The 2023 digital editions (full and appendix) of The Process are now available to be purchased (the paperback is off to the printers and will be available in two to four weeks). These editions are packed with new information. Read the rest of this entry »

It was a disappointing end to the 2022 season for me as I wrote up in my “What Missed” article. Stepping back, I shouldn’t be complaining with my first five-figure season (over 200% ROI), winning my LABR and TGFBI leagues, and almost the TGFBI overall (screw second). Here are a few things that did work. Read the rest of this entry »

It is time to look back on my season to see what worked and what didn’t. I had planned on just doing this Debby Downer article on what didn’t go right but it was depressing so tomorrow there will be an article full of humble brags and self-back pats. For today, it’s time for a beatdown.

Too much in a single player (a.k.a. the Luis Robert experience)

Tanner Bell and I shared nine draft-and-hold leagues and had the insane “luck” of drafting last in three of them. We liked Robert’s power-speed combination so we kept picking him there to the tune of five times. That was way too much exposure to a single player.

Tanner was on the BaseballHQ podcast with Patrick Davitt and one of his hitter banes was Robert. I commented on him bashing Robert and here was his response.

Tanner is about as calm as it gets and it is a rarity to see him get that worked up. We had Robert in over half our leagues and constantly battled from behind.

Simply, we had too many resources devoted to a single top-round pick. It was tough at the end of the first to diversify (ended up with Ozzie Albies and Bryce Harper, great) but we needed to limit our exposure to a single star.

A lack of diversification isn’t as much of an issue later in the draft, where players are likely headed to the wire at some point during the season.

The other issue with Robert is that I had blinders on for guys with steals and didn’t look at other options. Here are my rankings from my last draft.

Oh look, I have Aaron Judge and Yordan Alvarez ranked higher than Robert and I didn’t draft any Judge or Alvarez. None. While Judge and Alvarez did have some injury risk (so did Robert) and were projected as just four-category guys (I know Judge stole some bases), so I was off. Even though I plan on drafting fewer leagues next year (later topic), I need to diversify my top six to 10 picks (I’m not sure how many) hoping for Judge-like breakouts or not having my season riding on one player.

Lack of Power

I struggled for power in all my leagues. I have gotten to the point of ignoring Runs and RBI on draft day knowing I can stream them. There was no streaming for home runs this season. For reference, here are my overall percentile standings in NFBC leagues with an overall competition.

Here are the average of the percentile finishes:

Stat: Rank
Runs: 76%
HR: 54%
RBI: 77%
SB: 70%
AVG: 80%
K: 84%
W: 65%
SV: 69%
ERA: 56%
WHIP: 60%

Even with my home runs near 50%, I was able to push my Runs and RBI almost to 80%. If only I had a bit more power. I knew this deficiency was going to be an issue about a month into the season but I just couldn’t correct it. In the Main Event, we quit focusing on it and pushed all in for stolen bases and batting average.

Two issues were the cause: I expected the juiced ball to stay but it disappeared along with many 20 HR hitters (102 in 2021, 71 in 2022). Additionally, I just didn’t add enough power bats with too much of a focus on speed and batting average) and when I did, I missed (see: Jesús Sánchez).

I need to settle on a power metric that doesn’t matter what type of ball major league baseball is using that season.

Way Too Many Leagues

Over the past few years, I’ve kept adding leagues as the industry invitations and my bankroll have increased. I even took it a step further and agreed to manage a few leagues. It ended up doing 13 draft-and-holds and 17 FAAB leagues. Even typing it out seems like an insane number. It was way too many!

The volume cost me on two fronts. I don’t think I was able to concentrate on each league, especially at the season’s end. For most of the season, I just tried to add as many stats as possible, but when each league and opponent needed to be scrutinized in detail, the time commitment ballooned.

Here are some close calls:

In this league, I missed out on over $7000 in prizes by losing this close batting average race.

In TGFBI, I could have been the overall winner with just one more Win.

In my auction championship with Tanner Bell, we held onto a second-place tie but just a little bit here-or-there would have helped.

In the NFBC Online Championship, I managed two teams that ended up in the top 20. Each Win was worth around 50 points, so picking up one or two over the course of the season would have made a huge difference.

While it was nice to have more horses in the game, I think it cost me in the long run. I’m going to cut back on the number and concentrate on leagues with higher entry fees. Also, I might consider dropping one or two industry leagues. Finally, I’m going to rely on best ball leagues (zero in-season management) to fill my preseason draft itch.

