Category: Baseball

  • Why Paul DeJong Belongs Among MLBs Elite Shortstops

    The following is an article that appears in The Fielding BibleVolume V. You can purchase the book at ACTASports, Amazon, or wherever books are sold.

    By Mark Simon

    Paul DeJong of the Cardinals tied for the MLB lead among shortstops with 26 Defensive Runs Saved last season.

    That is a stat that should surprise you. Javier Baez dazzles regularly on highlight reels. Nick Ahmed has won two straight NL Gold Gloves. Trevor Story is one of a few heralded as the game’s standouts.

    Most Defensive Runs Saved—Shortstops (2019)
    Player DRS
    Paul DeJong 26
    Javier Baez 26
    Nick Ahmed 17
    Trevor Story 14

    DeJong on the other hand is rather ordinary. He finished 10th among shortstops in our Scouts Defensive Rating system, which essentially serves as a proxy for the eye test. He ranked last among shortstops in Good Fielding Plays per 1,000 innings (in other words, he didn’t have a lot of Web Gems). There is nothing in watching DeJong that would make you think he was the DRS leader at shortstop in 2019.

    But what DeJong did was play and he played well. He started 156 games at shortstop. He led all shortstops in putouts, was one shy of the lead in assists, and turned 29 more double plays than anyone else at the position (the widest gap between the leader and No. 2 since 1982).

    DeJong was a product of both opportunity and of being good. In particular, DeJong rated highly on balls hit to his left (in other words, usually up the middle). He had a knack for the play in which he quickly shuffled left and fielded the ball behind second base, occasionally diving, but usually just having good anticipatory instincts and a quick first step.

    Those balls didn’t get past Cardinals infielders. They converted 62% of groundballs hit past the mound and within 10 feet to the left or right of second base into outs, the second-highest rate in the majors.

    DeJong converted 173 of 265 balls hit to his left in which he had a greater than 0% chance of making a play, a 65% out rate. Baez had a 67% rate. However, there are two things to keep in mind.

    1) The expected out rate on DeJong’s balls was 57%. The expected out rate for Baez was 65%. In other words, the balls up the middle against DeJong had a higher degree of difficulty.

    2) DeJong had 72 more opportunities on those balls, thus giving him more opportunities to be above average at making plays.

    And DeJong’s 65% out rate on balls hit to his left was much better than Story (60%) and Ahmed (53%).

    Plays Made Above Expectations
    Player To His Right Straight On To His Left
    DeJong 11 2 22
    Baez 12 6 8
    Story 5 3 7
    Ahmed 18 5 -3

    DeJong did this without sacrificing balls hit either to his right or those hit within his immediate vicinity. DeJong was 13 plays above average on those balls, which was better than Story. It wasn’t as good as Baez or Ahmed, but the gap between them wasn’t as large as the gap between the DeJong and everyone else on balls hit up the middle.

    Want to look at this another way? Here’s a look at how often the top shortstops get an out on balls with a 25 to 75% out probability. This encompasses a wide swath of types of plays: from the challenging, but not impossible, to the routine, but not easy.

     Individual Out Rate on Batted Balls – With Out Probability Between 25% and 75%
    Player Actual

    Out Rate

    Expected

    Out Rate

    DeJong 66% 51%
    Baez 66% 53%
    Story 62% 52%
    Ahmed 56% 50%

    DeJong excelled because he fulfilled the bottom line. He got outs when he was supposed to get outs and got outs when he wasn’t supposed to get outs. The damage done on balls hit near him was minimal, more so than anyone at the position, similar to his teammate, two-time Fielding Bible Award-winning second baseman Kolten Wong.

    Did this make DeJong one of the best defensive shortstops in baseball in 2019? That’s a question without a right answer. It’s a matter of opinion. There is a good case to be made for many. But if we stick to the facts, we can tell you that DeJong (and Baez) saved more runs than any other shortstop in the majors last season. It may be surprising, but it’s what the data shows.

  • Notable Updates to Defensive Runs Saved

    By Brian Reiff

    Prior to the 2020 MLB season, Sports Info Solutions (SIS) announced major upgrades to its flagship defensive metric, Defensive Runs Saved (DRS). These upgrades centered around the incorporation of infielder starting positions in the calculations and the improvements that were consequently able to be made.

    Knowing where infielders started on the play allows us to separate out their Positioning from their other contributions on a play, namely their Range and their Throwing. Therefore, the new system is called the PART System, which stands for Positioning, Air balls, Range and Throwing.

    The PART System has replaced the Range and Positioning System (formerly known as the Plus/Minus System) as the primary component of DRS for infielders for all seasons since 2013. (Outfielders will continue to be evaluated using the Range and Positioning System.) This article focuses specifically on this new component, although further explanations and descriptions for the others can be found in the original DRS Glossary entry on FanGraphs or at FieldingBible.com.

    The PART System

    At its core, the PART System’s goal is to split a fielder’s contributions into its individual components. This differs from its predecessor, which calculated and reported a fielder’s positioning, range and throwing contributions as a single number.

    One of the primary reasons for the development of this new system was the massive increase in shift usage in recent years, since DRS had not included shift plays in its analysis of players before this update. In 2010, less than 2% of all balls in play featured a shift being employed by the fielding team, per SIS charting. In 2019, that number was over 40%.

