Why Chris Davis Is Not A Rally-Killer

 

Photo by Keith Allison

During last week’s Camden Highball podcast, I made the following statement (paraphrased):

I love you, Chris Davis. But I don’t want you batting in the bottom of the 9th when the team is down by two and there are two runners on base. One-third of the time you’re going to strike out (not advance the runner). These little moments are going to add up during the year.

Prior to recording the podcast I’d thought a lot about the relationship between swinging strike rate and WPA. My gut told me a high-strikeout player like Davis would hurt the team by failing to advance runners in close games.

It seemed true. It felt true. So I said it out loud.

After I listened to the recording, an embarrassed flush spread to my cheeks. Here I am, writing on a sabermetrics web site, and I just used my gut to make a statement. Ugh! We all say foolish things, but not many of us get the chance to say foolish things that strangers on the Internet hear and that live for eternity on Dropbox. I managed to do both at once.

In order to feel less foolish, I had to atone for my sins. Isn't that what this whole sabermetrics thing is about, backing up your beliefs with evidence? So I said "gut, I'm sorry, but I need to fact check you." My gut responded favorably, but that's probably because I'd just eaten a peanut butter creme Oreo.

I examined the relationship between a player's swinging strike rate and the following metrics:

• Win Probability Added: Measures how much a player added to their team’s chance to win during the course of a season, taking into account both the leverages (inning, score, runners on base, number of outs) in which they batted and how well they did in the plate appearance.
• Win Probability Added / Leverage Index (WPA/LI): WPA without the leverage component. Unlike WPA, WPA/LI doesn't punish players for appearing in lots of low-leverage situations, nor does it reward players to bat in a lot of high-leverage situations. Players can't control the leverage of the situations in which they bat.

I sampled non-pitchers from 2010-2015 who averaged at least 50 PA per season. This low threshold avoided survivor bias by looking at not only starters, but also role players and those who were injured.

My hypothesis: players with high swinging-strike rates will have a lower WPA than players with low or average swinging strike rates. For context, Davis’ swinging strike rate of 15.48% ranks 20th-highest out of 1,607 players in this sample.

Unfortunately for my gut, the research shows swinging strike rate doesn't correlate well to either WPA or WPA/LI:

Swinging strike rate explains only 0.07% of the variance in WPA, or about 0.002 wins per year. That's a tiny number of wins.

The relationship isn't much stronger when you remove leverage from the equation. The r^2 between swinging strike rate explains only 0.0198 wins of WPA/LI per year. No one will notice this change in a player's WAR.

But r^2 isn't everything. The regression lines slope upward, indicating that as swinging strike rate increases, WPA and WPA/LI also increase. If you followed this model you'd want a player to swing and miss as much as possible, because the model says their WPA would be very high. But no one wants a batter to swing and miss ever, let alone "as much as possible".

That's why the plots look different if you focus on players with medium-to-high swinging strike rates:

The r^2 values remain weak. More importantly, these trend lines slope downward. Now the model says: if you swing and miss a lot, you're starting from a deeper hole than your peers who make more contact. You can still make a positive contribution, but you'll have a harder time doing so. There's the logical sense we are looking for.

A 2nd-degree polynomial fit of the original data shows this effect better:

While Chris Davis' swinging strike rate doesn't explain his WPA or WPA/LI, he should be careful going forward. If he swings and misses much more than he does now, he'll have a harder time contributing to the team.

Fortunately, Davis is a more complete player than just swinging and missing. He possesses tremendous power and mixes in a pretty good walk rate. These factors boost his wOBA, which correlates much better with WPA and WPA/LI:

The r^2 between wOBA and WPA is 0.64 (2.1 wins), and between wOBA and WPA/LI it's a whopping 0.82 (2.3 wins). Overall offensive prowess, as measured by wOBA, explains variance in WPA and WPA/LI much better than than swinging strike rate does.

