Danny Santana Is More Interesting Than You Think

The 2019 season was a respectable, if not particularly remarkable year for the Texas Rangers. Following a 95-loss campaign that cost manager Jeff Banister his job, the Rangers bounced back to a 78-84 record, nowhere close to a wild card berth but nonetheless good for third place in a loaded AL West. On the whole, it’s not a stretch to say it was a successful season in Arlington — 78 wins is an impressive total for a team that lost its two best hitters in July and had exactly two non-replacement-level starting pitchers.

That doesn’t necessarily mean they were fun or interesting. Outside of Lance Lynn and Mike Minor possibly breaking WAR, the most curious thing about the 2019 Rangers may have been the truly out-of-the-blue breakout of Danny Santana. In a nutshell, after a 4-WAR debut in 2014 bolstered by a .405 BABIP, Santana appeared to be an afterthought unlikely to return to being a big-league contributor, checking in at well below replacement level over the subsequent four seasons split between Minnesota and Atlanta. Santana signed a minor league deal with Texas this past January, rewarding them with a 28 HR/21 SB season, slugging .524, and posting a 111 wRC+ across 511 plate appearances, all while playing every position on the diamond past the pitcher’s mound. Quite the turnaround!

Then again, one can’t be blamed for not paying much attention to what Jay Jaffe called “one of [2019’s] most unlikely breakouts.” In the year of the juiced ball, a light-hitting utility guy more than doubling his career home run production wasn’t as newsworthy as it ordinarily would be. Besides, most observers appear inclined to believe that 2019 was more flash in the pan than an All-Star leap. Jaffe concluded that “ability to hit pitchers of both hands will keep him relevant on a daily basis,” while remaining skeptical that another 28-homer performance or .352 wOBA output is in the cards. “A high BABIP paired with a high strikeout rate and a sudden burst of power screams regression,” Jake Mailhot recently opined. Even Rangers blogs are less than sold on his place on the team going forward. Read the rest of this entry »


Who Is Yoshitomo Tsutsugo?

Image result for 筒香 嘉智

Last month, the Tampa Bay Rays signed Japanese slugger Yoshitomo Tsutsugo (筒香 嘉智) to a two-year contract for $12 million. If you add the $2.4 million posting fee paid to the Yokohama Baystars, Tsutsugo’s team in the Japanese League, that would make the Rays’ investment at $14.4 million total for two seasons. The 28-year-old left fielder has been expressing his ambition to play in the majors for years, and he finally found the team to play for. Now the question is who this guy is and how he will fit.

Background

Tsutsugo has been one of the top prospects of Japanese baseball since his younger days. He was one of only two freshmen to hit cleanup in his high school team’s history. In his sophomore year, Tsutsugo led his team to the semifinal in Koshien, the biggest high school baseball tournament in Japan, with a .526 batting average, three home runs, and 14 RBIs in three games. It gained him enough attention to play on his country’s national team. In 2009, Tsutsugo was drafted by the Baystars as the first pick in the Nippon Professional Baseball (NPB) League.

Tsutsugo struggled in Japan until 2014. He struck out too much, and frequent injuries prevented him from playing full-time. Until 2014, he only had one season with more than 100 games played (NPB plays 144 per season). However, Tsutsugo started filling up his minimum at-bats, and his OPS has been over .900 every year since. The peak was 2016, when he hit 44 home runs in 133 games with an OPS of 1.110. He also played for Japan in the 2017 World Baseball Classic as the cleanup hitter and proved his power with three home runs and a .680 SLG in seven games. Throughout his nine-year career in Japan, Tsutsugo hit .285/.382/.528, good for a .910 OPS. The average OPS during that time was around .680 to .720. Yokohama’s superstar was truly one of the league’s elite power hitters. Read the rest of this entry »


Mariners Reveal Their Risk-Loving Nature with Evan White Contract

Do you like to gamble? The Seattle Mariners do. A lot. In fact, Seattle has chosen to introduce substantial risk into its relationship with Evan White this offseason, with little additional expected return. Given all of the action so far this offseason, you could be forgiven for paying little attention to this particular transaction back in November. But it’s an unusual type of deal that some analysts believe could become more common in future years, and it raises some thorny questions about financial risk management.

