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 »

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 »

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.

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 »

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 »

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 »

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 »

Last month at The Athletic, Patrick Mooney and Sahadev Sharma took a deep dive into the Cubs’ successes and failures from 2015 through the conclusion of 2019. This led me to reflect upon this five-year run and try to figure out if, on the whole, it should be considered a success. They famously broke the franchise’s 112-year World Series drought, yet this Cubs team has seemed to leave baseball fans (especially Cubs fans) wanting more. When they took the league by storm in 2015 to the tune of 97 wins (a meteoric 24-win increase from the previous season), the baseball community was not asking if this group would win a World Series, but when. After the 2016 championship, we spent all offseason dreaming about how many World Series this group could claim over the next five years.

Of course, this Cubs group has yet to win another ring. Joe Maddon has left. Trade rumors have been swarming around the likes of Kris Bryant and Kyle Schwarber following reports of the Ricketts wanting to cut payroll. How do the Cubs pivot after this lost season? How much longer does Theo Epstein have to turn this ship around? These are the existential questions being asked in and around Wrigleyville after this season’s second-half collapse.

However, I would argue these questions are not totally fair. This Cubs core of Bryant, Anthony Rizzo, Javier Baez, and Jon Lester has led the team to post one of the best five-year runs in the National League since the inception of the Wild Card in 1994. The Cubs were swept in the NLCS in 2015 at the hands of the Mets, won the World Series in 2016, lost the NLCS in five games to the Dodgers in 2017, lost in the wild card game to the Rockies in 2018, and missed the playoffs this year. Those regular seasons, in order, consisted of 97, 103, 92, 95, and just 84 wins this past season. Simply looking at the playoff and regular season results, this does not feel like a completely dominant stretch of baseball. Read the rest of this entry »

Each play in the playoffs holds extra weight compared to the regular season. An error can change a game, and a loss can doom a series. In close games and series, it is often the team that executes the small plays that comes out on top.

A particular play in Game 2 of the NLDS between Washington and Los Angeles stood out in this context: Asdrúbal Cabrera singled to right field, driving in Ryan Zimmerman. However, the throw from the outfield held up Kurt Suzuki at third base, and Cabrera was thrown out trying to advance to second base on the throw. Although the Nationals still won the game, the baserunning error was not inconsequential in the series.

Evaluating the Result with WE and RE24

Two statistics – Win Expectancy and RE24 – can be used to show why trying to advance was a bad decision.

Win expectancy (WE) is the probability a team will win given the specific circumstances. Greg Stoll’s Win Expectancy Calculator [1] shows how potential baserunning outcomes by Cabrera change Washington’s win expectancy in Table 1 below.

The Nationals’ win expectancy before Cabrera’s single was 82.7%. The highest WE is 93.4% and results when Cabrera gets to second base, however, staying at first only decreases Washington’s win expectancy by 0.9%. In comparison, getting thrown out decreases their chances by 6.7% compared to staying at first. A 0.9% increase in WE is probably not worth risking 6.7%, especially in a playoff game where you have the lead. Read the rest of this entry »

I love good defense. Watching a center fielder chase down what should have been a blooped-in single, instead creating a shocked reaction from the baserunner as he turns and realizes he’s out is priceless. That classic, one hand in the dirt, rest of the shortstop’s body flying through the air snag, is truly my favorite. I know what people say about the excitement of a home run and I get it. The rifle-like, cracking sound of bat on ball, closely followed by fans standing and cheering and spilling and spitting! God, I’m going to miss baseball this winter!

As the season comes to a close, we celebrate more than just home runs. We celebrate and award players for all their actions on and off the field. With that, it’s nearly time to award the best defensive players of the year with the Rawlings Gold Glove Award. There’s nothing like having a gold glover on your team and being able to watch them hold it down in the field all season long.

​Like many awards, managers and team coaches get to vote on the Gold Glove. Managers can’t vote for players on their own team and they have to stay in their own league. In addition, they have to vote for players who qualify (mostly needing at least 713 total innings) as laid out by Rawlings. It’s nice to have the men who are closest to the game voting and giving out these awards, but there must also be some quantifiable way to determine who is deserving. According to Rawlings, 25% of the vote is left up to metrics. Using the SABR Defensive Index, advanced analytics are now built into the award. This index includes:

– Defensive runs saved (DRS)
– Ultimate Zone Rating (UZR)
– Runs Effectively Defended
– Defensive Regression Analysis
– Total Zone Rating Read the rest of this entry »

When your favorite baseball team misses out on the playoffs, October offers a brief free-agency in fandom. Do you temporarily switch to root for a loved one’s team, or choose to root against a rival?

For me personally, I want former Rockies players to do well. It would be fantastic to see DJ LeMahieu lift the Commissioner’s Trophy, even if he’s now wearing the wrong color of pinstripes.

But do I really have to root for the Yankees? I wanted to see if I had any other option — to see if there was any other playoff team with more former Rockies.

I started with FanGraphs data showing player totals from every season going back to 2001 (CC Sabathia is the player on a 2019 playoff roster with the earliest debut, having come on April 8, 2001 for Cleveland). I also defined “playoff roster” as only including players who made an appearance for a playoff-bound team in September of 2019, so if someone hasn’t seen the field in the last month, they’re not counted here.

I didn’t want a player with only 15 ABs to have the same weight as a player with 1,000 at-bats, so I used each player’s “appearances” for their former clubs (plate appearances as a batter plus total batters faced for pitchers, including both regular season and playoffs). Read the rest of this entry »