These relationships hold up well for hitters in Davis' class:

In both cases, the regression models make logical sense. Have a high wOBA and you'll contribute wins to your team. Chris Davis should have a high wOBA. All is right with the universe.

I'm sorry, Chris Davis. I take back what I said. I won't grimace in frustration anymore when I see you bat in a high-leverage spot. I'll remind myself that you're a very talented baseball player who whacks the ball all over the yard, no matter the game situation.

But please don't swing and miss any more than you already do.

What WPA Teaches About The 2015 Orioles

Just five games ago, it seemed like the Orioles had finally turned the corner and were set to make a run to at least secure a wild-card spot. The Orioles lost each of those next five games and are now at .500. Orioles’ fans are feeling despondent while Manny Machado apparently boiled over in the locker room after the latest Orioles heartbreaker. Why have the Orioles struggled this year?

In 2014, the Orioles scored 705 runs while hitting 211 home runs and are on pace to score 715 runs and hit 212 home runs this year which means that their offense hasn't gotten worse. The pitching hasn’t performed as well as the Orioles allowed 505 runs through August (3.74 R/G) in 2014 and have so far allowed 498 runs this year (4.01 R/G).  Allowing an extra quarter of a run per game shouldn’t be the difference between winning 96 games and flirting with .500.

Looking at the Orioles’ Win Probability Added (WPA) and Clutch statistics from 2012-2015 can help explain why the Orioles have struggled this year. For those unfamiliar, WPA determines the change in the likelihood that a team will win from one plate appearance to the next and credits or debits the player based on how much their action increased their team’s odds of winning. The Clutch statistic measures how well a player has performed in high leverage situations.

The first chart, which measures the Orioles’ offense from 2012-2015, shows that the Orioles have scored a standard amount of runs. The problem is that they haven’t been in the right situations and is why the Orioles are projected to have a negative clutch score for the first time in the sample. In contrast, the Orioles’ offense was very clutch in 2013 and reasonably clutch in 2012 and 2014. This is also why the Orioles’ offensive WPA is on pace to be worth 2 wins while it was worth over 6 wins in 2013 and 2014.

While the Orioles are on pace to score 715 runs in 2015, the Orioles’ wRC suggests that they should only be scoring 687. This is lower than what the Orioles scored from 2012 through 2014 and could indicate that Orioles’ fans feel like their offense isn’t as good as it has been in past years because they've scored more runs than expected. 

The next chart shows that Orioles’ starters have a better ERA in 2015 than they did in 2012 or 2013 but have a considerably worse win-loss record and have a lower WPA. The data also suggests that the Orioles’ starters have been only average in the clutch as opposed to 2014 where they came up big in crucial situations. Unlike in previous years where the offense was able to offset the starting pitching weaknesses, it appears that the Orioles have been unable to recover from their starting pitching performances.

The third chart shows that the Orioles 2015 bullpen has had the best ERA out of the four bullpens when using either standard ERA or leveraged ERA (a metric that I use which grades relievers based on their innings pitched and game leverage to ensure that a closer is given more credit than a middle reliever for bullpen performance). Unsurprisingly, the solid 2015 bullpen has a high 59% win rate (equivalent to a 96-66 team) which is the best of any Orioles club over that period with the sole exception of the extremely clutch 2012 bullpen that had a 74.4% win rate (equivalent to a 121-41 team). Yet while this bullpen has been extremely effective, it hasn’t resulted in producing wins according to WPA compared to those other bullpens.

 

The reason for this can be explained partly by game leverage and partly by comparing saves, holds and blown saves to previous years. In 2015, the Orioles bullpen average game leverage has been 1.05. Their average game leverage ranged from 1.15 to 1.30 from 2012 to 2014. This means that they haven’t been able to pitch in as crucial of situations as they have in the past. This explains why the Orioles’ bullpen is on pace to have only 42 saves and 48 holds in 2015 despite having mid-50 saves from 2012-2014 and between 67 and 97 holds from 2012 to 2014. It would appear that the Orioles bullpen hasn’t had as many opportunities to pitch with a lead as they have previously and consequently saves, holds and blown saves have all decreased.