    In 2012, SIS realized that this increase in shifts was skewing individual player numbers—the example cited was Brett Lawrie, a third baseman who was often stationed in short right field when the team shifted its fielders. Because of this, he was making plays in “zones” that no other third baseman could and receiving tremendous amounts of credit as a result. At the time, the solution was to eliminate these shift plays from consideration when evaluating a fielder’s contributions, and instead calculate Shift Runs Saved at the team level. In an era where shifting was still a rarity, this decision made sense, but now that teams are shifting on nearly half of all balls in play (and showing no signs of slowing down), a different approach has become necessary to continue accurately and completely evaluating players.

    This new approach is the PART System. Rather than exclude plays where fielders are lined up dramatically differently from a traditional alignment, the PART System is able to handle these plays by incorporating the fielder’s starting position into the calculation of his Runs Saved on the play. Thus, what was becoming a large gap in individual player defensive evaluation has effectively been filled, all the while opening the door for greater and more in-depth analysis.

    Positioning and Shifts

    The PART System utilizes the starting positioning data collected by SIS to separate a fielder’s positioning from everything else they do on the play.

    The primary benefit of this is that players can be credited for what they can actually control. Positioning has been effectively removed from a player’s DRS total on the premise that teams now control where a player is standing more than the player does. Whatever credit the fielder may receive or lose on a play is based on where they were standing when the ball was hit, rather than simply assuming they were standing in a traditional starting location.

    Positioning, while removed from players’ DRS totals, is still aggregated and accounted for on the team level. Each team is now credited with a certain number of Infield Positioning Runs Saved, which is composed of the team’s positioning on both shifted and unshifted plays.

    Speaking of shifts—until this update, SIS had not included plays where the defense was shifted in its evaluation of individual fielders. This was because, in shifts, fielders could be positioned in vastly different locations than they would be in a standard alignment and therefore receive large amounts of undue credit for making plays that no other player at the position even had a chance of making.

    Fortunately, this is no longer a concern with the introduction of the PART System. No plays are excluded from the calculation, and, because the players’ positioning is used to determine the amount of credit they receive, “The Lawrie Problem” is a non-issue. If the ball is hit at or near the fielder, they will receive a lower amount of credit than if it is hit far away, regardless of where they were standing at the time of the pitch.

    Despite the inclusion of plays classified as shifts in player evaluation, SIS continues to estimate the number of runs each team is saving using the shift. In fact, the new calculation more accurately measures how many runs were saved by shifts independent of the quality of fielders who were in the field at the time. The new Shift Runs Saved, which is a subset of Infield Positioning Runs Saved, only takes into account the team’s positioning on shifts, as opposed to the previous version of Shift Runs Saved that could not make a distinction between the team’s positioning and the fielders’ out-converting abilities.

    Air-Range-Throwing Breakdown

    So far, Positioning is the only component of PART that has been discussed. The other components—Air, Range and Throwing—are what actually comprise each player’s ART Runs Saved total, the component that is replacing the former Range & Positioning Runs Saved in the new version of DRS.

    Range is perhaps the most intuitive of the three, although there is still some clarification needed. In this system, range represents a fielder’s ability to reach a batted ball in an efficient and timely manner. If a fielder reaches a ball that no one else would’ve, they will receive positive range credit. However, if they fail to reach a ball, or take longer than expected to reach it, they will receive negative range credit. It’s also worth specifying that, because of the way SIS data is collected, range is only concerned about when or if the fielder touches the ball, not whether they field it cleanly.

    Everything that happens after the fielder touches the ball is considered part of the Throwing sub-component, which, obviously, means that the name is vastly oversimplified.

    This means that on a given play, a fielder might receive Throwing credit despite not throwing the ball at all, a typical example being a fielder who steps on a base for a putout. It also means that, when a throw actually is made, this sub-component measures the fielder’s ability to field the ball cleanly, plant their feet (or not) and fire a ball quickly and accurately to whomever is receiving the ball. Ideally, each of those would be measured individually sometime in the future.

    Last, and probably least, is Air. As of this writing, SIS only collects infielder starting positioning data on all groundballs and short line drives (GSL). Therefore, the PRT sub-component splits only apply on those types of balls in play, which, in fairness, make up approximately 80% of all balls fielded by infielders. On the other ~20% of non-bunt balls in play fielded by infielders—composed essentially of bloops and popups—any credit or debit a fielder earns on a play will apply toward their Air Runs Saved. Because SIS does not record infielder starting positioning on these plays, non-GSL plays in which the defense is shifted will continue to be excluded from a player’s DRS total.

    When combined, a player’s Air, Range and Throwing runs saved will comprise their ART Runs Saved.

    Each sub-component is reported separately over at FieldingBible.com to allow for the comparison of individual skills and attributes of various players.

    Directional Ability

    Another upgrade comes in the form of evaluating a player’s ability by direction. Because a player’s starting positioning was not known in the previous system, this could only be done in terms of where a fielder was traditionally positioned. For example, a third baseman could be judged on plays down the line, in the hole, or straight on, but on a ball considered “straight on”, there’s no guarantee that it was actually hit at them. If the fielder was positioned close to the line, the ball would have been to their left; if they were positioned in the hole, it would have been to their right. While the breakdown was useful, especially in understanding how fielders were positioned, it did not accurately reflect a player’s ability to field balls in particular directions.

    That is no longer the case thanks to the starting positioning data. Knowing where the ball traveled in relation to where the fielder started the play allows for evaluation of a fielder based on what direction they had to move to field the ball.

