.
Barrel%
Speaking of barrels, it is the term used to define a well-struck ball where the combination of EV and LA generally leads to a minimum 0.500 BA and 1.500 SLG. The “Barrel Rate” is simply the number of barrels divided by the number of batted balls.
The league-wide average Barrel% in 2023 was 8.1% and top batters tend to average above 12%. That number works for me too…12% it is.
HardHit%
“Hard-Hit” fly balls = more HRs. “Hard-Hit” line drives = higher BA and OPS. For today’s journey, we’re more interested in the former, but it goes without saying the ability to do both is the best scenario all around.
A “hard-hit” ball is defined as a batted ball with an EV of 95 mph or higher. The HardHit% then simply shows the percentage of batted balls that qualify as a hard hit.
I set my HardHit% threshold at 49%. Again, that’s a subjective number but I’ll note only 30 players met that criterion last season. So, that qualifies as “elite” to me.
Hard-Soft%
Like the HR/PA stat above, the “Hard%-Soft%” stat is not one you’ll likely see others share in their projections. I stumbled upon the value when I was playing around on my handy dandy spreadsheet last season and like overcooked linguini, it just stuck with me.
Calculating Hard-Soft% looks at the hard-hit metric we just discussed in a slightly different way. It is simply the percentage of hard-hit batted balls minus the percentage of soft-hit batted balls. Remember earlier when I said our focus is to unearth information and trends to help you successfully win your leagues? That’s why I’m circling back to his one.
As you might expect, the larger the difference between hitting the ball hard and soft is where our target zone lies. Unsurprisingly, the player with the best number here last season was Aaron Judge (45.83%). What may be a surprise is the only other player above 40% was J.D. Martinez (41.44%). Other players in the top 10 include Corey Seager, Josh Jung, and Yandy Diaz. It’s not a coincidence that all three players are migrating upwards in rankings lists this offseason too.
I set my Hard-Soft% threshold at 22%. Once again, that’s a subjective number (see a theme here?). Only 85 players made the cut on this one. That may seem like a big number but let’s not forget, 329 players met the 250 PA criteria to be part of this little project. So again, I’ll call that “elite” for this effort.
There you go, now we’ve gone over the Analytics Anonymous program and the acronyms we’ll be using to do the “power” analysis, let’s start getting into the numbers.
2023 HR Leaders
Of the top 20 HR hitters last season, only four hitters surpassed my criteria in all 7 categories. Only four! Matt Olson and Aaron Judge are not surprises but would you also have guessed Adolis Garcia and J.D. Martinez as the other two?
Here is the full list of top 20 HR hitters:
A few quick takeaways from this table:
- Barrel% plus either EV or LA (or both) is a pretty good indicator of elite power potential.
- HR/FB or HR/PA alone as predictors of elite power achieved only 75% accuracy in identifying the top 20 HR hitters.
- HardHit% is not a strong predictor of elite power without additional considerations.
- Having elite LA, without scoring in any of the other categories, can still translate to higher HR numbers…but can we trust there won’t be a regression on the horizon?
Since Barrel% is clearly the analytic that best predicts power, I expanded the analysis to add the top 30, top 50, and top 100 HR hitters of 2023. This table shows the percent of HR hitters scoring elite in Barrel% and then the same numbers with Barrel% plus one of the other six categories.
Some interesting results, isn’t there?
As I said before, Barrel% alone is a pretty good predictor of top-end power. Adding one other power analytic, such as HR/FB, HR/PA, EV, or HardHit%, doesn’t appear to move the needle all that much. However, Barrel% plus LA results in a noticeable increase in predicting power (that makes sense!).
The ideal circumstance is being elite Barrel% plus either EV or LA. As you can see in the final row, almost 90% of the top 50 HR hitters of 2023 scored as “elite” in Barrel% plus one of EV or LA.
So, how can we use that information pre-draft?
Based on 2023 data (250+ PAs), 66 players had a Barrel% rate of 12% or greater. Here are the top 20 players sorted on Barrel%, along with their seven-category score, 2023 HR total, and EV and LA rankings):
The first thing I notice are the four players with elite Barrel% but not EV or LA.
- Jake Bauers – Barrel% is the only elite category he scored in. With an average EV and slightly over average LA, his good contact skills are working against him in the HR department. Sure enough, I note his GB% (Ground Ball %) increased from 33% to 38%, validating that finding. The 1B/OF finds himself behind a number of regulars on the Brewers so unless he makes a dramatic increase in EV or LA, I don’t expect he’ll be too fantasy relevant this season. THE BAT seems to agree with their prediction of 10 HRs.
- Jake Burger – Burger scored in 5 of the 7 categories, just not EV or LA. Looking a little closer, his average EV is just below my cutoff – and I mean LITERALLY just below – at 91.9 mph. His Barrel% and EV have gone up in each of his 3 seasons (LA has remained consistent at 12.3 degrees) so the 2023 HR totals look repeatable. THE BAT is predicting 27 HRs, so I may be a little bullish on Jake in my drafts.
I won’t keep going but you see how I used the information to do a quick assessment of the elite Barrel% (without EV or LA).
Players like Aaron Judge, Shohei Ohtani, and Yordan Alvarez don’t really need a lot of extra analysis. If you have an opportunity to draft them, it’s a no-brainer.
However, a player like Patrick Wisdom makes for an interesting case. In our analysis, he ranked as the 2nd best in Barrel% and also scored in EV and LA (in all 7, as a matter of fact). So, why the depressed HR total (23) and why does THE BAT only predict 20?
First of all, he doesn’t really have an everyday home. In 2023, he played 97 games, spread around 6 positions. So continued limited ABs are going to be a problem for us. Most of his advanced metrics suggest his skills (EV, LA, Hit Strength, etc.) look repeatable though. He just needs better contact, as his Contact % is well below league average.
Prior to 2023, he was pulling the ball between 51-55% of the time. Last year, he saw a decreased rate in both pull and opposite field and a spike in batted balls to center field. That’s a problem too.
Overall, he’s a player I might take a late-round flyer on. His power metrics suggest he could have a breakout, even if he only brings the Contact % up to league average and pulls the ball a little more.
Wrapping It Up
So, those are a few examples of how I use these metrics to put projections through the “analytical smell test” before my drafts. I could go on and on, but I think you get the picture. You may find another way to use this information, paired with other variables, to come to similar or even different conclusions…and that’s ok. We’re a support group but we may not always agree on an outcome. That’s part of the fun.
This was a fun way for me to get back into the baseball swing of things. As the reader though, be sure to let me know your thoughts on this project. Did you find it useful? Drop a note below and give me your feedback.
When you come to the Razzball site you can find me on both the baseball and football sides. Just look for “The Lineup Builder” and you’ve found me! Also, be sure to follow me on Twitter/X @Derek_Favret. I’m now on BlueSky as well (@dfavret.bsky.social).
Until next time, my friends.