It should come as no surprise that the Orioles are 17-22 in one run games and 10-15 in two run games because those are the ones most dependent on luck or clutch performance. If the Orioles were to have won as many one and two run games as they’ve won games decided by three or more runs, then they would have another ten wins and would likely be in a fight with the Blue Jays to determine the AL East winner.  Their problem is that they simply haven’t been clutch.

In previous years, the Orioles have been successful by getting a lead to their bullpen and letting their bullpen save the day. In 2013, the Orioles ultimately fell short because the bullpen couldn’t hold onto enough leads and win enough games. This year the bullpen has done well when given a lead (except for this past week) but it just hasn’t happened often enough. The story that the data seems to be telling is that the bullpen has been placed in a situation where they’re trailing by a small amount instead of leading by a small amount and the offense just can’t quite get that hit that would give the bullpen a lead. There’s only so much a bullpen can do in those situations.

The Orioles are still .500 and have over a month to play. Their team is really built to win in September and if the Os do go on a run and take the second wild card spot then no one will care what happened earlier this year. But if the Orioles don’t end up making the playoffs, then people will look at these close games and wonder what could have been with just one more solid offensive player or slightly better pitching from the starting rotation. 

Clutchest Hits of 2012

During the magical 2012 season, the Orioles came up with a bunch of clutch hits. After all, you don't outperform you Pythagorean Win totals buy 11 games without coming up big in some close games. The Orioles were no exception.

So I took the 10 biggest hits in terms of Win Probability added and listed them below. Lots of heroes, not all of them obvious.


10. Wilson Betemit - .43 WPA - 4/13/12

The Orioles were in Toronto with two outs in the 8th and the bases were loaded. Betemit singled on a sharp ground ball up the middle scoring Nolan Reimold and Nick Markakis turning a 1-run deficit into a 1-run lead. Reimold would tack on a run with a solo homer in the 9th and the Orioles would win 7-5, breaking a three game losing streak early in the season.




9. Adam Jones - .43 WPA  - 9/19/12

It was the top of the 11th in Seattle and the game had been tied since the 4th inning. Nate McLouth hit a 1 out single and then Adam Jones put the O's on top for good with a long home run to left field. The win put the team 21 games over .500 and kept them a half game back of the Yankees for the division lead.




8. Taylor Teagarden - .44 WPA - 7/14/12

The game versus the World Series bound Detroit Tigers on July 14th is the clutchiest team performance in terms of offense of the 2012 season. Taylor Teagarden's game winning 2-run homer in the bottom of the 13th is not even the biggest hit of the game in terms of WPA and is one of three hits that moved the winning probability more than 40% in the Orioles' favor.




7. Adam Jones - .44 WPA - 7/14/12

There would have been no Teagarden walk-off in the 13th without Adam Jones' big hit in the 11th. Down to their final out with two men on, Jones drove a liner into left scoring Nick Markakis and tying the game at 5 runs apiece.




6. Mark Reynolds - .45 WPA - 7/19/12

With two outs in the top of the 8th, Mark Reynolds singled in Matt Wieters and Wilson Betemit turning a one run deficit into a one run lead. The O's would beat the Twins 4-3.




5. Nick Johnson - .45 WPA - 5/11/12

Remember him? He didn't play much but he did have one of the biggest hits of the year for the Birds. With two outs in the bottom of the 7th, Johnson hit a 2-run homer and turned a 3-2 deficit into a 4-3 lead. (Sound familiar?). The bullpen made it stand up for the one run win over Tampa Bay.