    For each of the three directional groups, a fielder is compared against others at their position in terms of both Plays Above Average and Runs Above Average (or Runs Saved). Again, these numbers are reported at FieldingBible.com for those who wish to view them.

    Evaluation of Multiple Fielders on a Play

    Knowing where each fielder started on a play allows for an additional benefit: the evaluation of multiple fielders on a play. Under the Range and Positioning System, and by most if not all other public defensive metrics, if a team successfully records an out on a play, the fielder who recorded the assist or putout is given credit and every other player on the field receives nothing. Usually, this is a fair thing to do. Most plays will only feature one relevant fielder who should be credited or debited. But what about the cases where that’s not appropriate?

    Consider a ball that is hit in the third base-shortstop hole, directly between the two fielders. The third baseman, who was positioned shallower than the shortstop, goes for the ball, but it gets by him. Behind him, the shortstop fields the ball and throws it to first for the out.

    In any other defensive system, the shortstop would get credit for making the play, and that would be that. But why should that be it? We know the third baseman had a chance of making the out himself—in fact, we know exactly how likely he was to make the out. If there was an inferior shortstop behind him, the ball might have made it to the outfield, or the shortstop might not have gotten the throw to first base in time. The third baseman’s credit on the play is determined by something completely out of his control—the quality of his teammate.

    The PART System offers a solution to this. By knowing where each player started on the field, it can assess multiple fielders on the same play under the assumption that fielders who are positioned shallower (closer to home plate) are able to act on the ball before fielders who are positioned deeper (further away from home plate). In this example, not only would the shortstop be given credit, but the third baseman would also be debited for having failed to make the play himself.

    Right now, this assessment of multiple fielders is only utilized on plays where the defense is shifted, although that may be changed in the future. This was done to keep players’ unshifted DRS as similar as possible to how it was being reported previously (at least methodologically—obviously, excluding positioning from DRS is still a major change). On plays where the defense is not shifted, fielders are less likely to be standing close to each other anyway, so it’s unlikely that a play would occur where two or more fielders both have a non-insignificant chance of making an out and therefore unlikely to matter as much. That said, this is an area that SIS expects to research heavily in the coming months as more upgrades are made to the PART System, especially as it pertains to fielders deferring to their teammates on balls either of them could field.

    How the Numbers are Changing

    Understanding how the PART System differs in its evaluation of players from the Range & Positioning System is difficult. To show how two systems relate, let’s use Javier Baez as an example.

    Using the Range & Positioning System, Baez saved 15 runs in 2019, good for third among shortstops. Using the PART System, he saved 26 runs, tied for first among shortstops. So where did those 11 runs come from?

    To keep things as simple as possible, instead of looking at total DRS—which includes things like Double Play Runs Saved and Good Fielding Play Runs Saved, for example—just Baez’s Range & Positioning Runs Saved and PART Runs Saved will be looked at. In 2019, Baez saved 8 and 19 runs, respectively, by those components of DRS. The 11-run difference is still there. That’s important to note—this singular component of DRS is the only component that’s changing. All the other components are staying the same.

    But anyway, the 11-run difference: On plays where the Cubs didn’t use a shift in 2019, the Cubs’ positioning of Baez cost the team one run. That’s part of the difference—PART Runs Saved doesn’t count that against him, unlike the Range & Positioning System. Secondly, Baez saved 10 runs with his range and throwing on plays where the Cubs were shifted. Again, those plays weren’t included in his Range & Positioning Runs Saved total, but they are included in his PART Runs Saved total.

    Now to add the numbers back together. Baez is given back the one run his positioning cost the Cubs, since the PART System does not credit or debit fielders for their positioning. Starting from his eight Range & Positioning Runs Saved, that brings him to nine. Then, adding the 10 runs he saved when the Cubs were shifted brings him to 19 runs saved, the exact number that the PART Runs Saved System awarded him.

    To summarize:

    Range & Positioning Runs Saved – Non-Shift Positioning Runs Saved + Shift ART Runs Saved = PART Runs Saved

    Now, I’ll admit I cherry-picked this example and this will not work out as nicely as it did for Baez for every fielder. Because there were other small improvements and bug fixes made as part of this upgrade, this math won’t add up exactly for everyone. But it’s close. Using the above equation for every infielder (excluding pitchers and catchers) who played in 2019, the average of the absolute values of the differences between the left-hand and right-hand sides of the equations was 0.58 runs. So, if you’re confused about how a player’s PART value was determined, using that equation will get you almost entirely the way there.

    Here are the players who changed the most between the two systems in 2019:

    Player Pos Pre-2020 DRS Non-Shift Pos RS Shift ART RS PART DRS Change
    Matt Chapman 3B 18 -10 9 34 16
    Paul DeJong SS 14 0 12 26 12
    Javier Baez SS 15 -1 10 26 11
    Miguel Rojas SS 12 3 -6 2 -10
    Nolan Arenado 3B 8 1 11 18 10

     

    Context

    The scale for evaluating players’ DRS hasn’t changed much with the update. The same tiers that had been used with DRS still applies to the new totals. As a reminder, those tiers are:

    Defensive Ability DRS
    Gold Glove Caliber +15
    Great +10
    Above Average +5
    Average  0
    Below Average -5
    Poor -10
    Awful -15

    Methodology

    While it may seem much more complex, in reality, the PART System is not that much more complex than the Range & Positioning System. Both rely on the Plus/Minus technique, where credit is given or taken away based on how difficult of a play it was for the fielder. For example, imagine a batted ball with a given velocity and spray angle. Past balls in play with similar characteristics were turned into an out 60% of the time. If the fielder ends up making the play, they would receive 0.4 plays worth of credit (1.0-0.6); if they don’t make the play, they would be debited 0.6 plays (0.0-0.6). In this way, fielders get credited more for making more difficult plays and credited less for making easy plays. An average fielder would then save a net of zero plays for the season.