Cross-off or acknowledge similar players (Myles Straw rule)

In the Tout Wars auction, I had all the speed I wanted when Myles Straw came up for auction. I wasn’t completely off Straw (even though he fell on his face) because Tout Wars is an on-base league.

I didn’t need a speed source at all. I needed a well-rounded power bat and I was grinding for home runs the entire season.

Auctions, especially in dollar days can be a little chaotic, but I need to cross off any rabbits once I feel I have enough speed.

As we head toward the final week and a half of the season, we have one more full week for weekly transaction leaguers to ponder. While this current week included two teams with eight games and no teams with fewer than six, next week features teams playing between five and seven games. Let’s review which teams to more highly consider their players (seven gamers) and which teams you should consider alternatives (five gamers). Below are the teams in each group, plus a handful of players that should get a relative boost in value and aren’t heavily owned, along with borderline players who should see a relative reduction in value.

Read the rest of this entry »

A couple of weeks ago, I examined hitters who were getting No Respect from the opposing defense. The pitchers were throwing these batters slow fastballs right across the plate. Additionally, the fielders moved up because they didn’t expect the guy to hit the ball with authority. After getting some hints from the comments and some changes I listed in the original article, I decided to implement a some with the goal to find inexperienced major league hitters who might not have shown all their power and have another gear. The MLB teams know of this power since they have access to minor league Trackman information. Read the rest of this entry »

Recently I wrote up Myles Straw, I found out the league was throwing him the most fastballs (60%, league at 49%) and the most pitches in the strike zone (57%, league at 50%). Additionally, slow fastball pitchers weren’t afraid of him with the 13th lowest fastball velocity against. I went one step further and looked to see how far outfielders were playing him and he was one of the shallowest played guys. He was just getting no respect. Read the rest of this entry »

On this past weekend’s On The Wire Podcast, there was a discussion surrounding Esteury Ruiz stolen base numbers and the effect of the minor league pitch clock. The gist of the situation can be taken from this Tucker Davidson tweet thread.

Some Take Aways From the newly installed pitch clock. I’ve made 3 starts with it and each time it’s been a different experience. Overall not a fan. Let’s talk about the good and the bad. (Thread) @jjcoop36 @JeffPassan

— Tucker Davidson (@tucktuck6) April 29, 2022

The rate of stolen bases is up in the minors as soon as they implemented the change. With the numbers up, I wanted to calculate a simple rule to see how much I should expect a hitter’s stolen base rate to change once promoted, especially rabbits like Ruiz.

For the calculations, needed to set some ground rules. I limited my sample to this season’s hitters who stole four or more bases in AAA. Additionally, they had to go on and have 30 MLB plate appearances. In the end, 40 players met the requirements. I know the sample isn’t the biggest, but I’m just looking at how a hitter’s stolen base rates should change.

For the first test, I compared the stolen base attempt rate ((SB+CS)/(1B+BB+HBP)) in AAA and the majors. In AAA, the median stolen base rate among these guys was 19.5% and it dropped to 10.8% in the majors. When comparing the ratio change (MLB rate/AAA rate) it worked out to 53.5%. So a hitter’s stolen base rate should drop about 50%.

The next test was to look at the success rate. In AAA, this group had an 80.2% success rate and it dropped to 72.1% in the majors. A success of 80% would help a team while 72% hurts their chances of winning.

One final test, what was stolen base per plate appearance change. This value is a quick rule of thumb that takes into account attempts, success, and changes in on-base rate. This value works that the MLB rate is 43% of the AAA numbers.

So going back to Ruiz, here are his expected stolen base rates knowing what he did in AAA.

Here are the stolen base per 600 PA values for our projection systems.

His projections are close but just a little lower than the value I found. Maybe I should just follow the projections.

The following nerd talk can be blamed on Ozzie Albies. Currently, he’s on the IL after needing surgery on his broken foot but plans on an August return. While digging through his stats, I was not sold on him being an early-round difference maker. Over the past two seasons, he just had a .255 AVG after it was at .279 in his first four seasons. One obvious change was that he has really started going for flyballs with his Flyball Rate (and Launch Angle (LA)) heading up.

What I wanted to know if Albies has changed his swing for more power and a lower batting average should be expected going forward.