When I first read reports that some players were criticizing White — a 23-year-old first-base prospect who has never played above Double-A — for signing a long-term contract with the M’s, I was a little taken aback. My initial reaction to the deal had been the opposite: I couldn’t understand why the Mariners would lock themselves into paying a minimum of $24 million to a player who had never taken an at-bat in Triple-A, much less the majors, and who they would have had team control over through at least his age-29 or age-30 season (depending on when they call him up) in the absence of any long-term contract. If the Mariners simply played it year-by-year with White and he ends up being an above-average major leaguer — or even a star — they could expect to pay him somewhere in the range of $24 million through his six years of pre-arbitration and arbitration years. And if White ends up being a complete or near-complete bust (as is quite possible), the Mariners could have cut him loose while paying him a negligible sum.

And from White’s perspective, if he takes a cold, hard look at the numbers, the probability of him making less than $24 million in his career absent this contract is quite high. Some research indicates that the bust rate for hitters ranked in the bottom half of top 100 prospects and assigned an OFP of 55 on the scouting scale (as Baseball Prospectus did this offseason) is as high as 30-40%. If I’m Evan White, and I assess that there is a greater than, say, 1-in-4 chance that I end up making no more money in my baseball career, you don’t have to ask me twice to sign a contract that guarantees me somewhere between $24 and $55 million. I’m popping the champagne that night and paying for all of my friends to join me on a celebratory trip to Vegas. Read the rest of this entry »


Fixing Zack Wheeler’s Fastball Mix

Although he may not have been one of truly few elite free agents on the market, Zack Wheeler was a very big signing for Philadelphia, agreeing to a five-year contract worth $118 million. Over the past two years, Wheeler’s amassed an fWAR of 8.9 in 377.2 innings while posting above-average strikeout and walk rates. Additionally, his underlying metrics have also been strong over the past two seasons, and they don’t signal any drastic mean reversals in performance. Granted, there is obviously still risk here. Wheeler missed the 2015 season and the start of 2016 with a UCL tear, and he was shut down upon his return with a flexor strain. Furthermore, this past July he was shut down with shoulder fatigue, limiting the Mets’ ability to market him to potential suitors at the trade deadline.

One of the most interesting storylines in the game is player development. At the moment, the most analytically inclined teams are thriving at meshing the data with coaching, and the gap is only growing. These teams are creating new players. This is particularly important when signing free agents given the current contract negotiation dynamics. The teams and players have access to most of the same information, with the $/WAR metric playing a central role in future valuations, and if you can “create” a new player who beats the projections, you’re generating additional value for your club.

In terms of Wheeler, I think I have a bit of a theory on how to generate that marginal value through a tweak in his approach. The biggest change in Wheeler’s approach between 2018 and 2019 was in his usage of his fastballs and his changeup. In 2018, the righty threw his four-seam fastball almost three times as frequently as his two-seamer, and his changeup was almost almost non-existent. (Disclaimer: I believe that there may be an error in Statcasts’ classification of Wheeler’s splitter and changeup — they may actually be the same pitch). Read the rest of this entry »


An Interesting Bias in xWOBA

I’d like to highlight a bias within xWOBA that could possibly be accounted for to improve the metric. In my view, however, the more interesting takeaway is the “why” behind what is happening and how this might be used from both a player evaluation and player development perspective.

The bias in xWOBA is found in the amount of backspin on hit balls. For spin, I created an expected distance model based on Exit Velocity (EV), Launch Angle (LA), and Horizontal Hit Direction or Spray Angle. This model has been helpful in assessing whether players should hit with backspin (article here) as well as changes to the ball and the amount of drag (article and model here). Alan Nathan and Tom Tango have pointed out that very-high-spin balls actually have increased drag and less distance. However, what happens at the high end of the spin spectrum does not interfere with the low end; thus, the general conclusions that follow would appear to remain valid. Additionally, while knowing actual spin values might help confirm the findings, it’s not just the spin rpms that are relevant, as the spin type (based on the spin axis) must also be considered. Rolling all this information up into an overall player average for a comprehensive cost/benefit analysis will likely prove challenging as spin axis values don’t average well.