    The difference with the PART System is that it uses the Plus/Minus technique for three different components: Positioning, Range and Throwing (as noted above, Air Runs Saved is an independent calculation). To do this, three different Out Rates must be calculated:

    A – The chance that the play will be made given only information about the batted ball (trajectory, location, and velocity) and the batter (speed)

    B – The chance that the play will be made given information about the batted ball (trajectory, location, and velocity), the batter (speed), and the initial positioning of the fielders relative to the ball in play

    C – The chance that the play will be made at the point that the fielder obtains the ball given the distance he has to throw and how long he has to complete the play before the batter/runner reaches safely

    Combined with this is a variable (here referred to as D) that is set to either 1 if the fielder made the play, or 0 if they did not. With those Out Rates in hand, determining how much credit to assign to each component is simple subtraction:

    Positioning= A – B

    Range = C – B

    Throwing = D – C

    An example may help to make things clearer. Take a groundball hit up the middle over the pitcher’s mound, just barely on the third base side of the field. The majority of shortstops wouldn’t make this play given where they would usually be standing, so Out Rate A is low, say 0.2.

    However, the shortstop in this instance was positioned well, and so they only have to move a few feet to field the ball. Given that it’s a relatively easy play when the fielder’s position was known, Out Rate B is reasonably high—let’s say 0.7. In other words, 70 percent of shortstops make this play when they’re standing where this one was in relation to where the ball was heading.

    This shortstop has particularly good instincts (we’ll call them Ambrelton Timmons) and they get to the ball quicker than an average shortstop would. Because of the extra time afforded to the shortstop to get the ball to first base, their expected out rate makes another jump—Out Rate C is then 0.9. And, predictably, the shortstop makes the out, so D is 1.0.

    On this play, here’s how the shortstop’s credit would break down:

    Positioning= 0.7 – 0.2 = 0.5

    Range = 0.9 – 0.7 = 0.2

    Throwing = 1.0 – 0.9 = 0.1

    Of course, those components are all still in the units of plays saved, and they still have to be converted to runs. But that right there is the essence of how the PART System works. Instead of receiving 0.8 plays’ worth of credit (1.0 – 0.2), the shortstop here would only receive 0.3 plays’ worth of credit (1.0 – 0.7), split between range and throwing. Of course, it’s actually slightly more complicated than that.

    One adjustment that needs to be made is for poorly positioned fielders on plays where the team was well positioned. The most common example of this is a play in which the team in the field is employing a shift—the second baseman moves over to short right field, and the shortstop moves over to the right-hand side of second base. On a ball hit to the shortstop, the second baseman would initially be determined to have been positioned poorly. While a traditionally positioned second baseman may have been able to make the play, the one in this example had no chance because of their positioning in shallow right field. However, the ball was hit straight to the shortstop, so the team was still positioned well.

    To account for this, adjustments are made such that no fielder can receive negative positioning credit when their team is positioned well, and no fielder can receive positive positioning credit when their team is positioned poorly.

    The other primary adjustment, at least on shift plays, arises from the fact that multiple fielders are assessed on each play. When a ball is fielded by a shallower fielder, the deeper fielder’s range obviously should not be penalized, as it was impossible to know if he would have made the play or not. So, on shift plays, any fielder who was positioned deeper than the one who first touched the ball will not receive any range credit or debit.

    Furthermore, the fielder that first touched the ball on these plays will “steal” the out rates from those behind them. This is done to prevent players from being over-credited when they make a play that would have otherwise been easy for the fielder behind them. For example, on a routine grounder to the shortstop, the third baseman decides to instead cut the ball off and make the play himself.

    The third baseman may have had a low chance of converting the out, but they would not receive credit as if it were a difficult play because it was not, at least for the team. Whatever the shortstop’s expectation of making the play was would be added to the third baseman’s, and the third baseman’s range credit would then be determined based off that new expected out rate. If the third baseman’s initial out rate was 0.05 and the shortstop’s was 0.90, the third baseman would be debited 0.95 plays’ worth of credit.

    Conclusion

    The PART System has replaced the Range & Positioning System in DRS going back to 2013, the first year for which SIS collected the infield starting position data. Going forward, SIS will continue to make improvements to the PART System and DRS as a whole as it continues to strive toward its goal of being at the forefront of defensive analytics.

    Most Important Takeaways
    Positioning is no longer factored into a player’s Defensive Runs Saved total

    This system allows for the evaluation of all infield plays, not just ones involving an unshifted defense

    Transition from evaluating: “How often did a player make that play?” to “How often did a player make that play given where they were positioned?” with the PART System

    The result is a more accurate overall depiction of defensive performance

     

    This article is adapted from The Fielding Bible – Volume V. For more information on this stat, check out FieldingBible.com

  • New podcast: Biomechanics and Analytics in College Baseball with Wake Forest’s Tom Walter

    LISTEN HERE

    On this edition of the Sports Info Solutions Baseball Podcast, Mark Simon (@MarkASimonSays) welcomes baseball back. Hooray!