To find the values, I had to do some manipulation of the public StatCast data. I don’t like how it’s currently being provided, so I needed to make a few adjustments.

First, instead of the 95 mph cutoff for the Hard Hit rate (used by BaseballSavant.com), I prefer 102 mph based on this Twitter thread I had with Jon Anderson.

Okay minimum exit velo at 26-30 degrees to reach .500 AVG and 1.500 SLG

2019: 98 mph
2020: 98 mph
2021: 100 mph
2022: 102 mph

— Jon Anderson (@JonPgh) May 20, 2022

A batter’s swing path is the point where they create the hardest contact. The theory behind this concept can be found in these two articles. The value is a by-product of the Hard Hit query. Both of the values can be found in this BaseballSavant search.

The key with this information is to find the sweet spot of getting enough air under the ball for line drives and home runs while at the same time not popping up for some easy outs. Here are six graphs that will get us to a simple rule. If you don’t want to be overwhelmed by the graphs and numbers, feel free to jump down to the Conclusions section.

Graph and Math Stuff

For this step, I going to compare the average hitters’ Isolated Power (ISO) and BABIP using the Hard Hit% and Bat Path. I studied all non-pitchers from 2015 to the present who had 50 batted ball events in a season. I’ll start with ISO since the results are cleaner.

ISO vs HardHit% and Bat Path

First, here is a simple table of average ISO and for certain Hard Hit% and Bat Path. I tried to limit the number of empty values here.

To no one’s surprise, the higher and hard a ball is hit, the hitter’s ISO get higher

The deal is that on the right side of the table a change is starting to occur. For the weak hitters, their ISO has peaked and is heading down.

The change isn’t 100% clear, looks to start around 22 degrees.

Looking at the information another way, here is the average ISO grouped just by the Swing Path.

The ISO values peak around 20 degrees and then start declining. The key swing path for power seems to be around 20 degrees

BABIP vs HardHit% and Bat Path

Power isn’t the only factor to take into account So to start out again, here are the average BABIPs for a certain HardHit% and Bat Path.

The image is not as clean as the ISO one, but there is a range of high BABIP under 15-degrees Bat Path and over 15% Hard Hit%

Again, here is a look at the limited results from an upper cut bat path.

Again, not the prettiest image, but all the extremely low BABIP values fall in this range.

And finally, one last graph to show the average BABIP at different bat paths

While there is some curvature to the BABIP graph, it’s flatter from -5 to 20 degrees.

Conclusions

From the graphs and tables, the key to being productive is to hit the ball as hard as possible (duh) with a swing plane of 20 degrees. To get to elite levels, the Hard Hit% needs to be over 20%

Going back to Albies, here are his Hard Hit% rates and Swing Paths over the years.

The change in Swing Path obviously occurred between the 2019 and 2020 seasons. The change wasn’t as obvious since his Hard Hit% was in the low teens. When that rate dropped to 6% this season, all his results tanked. Albies swing path is fine as long as he’s hitting the ball hard.

Besides Albies, here are some other hitters with a Swing Path over 22 degrees but a sub-15% Hard Hit%.

I’ve had a hard time figuring out Dean Kremer and couldn’t explain his low 2.48 ERA while most of his ERA estimators are in the high 4.00s. I finally got around to looking at his splits with the bases empty and those with runners on base. With the bases empty, Kremer has a .391 BABIP. Once someone gets on base, he has a .167 BABIP. Since he has a .310 overall BABIP, the discrepancy wasn’t obvious. I decided to look into the predictability of BABIP with and without runners and with BABIP-related issues and how much a difference can help predict an ERA regression.

To do the study, I look at starters (>90% games where starts) who at least threw 80 IP in season one and at least 40 IP in the next to help account for survivor bias. Just a reminder that previous studies found it takes forever for a pitcher’s normal BABIP to stabilize (2000 BIP, ~ 4 seasons of 180 IP). Read the rest of this entry »

Over the last two seasons, several highly-touted rookies have struggled with the jump to the majors like Jo Adell, Jarred Kelenic, Joey Bart, and Josh Lowe. I examined strikeout and shift numbers. Also, I wanted to find the major league replacement level OPS where hitters get demoted this season. Usually, it’s just under .650 but I was wondering if it has changed.

I’m not going to put a story around each study. Examples of hitters struggling with the jump to the majors are everywhere. I just want the facts when those stories pop up in the future. Read the rest of this entry »