4. Matt Wieters - .46 WPA - 6/24/12

The Nationals had shutout the Orioles for 7 innings but in the bottom of the 8th, Adam Jones singled and then Matt Wieters hit a homer to deep left-center. The blast gave Baltimore the 2-1 lead and, once again, the bullpen made it hold up.




3. Nick Markakis - .46 WPA - 4/22/12

Like many others, Nick Markakis turned a one run deficit into a one run lead with a bases loaded single in the top of the 8th. For good measure, after Angels had tied the game, Nick singled home the go-ahead run yet again in the top of the 10th off of La Troy Hawkins to give the O's their 3-2 victory. With those two big hits, Markakis had .741 WPA for the game, the clutchiest game for an Oriole hitter during the season.




2. J.J. Hardy - .47 WPA - 7/14/12

Back to the July 14th game against the Tigers, the Orioles were down by one run with one out in the bottom of the 13th. Taylor Teagarden was able to give the Birds the win thanks to J.J. Hardy's game tying homer earlier in the inning bringing them back from the brink of defeat.




1. Nate McLouth - .54 WPA - 8/27/12

Pedro Strop gave up three straight singles in the top of the 8th to give the White Sox the 3-2 lead. With one out in the bottom of the inning, Mark Reynolds walked and Nate McLouth hit a 2-run homer to deep right to give the Orioles the 4-3 lead that Jim Johnson would again make stand up.




Looking over this list, you can make the argument that the July 14th game versus Detroit was the turning point of the season. The Orioles were just 4 games over .500 heading into that game and went 48-28 the rest of the way, 20 games over .500. There were lots of great moments in this Oriole season but July 14th may have been the greatest game they played and sparked them to greater things as the rest of the season played out.

Measuring Bullpen Management: Bucking Up the Bullpen

A common thought among many of us is that much of the Orioles' success in 2012 was largely dependent on the bullpen.  An fWAR breakdown shows that the bullpen (6.4 fWAR, 5th) was better ranking-wise than either batting (15.3 fWAR, 25th) or starting pitching (10.2 fWAR, 19th).  The bullpen was largely constructed with existing pieces, half of the return for the Guthrie trade, and a small late winter free agent signing.  A more thorough discussion of the various pieces of the bullpen can be found in an article Jon Bernhardt wrote in August.  This post however will take a look at whether bullpen performance can be attributed to a manager.

Generally, conventional wisdom has it that individual relief pitchers are a widely varying lot in terms of performance.  These pitchers put up about 50 innings or so each year, which really is not enough time on the mound to statistically inform an assessment of future performance.  However, it may well be that a manager (or perhaps a manager with his General Manager) may actually be able to create a high performing bullpen on a relatively consistent basis.

A Hardball Times article suggested using WPA - WPA/LI as a measure of bullpen performance that would be useful in assessing bullpen management.  WPA is the acronym for Wins Probability Added.  This is calculated as the difference in win expectancy before and after an event. LI is the Leverage Index.  It is a measurement of how consequential a specific scenario is based on the inning, outs, score, baserunners, and baserunner position.  By using the two statistics in concert, you arguably have a measure that gives you a context neutral wins added metric.

To test whether this metric would give an indication that managers have skill associated with using a bullpen well, I decided to take the last five seasons of several recent managers.  I compare each manager's mean for WPA, WPA/LI, and WPA-WPA/LI (ANOVA).  WPA will inform us simply if certain teams wind up with better outcomes for winning based on reliever usage.  WPA/LI will neutralize all situations and measure reliever ability in general (similar to wOBA).  WPA-WPA/LI is being used to inform us about whether relievers actually perform better in clutch situations.  If one of these statistics indicate an actual skill then the numbers associated with a manager should be (1) repeatable and (2) result in managers being different from each other.  Of course, this assumes that these things are, in fact, measurable.