    He’s then joined by Wake Forest (@WakeBaseball) baseball coach Tom Walter (@WaltWFU), who explains how the school’s state-of-the-art pitching lab came to be (2:18), how information gets translated from the language of a PhD to the language of baseball (5:44), the difference between performance science and analytics now versus when Coach Walter first began coaching (8:31), how the school applies the lab to studying hitters too (10:52), how his program uses shifting and how their shifts adjust based on count (12:06), future developments in performance science (15:03), expectations for this season (16:36), and what the team does in the local community (17:36).

  • Fielding Bible Volume V preview: The Twins defense

    By Mark Simon

    Marwin Gonzalez may have finished ninth in the 2019 Fielding Bible Multi-Position Award voting, but it would be hard to find a player more versatile than he is. Gonzalez started at least 10 games at each corner infield spot and each corner outfield spot. He did much more good than harm at those positions, saving five runs at left field and third base, and one run in right field. He did cost the team two runs at first base, so he wasn’t perfect, but his success at the other three spots made up for any deficiencies.

    The Twins needed the help, particularly at third and left, where Miguel Sano’s defense cost the team seven runs and Eddie Rosario’s cost them six runs. Though the Twins won the AL Central, their defense was not their strong suit – except in a few cases, like Gonzalez delivering as advertised.

    The Twins won’t need Gonzalez to play third in 2020 with the addition of Josh Donaldson. Donaldson matched a career-high with 15 Runs Saved there with the Braves last season. That total ranked third in the majors behind Matt Chapman (34) and Nolan Arenado (18).

     Buxton Among Best When Healthy

    The strongest suit of the Twins defense is center fielder Byron Buxton, who saved 10 runs in an injury-shortened season. Buxton probably wouldn’t have challenged Lorenzo Cain for the Fielding Bible Award had he stayed healthy, but he definitely would have given Kevin Kiermaier a run for his money for the AL Gold Glove.

    Buxton was as good as it gets on balls hit to the deepest part of center field, catching 96-of-111 in which he had a greater than zero chance to make a play. That was nine plays above his expected total. On a per 100 plays basis, he was better than Cain, for whom catches on deep balls was the most valuable part of his game.

    Mitch Garver A Much-Improved Catcher

    Mitch Garver wasn’t expected to be the better defensive catcher between him and Jason Castro, but it turned out that way in 2019. Garver made a 18-run improvement from 2018, saving one run, though that doesn’t tell the full story. Where Garver’s improvement came was in pitch framing, where he went from costing the Twins eight runs to saving them a run. He and Tucker Barnhart of the Reds were two catchers who greatly benefited from individual instruction (Barnhart’s improvements are noted in the Reds essay).

    Garver’s improvements were documented in the Minnesota media and were attributed to Garver’s working with catching coach Tanner Swanson.

    To illustrate the difference Swanson made, consider pitches that BIS plotted that were low, but were over the plate and within one inch of the knees. In 2018, Garver and his pitchers got the call 10% of the time (14-of-141). In 2019, that improved to 31% (39-of-125).

    The numbers indicate that Garver still has some work to do, particularly when it comes to blocking pitches and stopping stolen bases. He cost the Twins seven runs in those areas in 2018 and five in 2019.

    Max Kepler Gets The Job Done

    Max Kepler may not win any Fielding Bible Awards in right field but if you’re looking for consistency from an outfielder, he should be in every discussion. Kepler has saved eight, five, 13, and eight runs in the outfield the last four seasons. He plays right field well and has filled in as the center fielder when Buxton got hurt, saving three runs in 2018 and four in 2019.

    What’s interesting to watch about Kepler in right field is that he gets it done without a lot of splash. He had only one sliding or diving catch in 2019. Kepler’s means of making a play there comes down to his route running. By Statcast’s numbers, he matched Mike Trout and Andrew Benintendi in having the most efficiently run routes within three seconds of bat-ball contact.

  • New podcast: Royals GM Dayton Moore on analytics, leadership, breaking into baseball

    LISTEN HERE

    Apple Podcast LINK

    Stitcher LINK

    Anchor LINK

    Spotify LINK

    Episode Summary

    On this month’s edition of the SIS Baseball Podcast, senior research analyst Mark Simon (@MarkASimonSays) shares interesting things he’s learned about Matt Chapman, Fernando Tatis Jr., and Didi Gregorius from the new Defensive Runs Saved (1:06).

    Mark is then joined by Kansas City Royals general manager Dayton Moore. They discuss the state of the Royals rebuild (3:05), what an MLB manager should be expected to know about analytics and performance science (6:53), how the Royals shift and how they evaluate whether their defensive shifts are working (9:52), the importance of chase rate in evaluating draft prospects (12:33), Dayton’s interest in learning about leadership (16:18), and his advice for those who want to work in baseball (listen before you speak!) (19:37).

    Andrew Kyne (@Andrew_Kyne) also joins Mark to talk about The Fielding Bible Volume V, which will be out March 1 (23:12). Andrew also answers a listener question about how different aspects of defensive performance factor into a pitcher’s value (27:18).

    For more information, check out FieldingBible.com and SportsInfoSolutionsBlog.com. Thanks for listening!