The general takeaway from the research on whether players should hit with backspin is that backspin balls outperform expectations but the players that hit backspin balls more often actually underperform. That may seem a little counterintuitive at first; however, this relationship is clearly visible in the xWOBA player averages based on the data: Read the rest of this entry »


Using Objective Feedback to Drive Hitting Programming and Evaluate Progress at LSU Shreveport

The Louisiana State University Shreveport Pilots are an NAIA team in Shreveport, Louisiana competing in the Red River Athletic Conference. This article was written by Brent Lavallee and David Howell. Brent Lavallee is the Head Coach of the Pilots and David Howell is the Director of Player Development, Director of R&D, and Assistant Pitching Coach.

Introduction

With the rise of affordable bat sensors, we no longer have to rely on only the eye test when it comes to evaluating swings. Gone are the days of attempting to evaluate a hitter’s progress based on the small sample of fall games, or how well they seem to be hitting flips at the end of the season. Even the days of measuring exit velocity during tee work with a radar gun are comparatively basic with what can be accomplished with a sub-$200 Bluetooth sensor.

Blast sensor attached to the knob of a bat.

At LSU Shreveport, we started using Blast Motion sensors this fall, which are placed on the knob of a bat and measure metrics such as bat speed, attack angle, rotational acceleration, and more. The sensors work by taking into account the characteristics of a bat (length, weight, etc.) and derive swing metrics when hitters make contact. Read the rest of this entry »


Spin Trends by Pitching Staff

With the 2019 season firmly in the books and the expanded offering of spin-related pitching data now readily available across the internet, I decided it was time to take a hard look at every team’s pitching staff. The hope in doing so was to identify a trend, if any, within the spin metrics of the best clubs. Do any staffs have a noticeable tendency to use pitchers with a specific spin profile?

To answer this, I pulled together every pitcher and their average spin metrics for each pitch type that they threw a qualified amount of times (30-plus in most cases) in 2019. This meant ignoring splitters because of sample size considerations. I was also tempted to use Bauer Units — a proxy for spin rate divided by velocity, as well as a nod to Trevor Bauer — to control for velocity in this study, but I decided to keep this post more straightforward. The study instead uses raw spin rate, horizontal and vertical movement, and spin efficiency as reported by Baseball Savant. I then aggregated the players’ data by the team they finished the season with to create an average spin profile for every team. This team profile weighs all of their qualified pitchers equally.

Once I was able to establish what the normal team looks like across those categories, I wanted to identify any clear outliers to possibly show where organizations consciously emphasized certain metrics. To do that, I produced league rankings and standard deviations for each category based on the team averages. Read the rest of this entry »


2019 MVP Winners as Voted by Dead Sportwriters

“Alex Bregman is the runaway AL MVP for 2019” – MVP voters from the 1950s & 1960s

“Mike Trout finishes a disappointing 5th in 2019 AL MVP voting” – MVP voters from the 1960s & 1970s

“Christian Yelich is the near-unanimous 2019 NL MVP” – MVP voters from the 1980s & 1990s

“Xander Bogaerts narrowly misses the 2019 AL MVP” – MVP voters from the 1960s & 1970s

The Evolving MVP Voter’s Criteria

The winner of the MLB MVP awards is a function of two factors: How the players performed, and how the electorate evaluated that performance.

Much attention is paid to how players perform and how they stack up historically to peers from different eras, but for MVP selection, little attention has been paid to how the electorate has changed and shifted the definition of the Most Valuable Player.

Since 1931, the Baseball Writers Association of America (BBWAA) has voted and awarded each league’s MVP award. Over this period of time, the world’s understanding of player performance and what contributes to winning has changed dramatically. The 1931 voters probably looked at home runs, RBIs, and batting average leaderboards printed at year-end in their daily newspaper before filling out their ballot. That’s not to accuse them of being narrowly minded, it was just all they had available to them and all the baseball world knew to look at.