	WPA	WPA/LI	WPA - WPA/LI
Bob Melvin	3.75	0.83	2.92
Bruce Bochy	2.98	0.13	2.84
Joe Giraldi	7.37	4.88	2.49
Buck Showalter	5.61	3.67	1.94
Terry Francona	5.56	3.69	1.88
Mike Scioscia	1.94	0.13	1.81
Ozzie Guillen	1.86	0.31	1.54
Joe Madden	4.42	3.21	1.22
Ron Gardenhire	2.78	1.59	1.19
Charlie Manuel	2.60	1.49	1.11
Ron Washington	4.35	3.25	1.10
Bud Black	1.74	0.80	0.94
Dusty Baker	2.76	2.19	0.56
Joe Torre	2.81	2.28	0.53
Jim Leyland	1.16	0.90	0.26
Ned Yost	1.00	1.29	-0.29
Tony LaRussa	1.28	1.74	-0.46
Eric Wedge	-0.80	-0.15	-0.66
Bobby Cox	0.31	1.63	-1.31

Interestingly enough, both WPA (p=0.12) and WPA - WPA/LI (p=0.45) were not found to be significant in this study using this data.  However, WPA/LI was found to have significant differences within the population (p < 0.05).

So who typically has a good bullpen based on WPA/LI?

Joe Giraldi	123~5~~~~~~
Terry Francona	12345678~~~
Buck Showalter	1234567~~~~
Ron Washington	~234567~~~~
Joe Madden	123456789~~
Joe Torre	~234567890~
Dusty Baker	~234567890X
Tony LaRussa	~234567890X
Bobby Cox	~234567890X
Ron Gardenhire	~234567890X
Charlie Manuel	~2~~567890X
Ned Yost	~234567890X
Jim Leyland	~~~~567890X
Bob Melvin	~234567890X
Bud Black	~234567890X
Ozzie Guillen	~~~~~67890X
Bruce Bochy	~~~~567890X
Mike Scioscia	~~~~~~7890X
Eric Wedge	~~~~~67890X

The above table shows groups of similar performance.  The bold numbers indicate how managers differ.  Most managers belong to their own specific number, but 7 (Baker, LaRussa, Cox, Gardenhire, Yost, Melvin, and Black), 9 (Leyland and Bochy), and 0 (Guillen and Wedge) are shared.  For instance all 1s are not significantly different from Joe Giraldi and Joe Giraldi is significantly different from groups 4 and 6 through X.  Eye-balling it there are essentially three tiers:

Tier 1
Giraldi, Francona, Showalter, Washington, and Madden

All five of these managers get consistently good performance out of their bullpens and, as a whole, have significantly better performance than groups 9 through X.  Joe Giralid's pens have produced very well making his group significantly better than all of the others except 1, 2, 3, and 5.  This actually provides a potential argument for leaving Washington out of this tier.  However, the relationships of his performance with the other managers' performances appear to fit best in group 1. Only Showalter had multiple GMs in this grouping.

Tier 2
Torre, Baker, LaRussa, Cox, Gardenhire, Yost, Melvin, and Black

This group appears no different from anyone other than Joe Giraldi's bullpen.  Torre, Yost, and Melvin account for the managers for more than one GM.

Tier 3
Manuel, Leyland, Guillen, Bochy, Scioscia, and Wedge

The bullpen performance out of this group are notable in that they are not included in some of the upper performing groups.  In fact, their performances are significantly worse than everyone in Tier 1 except for Francona and Madden.  Only Wedge and Guillen were managers under different GMs.

The above study shows that good bullpen performance when measured as context neutral does tend to relate to specific managers.  However, it is unclear exactly what is resulting in these managers having good bullpens.  It does not appear that certain managers are adept at putting their pitchers in certain scenarios to get the most out of them, but that may simply be a limitation in how I tried to measure bullpen management.

Orioles Clutch

by Daniel Moroz

 

This has obviously been a magical season for the Orioles, and part of that has been guys coming up big when the team has needed them to. There's probably no better example of that than back-up catcher Taylor Teagarden, who has all of 7 hits on the season (.140 batting average, .229 wOBA), but who has made those hits count.