  • Stat of the Week: The Fielding Bible All-Decade Team

    By Mark Simon

    Since 2006, Baseball Info Solutions has used The Fielding Bible Awards as its means of honoring the top defensive players in baseball. The Fielding Bible Awards have been voted on by a panel of experts – baseball writers, broadcasters, statistical analysts, and former major league players. Voting is based on both visual observation and performance in objective fielding metrics. With that in mind, we decided to take the voting from past Fielding Bible Awards and use it to come up with a team of the best defensive players in the 2010s.

    Our methodology for picking the All-Decade representatives was to use the Fielding Bible voting that was conducted annually throughout the decade. The player with the highest summed vote total from the 10 seasons was deemed the winner at that position. Note that for the years 2010 to 2012, each player’s vote total was multiplied by 1.2 to account for the use of 10 voters in those years compared to 12 in the other years.

    Fielding Bible Award Vote Leaders, 2010-2019
    PositionPlayer
    First BasePaul Goldschmidt
    Second BaseDustin Pedroia
    ShortstopAndrelton Simmons
    Third BaseNolan Arenado
    Left FieldAlex Gordon
    Center FieldLorenzo Cain
    Right FieldJason Heyward
    CatcherYadier Molina
    PitcherZack Greinke
    Multi-PositionJavier Báez

    Paul Goldschmidt starred for the Diamondbacks for most of the decade. His three Fielding Bible Awards (2013, 2015, 2017) were the most of anyone at first base in the 2010s. Goldschmidt’s 9.5 Scoop Runs Saved rank second to Freddie Freeman among first basemen this decade.

    Dustin Pedroia’s four Fielding Bible Awards (2011, 2013, 2014, 2016) are the most for any second baseman since BIS began presenting the honor in 2006. Known for a distinct and sizable crow hop that he combined with great anticipatory skills, Pedroia twice led the position in Defensive Runs Saved during the 2010s and had four straight seasons with at least 10 Runs Saved.

    Andrelton Simmons is the only player to win a Fielding Bible Award in six straight seasons. He did it in his first six full seasons in the major leagues (2013 to 2018). His 193 Defensive Runs Saved are the most of any player at any position for the decade, 115 more than the shortstop with the next-highest total (Brandon Crawford, 78).

    Nolan Arenado didn’t win a Fielding Bible Award until his third major league season, but once he did, he won three in a row (2015 to 2017). Arenado’s 105 Defensive Runs Saved were the most of any third baseman this decade, even though he didn’t start playing until 2013.

    Alex Gordon has had staying power. His four Fielding Bible Awards (2012, 2013, 2014, 2018) are the most of any left fielder, edging Brett Gardner and Carl Crawford by one. His 45 Outfield Arm Runs Saved this decade were the key to his success. They are the most by any outfielder in the 2010s.

    Lorenzo Cain became the first center fielder to win the Fielding Bible Award in consecutive seasons (2018, 2019) and also won the Multi-Position award in 2014. Cain’s specialty has been chasing down the deep fly ball. In 2019 he tied the single-season mark for home run robberies (5) since BIS began tracking them in 2004.

    Jason Heyward’s consistently excellent defense won him three Fielding Bible Awards (2012, 2014, 2015). He reached double-digits in Defensive Runs Saved in right field in each of the first eight years of the decade. His 141 Runs Saved from Range & Positioning are more than double the next-highest total of any right fielder this decade.

    Yadier Molina won three Fielding Bible Awards in the 2000s and three more in the 2010s, giving him six in total. That ties Andrelton Simmons for the most such awards won. Molina set the mark for most Defensive Runs Saved by a catcher with 30 in 2013 (since tied by Roberto Pérez in 2019). He also totaled 29 in 2012 and 26 in 2010.

    Zack Greinke’s only Fielding Bible Awards came the last two seasons. But he’s been in the hunt frequently, finishing second four times this decade. Greinke’s kept himself in top shape and been a standout athlete throughout his career. That’s allowed him to get off the mound aggressively to make plays that other pitchers don’t make.

    Javier Báez won the Multi-Position award in three consecutive seasons (2016, 2017, 2018) so he comes out on top. This award comes with an asterisk in that it wasn’t given out until 2014. Had it been awarded for the entirety of the decade, there’s a chance that Ben Zobrist, who played excellent defense at second base and in the outfield, would have edged Báez out.

    For more statistical leaders, check out the 2020 Bill James Handbook and the Sports Info Solutions blog.

  • Evaluating Infielder Throwing with the DRS PART System

    Baseball Info Solutions recently introduced a major update to Defensive Runs Saved that will be rolling out this offseason. We’re splitting DRS for infielders into Positioning, Air, Range, and Throwing components.

    In that introductory blog post, we mostly covered how this will affect the Positioning and Range components (which were previously reported together as one “Range & Positioning” metric). However, it’s also important to note how this system can estimate the value an infielder adds with his arm.

    So how do we calculate the Throwing component of the improved DRS?

    Using ball in play and positioning data charted by BIS Video Scouts, we estimate the chance that the play will be made at the point that the fielder obtains the ball, given the distance he must throw and how long he has to complete the play before the batter/runner reaches safely.

    This number is then subtracted from whether the play is made (0 or 1). That value gives us how many plays were saved by throwing, which is then multiplied by an expected run value to generate runs saved.

    Consider this play by Javier Baez. The chance that he would make the play from the point at which he obtained the ball – given his distance from first base and time to make the play – is estimated at approximately 39 percent. Baez made the play, so he’s credited with 0.61 plays saved (1 – 0.39).