On the other hand, the 2019 voter (hopefully) spent at least a few minutes on FanGraphs or a similar site looking at things like WAR, wRC+, and DRS, and at best also considered advanced Statcast data and maybe even built their own AI-powered simulations to model a season without the player to see how much worse their team performed. At least, that’s what I would do if I had a ballot, and that’s what I would call “responsible voting” in 2019. Read the rest of this entry »


The Brief But Brilliant Pitcher

With the regular season over, my routine Baseball-Reference wanderings brought me to the JAWS rankings for pitchers. I had been tracking a handful of current players throughout the year and I wanted to see where they’d finished up. Before getting very far, however, I was quickly reminded that there’s a lot to be desired when it comes to pitcher recognition in the Hall of Fame. Why is it that owners of some of the best pitching seasons of the twentieth century have been left out of the Hall of Fame? Surely there is a level of brilliance that eclipses brevity and manages to leave an indelible mark in baseball history.

Sandy Koufax is a prime example of this. He had just six seasons of 100-plus innings where he had an ERA+ over 106, accumulating 48.9 career WAR and 46.0 peak WAR for a JAWS score of 47.4, far short of the Hall of Fame averages of 73.2/49.9/61.5 for starting pitchers. In a vacuum, one could view his JAWS numbers and dismiss his career as good but not worth of the Hall of Fame. But we don’t live in a vacuum. Despite falling short across the JAWS board, Mr. Koufax was nevertheless inducted in his first year of eligibility by appearing on a healthy 86.9% of ballots due to the fact that his final four years were the greatest final four years by a pitcher in baseball history. In terms of WAR, they each rank among the top 220 pitching seasons since 1920, with his 1963 and ’66 seasons ranking 13th and 22nd best of all time, respectively. Averaging 24 wins, eight shutouts, 298 innings, 307 strikeouts, and 9.1 WAR, these seasons have come to define the era. The 1972 baseball writers understood that his brilliance outshone his brevity when they voted him in.

However, while Koufax may be the archetype of the brilliant but brief ace, he was an outlier only in terms of how his meteoric career was recognized by Hall of Fame voters. When sampling the 250 greatest pitching seasons by WAR since 1920, did you know that only 43% of them belong to Hall of Famers? As a basis of comparison, 61% of the 250 greatest position players’ seasons by WAR since 1920 belong to Hall of Famers. These differences become even more stark as we narrow down to the 100, 50, 25, and 10 greatest seasons and exclude not-yet-eligible players, players connected to steroid allegations, or players banned from the game (Pete Rose). Read the rest of this entry »


The Effects of Repeating Pitches on Pitcher Success Rate

It’s the bottom of the sixth inning at Minute Maid Park. Down 3-2 in the series and facing elimination, the Yankees are trailing the Astros, 4-2, in Game 6 of the 2019 American League Championship Series. Facing Yordan Alvarez with two out and nobody on, Tommy Kahnle needs to keep the game within reach to give his offense a shot at coming back. After falling behind 2-0 to Alvarez, Kahnle comes back and gets a strike looking on a changeup up in the zone. On 2-1, Kahnle throws a changeup below the zone and gets Alvarez to swing through it for strike two.

After getting a swinging strike and with the count now at 2-2, what does Kahnle do to try to get Alvarez out? Does he attempt to repeat the previous pitch after successfully inducing a swinging strike, or does he throw a different pitch in anticipation that Alvarez is expecting the same pitch? Kahnle repeated the changeup below the zone and got Alvarez swinging on strikes to keep the Yankees within two runs.

Pitch sequences like these are very intriguing because of the variety of factors that affect the at-bat, such as the pitcher and hitter’s game plans, game situations, and recent performance. It is a big reason organizations carefully study pitch sequencing. I wanted to quantify and analyze the effectiveness of situations like Kahnle’s against Alvarez. That is, I wanted to determine the most effective two-strike strategy for the pitcher after the batter swung and missed on the previous pitch. Organizations can then share these findings with their pitchers so that they have better success as a staff. Read the rest of this entry »