 

He knocked in the winning run with a pinch-hit single in the 18th inning in Seattle.

He hit a 7th inning go-ahead two-run double against the Rays, moving the score from 0-1 to 2-1 (the O's eventually on in the 14th).

He hit a game-tying home run against the White Sox in the 3rd inning, and then tacked on an insurance run in the 4th (that might have come into play, as the Sox made a failed rally in the 9th).

He drove in the only run of the game with a 10th inning double against the Rays at the beginning of August.

He singled as part of a rally against the A's in July, scoring a run in an inning that saw the O's go from down 5-2 to up 6-5 (though they lost). This is the only hit Teagarden has all year that didn't drive in a run, and it's the only game in which he got a hit that the Orioles didn't win.

In his first game of the season, he hit a 13th inning walk-off home run against the Tigers (giving Kevin Gregg the W!).

 

He also threw the potential tying runner out trying to steal to end last night's game. That is some clutch performance* right there.

 

* Note, this does not mean that Teagarden is a "clutch player", or that he'll continue to come up big going forward. Nice microcosm of the Orioles' season thus far in that respect.

 

Teagarden inspired me to take a look at such "overperformance", so I compared players' Win Probability Added (WPA) with their batting runs (as part of Wins Above Replacement) which looks at just individual production removed from context. Teagarden has a ho-hum +0.6 WPA (~5.7 in runs), while he's been at -4.1 batting runs overall - that's a difference of 9.8 runs based on the timing and context of his hits. That's not the best in the Majors this year by a long shot - Ian Desmond  is at +23 runs - but give Teagarden a little credit given his all the team he's missed; on a per plate appearance basis, he's easily #1 at making the most of his successes (+0.2 runs/PA).

 

Just looking at the Orioles, Teagarden is by far the best representation of this. Second (by plate appearances), is actually Steve Tolleson, at +2.5 in 74 PA. He's been a negative based on WPA (-0.2) but considering how awful of a hitter he is (.188/.233/.319, -4.4 batting runs), he should have hurt the team even more. His biggest moment was hitting a game-tying three-run homer off of Cliff Lee (the O's went on to win 5-4 in extras - I'm seeing a pattern here).

 

Ryan Flaherty (+4 in 137 PA) is in a similar bad-WPA, worse-hitter situation. His highest WPA play was breaking a 7th inning tie game against the Indians with a single (the O's went on to win 9-8, as a Xavier Avery homer provided a needed insurance run).

 

Steve Pearce isn't with the O's, but he did his part (0 batting runs above average, but +0.1 WPA) with a game-winning three-run homer against the Angels (the only runs the O's scored in that game).

 

Nate McLouth was a little lower than I expected, but he's actually hit quite well for the Orioles (.287/.358/.446, +5.4 batting runs) so his +0.9 WPA isn't that impressive. He does have three game-winning hits; a 4th inning two-run triple against the Tigers that moved the O's from behind to ahead and stood up for the rest of the game, an 8th inning two-run homer against the White Sox that moved the O's from behind to ahead (I believe this was the play of the year, at +0.53 WPA), and a walk-off RBI single against the Rays. McLouth has been one of those scrap-heap pick-ups that's done a really nice job for the team.

 

Mark Reynolds is often vilified by fans - especially as "garbage time" home run hitter - but his 1.6 WPA (second best amongst position players on the team) has outstripped his +9.2 batting runs. Perhaps ironically, his biggest hit of the season wasn't a homer but a two-run 8th inning single against the Twins that put the O's ahead 4-3 to stay. More musingly, his second biggest didn't even drive in a run - it was a ball he hit to lead off the 10th inning against the White Sox on which their center-fielder made a three-base error (Reynolds scored the winning run on Chris Davis' subsequent double, and O's won what ended up being a 10-4 route).