    Baez is a standout with his strong throwing arm at shortstop. With our new methodology, he tied Matt Chapman at +11 Throwing Runs Saved to lead all infielders in 2019.

    Here’s a look at the top ten:

    Throwing Runs Saved Leaders, 2019

    Player Position Runs Saved
    Javier Baez SS 11
    Matt Chapman 3B 11
    Yolmer Sanchez 2B 8
    Amed Rosario SS 7
    Andrelton Simmons SS 7
    Jonathan Schoop 2B 7
    Nick Ahmed SS 7
    Tim Anderson SS 7
    Carlos Correa SS 6
    Kyle Seager 3B 6

    Over the past three seasons, the leaders are Nick Ahmed (+23), Kyle Seager (+23), Matt Chapman (+23), Jean Segura (+17), and Yolmer Sanchez (+17).

    This update to DRS allows us to not only split out the Positioning and Range components, but also to better understand an infielder’s value added with his arm. The data is now available on FieldingBible.com and will be featured in The Fielding Bible – Volume V (coming in the spring of 2020).

    Stay tuned for more information and updates regarding this improvement to DRS.

  • Updated 2019 Infield DRS Leaders Using the PART System

    Updated 2019 Infield DRS Leaders Using the PART System

    By Alex Vigderman

    It’s a big day for us at Sports Info Solutions. As of today, we have a new-and-improved version of our flagship statistic, Defensive Runs Saved, available to the public via FieldingBible.com.

    Previously, infielder DRS (specifically the Range and Positioning portion of DRS) used just the information about the ball in play to determine its likelihood of being turned into an out. That meant that we didn’t have the granularity to tell whether a play was made because the fielder went above and beyond or he was just positioned well.

    In essence, the calculation of Range and Positioning Runs Saved boils down to this single question: how well did the fielder do in completing the play given how often similar batted balls are turned into outs?

    A few years ago SIS started tracking infielder starting positions on balls in play, which we’ve collected back to 2013. That allows us to evaluate each infield play (groundball or short line drive) at multiple points in time, so instead of just answering the one question above, we can now answer three questions about a play:

    • Positioning: How much does the expected out rate change once we know how each fielder was positioned?
    • Range: How much does the expected out rate change between when the ball was hit and when the fielder gets to the ball (or fails to), given that we know where everyone started?
    • Throwing: How well did the fielder do in completing the play given where he fielded the ball, how hard the ball was hit, and the speed of the runner?

    Bundle those components with the evaluation of infield air balls and you get the PART System, which serves as the replacement for the Range and Positioning System for infielders.

    We’re really excited to bring all of this work out into the open.  After all, we’ve been collecting the required data for several years! We are releasing it via FieldingBible.com for now, and will work to get the numbers updated on other websites over the offseason.

    For now, here’s a rundown of how we rated infielders previously and how we rate them now. Remember when you’re looking at these changes, there are two big things the new system accounts for that DRS as you know it didn’t handle so well.

    1. We can now split up infielder performance in terms of Positioning, Air balls, Range, and Throwing. Because positioning tends to be a team decision, that positioning value is actually getting removed from a player’s total. Therefore, a player’s total in this new component of DRS really is his ART Runs Saved.
    2. Because it was difficult to evaluate players on shift plays before, we removed them from DRS. Now that we can measure performance independent of positioning, we can add those plays back in, giving a much more complete picture of a player’s value.

    Without further ado, here are the updated leaders at each infield position in 2019.  We’re excluding pitchers and catchers here because any impact that would come from the two changes above would negligibly affect those positions.

    First Base Defensive Runs Saved Leaders, 2019

    We don’t get a very different picture of the top players at first base as a result of these changes, but we do get a little bit of a picture of different players’ usage and competencies. Matt Olson and Christian Walker separate from each other partially because of the quality of their positioning, with Olson getting some negative positioning removed and Walker losing the benefit of strong positioning (more on the DBacks’ positioning in a bit).

    Another important but subtle thing to note here is that “Throwing” is a bit of a misnomer, especially for first basemen. Technically it’s a measure of how well you turn balls in play into outs once you’ve fielded them. For first basemen, that often involves running to tag first base or flipping to the pitcher as opposed to what we usually think of as throwing. Joey Votto was quite good in this respect in 2019, while Walker was not.

    Second Base Defensive Runs Saved Leaders, 2019

    At second base, the inclusion of shift plays was the biggest factor in who came out on top, as both Kolten Wong and Kiké Hernandez combined strong performance with excellent positioning. This is no surprise given that the Cardinals and Dodgers each netted 30 or more Shift Runs Saved in 2019.

    Falling off the leaderboard was Yolmer Sanchez. His 17 Positioning Runs Saved buoyed his total in the previous system, but the new system rates him as slightly below average in 2019.

    Third Base Defensive Runs Saved Leaders, 2019

     

    Andrew Kyne has already written about the changes to Matt Chapman’s numbers. He cements himself as the best defender relative to his peers, nearly doubling another mainstay at the hot corner, Nolan Arenado. You can see evidence that Chapman’s arm actually gives the A’s license to position him poorly, because he’s able to make up for it on the back end.

    Shortstop Defensive Runs Saved Leaders, 2019

    The numbers for Javier Baez and Nick Ahmed are really illuminating thanks to the new system’s breakdown. Baez leaps up by 10 runs from the previous system thanks to his excellent performance on shift plays, even with the Cubs ranking second-lowest in shift usage per BIS. His 11 Throwing Runs Saved tied Matt Chapman for the most among infielders, a fact we would not have been able to uncover with the previous system.

    Ahmed benefited from Arizona’s outstanding positioning, saving an additional 16 runs. That great positioning gave him quite the boost relative to his peers in the previous DRS system, so he drops back a bit in the overall rankings. He also didn’t perform as well while shifted, so adding those plays back in didn’t help him like it did Baez and shortstop leader Paul DeJong.

    This data is now available for all Major League players on FieldingBible.com, and it will also be featured in The Fielding Bible – Volume V (coming in the spring of 2020) and in The Bill James Handbook 2020 (out now).

  • New podcast: Nationals assistant GM, free agents and more awards

    LISTEN HERE

    On this week’s edition of the Sports Info Solutions Baseball podcast, senior research analyst Mark Simon ( @MarkASimonSays) opens the show by talking about the defensive analytics concepts he hopes a manager would know (1:16). Mark then talks with Nationals assistant general manager for baseball research and development, Samuel Mondry-Cohen.

    They discuss Sam’s path from batboy to front office executive (4:19), how the Nationals analytics department is structured (7:57), what it’s like to work with the coaching staff and with ace pitcher Max Scherzer (9:53), what his group was working on when the team was 19-31 (12:54), what role the analytics group played in the team’s acquisition of Daniel Hudson (14:12), and tips for pursuing a job in sports analytics (spoiler: Learn to code!) (15:59).

    Afterwards Mark is joined by SIS research associate Andrew Kyne ( @Andrew_Kyne). They review the White Sox signing of Yasmani Grandal and look at three other free agents of note (20:16). They also offer their own version of 8 MLB Awards ranging from “Hall of Framer” to “Flat Bat.” (25:20)

    Next podcast episode will be in December. See you then!

    Supplemental links

    Mark’s article in The Athletic on how free agents will impact a team on Defense

    Tyler Kepner on Samuel Mondry-Cohen

     

  • Stat of the Week: Who does the public want elected to the Hall of Fame?

    By Mark Simon

    The 2020 Baseball Hall of Fame ballot came out on Monday, which will inevitably lead to discussion on who deserves to go into the Hall of Fame and who meets the standards of being a Hall of Famer.

    But what about the question of whom the public would most like to see go into the Hall of Fame?

    Bill James attempted to answer this question in the lead article in the 2020 Bill James Handbook. He made a list of 156 current and retired players whom he felt would receive some suport and had each candidate polled six times over a three-month period this past summer, comparing that player’s Hall of Fame support to three other candidates on each poll.

    That resulted in 234 polls and nearly 290-thousand votes, which were analyzed by 12 formulas to measure each player’s Hall of Fame support.

    The result of all of the polling was that each player received a Support Score, indicative of how much public support they received. From that, Bill grouped players into six levels of Hall of Fame support. There were 14 players who received overwhelming support – a Support Score of more than 200 (an average score is 100). Some of them are still active. Some are long retired. One (Lou Whitaker) is on the Modern Era Committee Ballot. Four who are on the 2020 BBWAA ballot are marked in bold.

    Highest Hall of Fame Support Score
    NameSupport Score
    Barry Bonds1,445
    Justin Verlander772
    Adrián Beltré742
    Clayton Kershaw558
    Roger Clemens473
    Max Scherzer439
    Pete Rose414
    David Ortiz343
    Joe Jackson335
    Larry Walker292
    Alex Rodriguez258
    Lou Whitaker247
    Manny Ramírez223
    Carlos Beltrán220

    “The most striking thing about the list of players most-favored for Cooperstown selection is the concentration on the list of those who have been kicked out of baseball in gambling scandals (two) or kept out of the Hall of Fame in righteous indignation about PEDs or suspended for some period of time for failing a PED test,” Bill wrote, referring to Barry BondsRoger ClemensPete Rose, and Joe Jackson. Further, he pointed out that this isn’t a case of the public being willing to let PED usage slide. The public does care about PED usage, as evidenced by Rafael Palmeiro’s low Support Score (53).

    Granted, the polling system was imperfect because it was only polling Twitter users, but Bill noted that any system is going to have sampling issues, and he thinks this survey is “the largest and most extensive study ever of who the public WANTS to get into the Hall of Fame. That’s the goal, anyway.”

    Clemens, Bonds, and Walker are within sight of the 75% of votes needed to be elected, but still have a ways to go. Clemens received 59.5% on the last ballot, Bonds 59.1%, and Walker 54.6%.

    Clemens and Bonds have inched their way up slowly the last two years, making a gain of about 5 percentage points in that time. They have three ballots left to pick up the remaining votes needed. Walker made a jump of 20.5 percentage points from 2018 to 2019. He needs to do that again this year, in his final year on the ballot, to be elected. Ramirez has much more of an uphill climb, having received 23% of the votes in the last BBWAA balloting.

    If it were up to the Twitter-voting public, those four players would be on their way to Cooperstown. We’ll see if there’s any change among the writers to reflect that sentiment. In the meantime, buy the Handbook and check out the rest of Bill’s article to see how the public feels about the rest of the 156 notable players he included in the study.

    For more baseball content, check out the Sports Info Solutions Blog or the SIS Baseball Podcast.