 

Getting mighty close to parity (on a rate basis), we have Adam Jones at +2.8 WPA and +22.3 batting runs. He has a ton of big hits, including 4 extra-inning home runs (all game-winners, though only one was a walk-off). #1 for him was actually not a homer or even a game-winner though, but an 11th inning game-tying single to keep the O's alive (they fell behind in the top of the frame, and went on to win in the 13th when the Orioles were behind again and JJ Hardy hit a game-tying homer before Teagarden did the walking-off).

 

On the other end of the spectrum you have the likes of Wilson Betemit (-0.9 WPA despite +1 batting runs), who has some late-inning heroics but also a lot of negative at bats.

 

Overall, most Orioles position players aren't too too far off between how they've hit overall and their Win Probability added - it's pretty much the Magic of Taylor Teagarden, and everyone else balances out (-1.7 WPA, -19.3 batting runs).

 

Things are a little different on the other side of the ball. Oriole starters have been below average (9th in the AL in ERA, FIP, xFIP, and SIERA all) and have a -1.2 WPA to show for it (8th in the league). The bullpen though, has been nuts; 3rd in ERA, 7th in FIP, and 6th in xFIP, but in first by far in WPA at a whopping +12.8. That's the best mark... ever*. This has been a historically lucky or clutch (or however you want to explain) group.

 

* Going back to 1974, but given the way reliever usage has changed over time - 14 of the top 20 are from the 2000s - I'd guess that it would hold up.

 

Jim Johnson: +4.8 WPA (best in the AL for relievers), 1.2 fWAR (16th in the AL for relievers)

Darren O'Day: +3.1 WPA (5th), 1.2 fWAR (14th)

Pedro Strop: +1.4 WPA (19th), 0.8 fWAR (39th)

Luis Ayala: +1.2 WPA (24th), 0.6 fWAR (44th)

Troy Patton: +0.9 WPA (37th), 0.8 fWAR (37th)

 

Plus Steve Johnson and Brian Matusz have combined for +1.0 WPA in their relatively short time out there.

 

The worst mark in the pen for a reliever with more than 10.1 IP is Kevin Gregg... at -0.1 WPA. Even Kevin Gregg barely decreased the Orioles' probability of winning games this year. That's amazing.

 

I guess that's how you win 15 straight extra-inning games (15-2 overall) and go 27-8 in one-run games. Having Taylor Teagarden around in later innings might help a little too.

Orioles Recap: Oh So Fickle

I typically never run recaps because you can easily find your descriptive columns elsewhere. At Camden Depot we try to go underneath the surface and try to explain how things happened or what will happen. Last night though is a good time to introduce leverage index values and winning probability added. These two statistics are collected by FanGraphs.

Here is the graph from last night's game:



Winning Probability (WP) is shown on the top graph. Essentially, the statistic is based on the probability of a certain result in relation to the score, inning, and outs affects a team's chances to win. This is often expressed as Winning Probability Added (WPA). This try to discern how different players producing certain events affect changes in WP. For instance, Salazar's homerun increased the Orioles' chances of winning by ~40%. His WPA for the single event would be 0.40 and this would be added to his other events during the day. His final WPA for yesterday's game was .321 and was third among Orioles' hitters for the day.

Leverage Index in the bottom graph. Basically, the greater your value, the greater the probability in winning is shifted. For instance, in the top of the first inning, you can see that the leverage decreases as each out is made. In relation to other innings, the leverage is low because the game is tied and there are plentiful opportunities to score runs later. A run in the first has less meaning than a run in the ninth because the opposing team has less opportunity to score that single run back to even it out. Another example would be in the top of the ninth when George Sherrill entered the game. The leverage starts high because the Orioles have a one run lead and the Pirates have no outs. It then becomes greater with Nady's single to right. After LaRoche's home run, the leverage is almost nothing because there is no one on and the Orioles are down by a run.

Hopefully, you found this interesting.