Expanded Four Factors links:
Average Player
Math/Reference

For our first use of the expanded four factors with a real, live Major League Baseball player, let’s take a look at Ryan Howard. Howard has had an interesting season this year, posting a solid .377 wOBA despite a pretty severe drop in both power and walk rate. His ISO is down from .292 to .236 and his POWH (XB/H) is down from 1.05 to 0.81. His walk rate has dropped from 10.7% to 7.5%, but the strikeout rate (in K/PA) has also dipped, from 26.5% to 23.7%.

Basically, we see two bad signs combined with one excellent sign for Howard. Some in Philadelphia are excited to see what Howard can do making more contact, especially if the power and discipline were to return to their normal rates. Let’s take a look at what would happen for Howard if his K-rate were to decrease from its career mark of 27.4% to his current mark of 23.7%, if his power and walk rates were to return to their typical levels. For his career, Howard has posted a .393 wOBA, which the Four Factors method overshoots by 5 points, even after his career 2B/HR and 3B/HR rates are input.

Here we see why Phillies fans would be so excited about a new, relatively contact happy Howard. Howard was truly an elite hitter in 2006, putting up a .436 wOBA, thanks in large part to 58 homers as well as a 15% walk rate. If Howard were to hold his strikeout rate as low as it has been in 2010 while returning to the power and discipline numbers that he’s shown over his career, his ffwOBA jumps up to .418 from .398 – not as high as his 2006 season nor Pujols’s crazy numbers from the last 3 calendar years, but still elite and likely top-5 type material.

That said, there are legitimate reasons to worry about Howard. He has been a second half hitter by the numbers, but stranger things have happened than a player losing a significant amount of his power in his age 30 season. What if instead of the K-rate staying down, it’s the power numbers that decline. Let his career BABIP remain at .329, slightly below his rate from this season. Finally, let’s look at this decline both if the walk rate stays at 7.5%, its current rate, his career low, or if it rebounds to 12.2%, his career average. The low walk rate is in blue; the high in red.

Here we see cause for concern. If the walk rate returns but the power stays as low as it has, Howard will be around a .360 wOBA hitter, which is right around the level of David DeJesus and Vernon Wells, and it would be exceptionally difficult for Howard to justify his 5 year, 125 million dollar contract providing such little pop at the plate. If the walks and power both are gone, than Howard’s wOBA slips to .350, right in line with Daric Barton – a good first baseman, particularly with the glove, in a pitcher’s park, but that’s hardly the all-star level performance expected out of Ryan Howard.

Of course, we come now to the question of what we actually think will happen with Howard. ZiPS projects a .398 wOBA due to a spike in BB% and a jump in power to just below previous levels, along with a rise in K rate back to previous levels. CHONE doesn’t project that Howard’s walk rate will rise above 10% again. Along with a rise in K% back to previous norms and a rise in power that doesn’t quite reach its old heights, CHONE projects a .273/.344/.537 line.

Interestingly, power is the one aspect that takes the longest to stabilize. To me, that suggests that the power could easily return to 2009 levels, but the walk rates and strikeout rates may not. Howard’s ability to reach the base via the walk is extremely important, and his 2010 BB rate is merely half of what it was in that fantastic 2006 campaign. Still, the numbers here suggest that even a drop in XB/H from 1.05 to 0.95, as CHONE projects would cause nearly a 20 point drop in wOBA.

So, in summary, yes, Howard’s drop in power will be of concern unless he has another monster August/September, which, given his 153/175 career wRC+’s in those months, isn’t exactly unlikely. At the same time, Howard’s drop in strikeouts is great to see, but the projection systems don’t appear to be convinced in the slightest. Howard would likely be the best non-Pujols hitter in the league if both the drop in strikeouts persists and his power fully returns. The flip side, however, would see Ryan Howard and Daric Barton fighting it out on a yearly basis, and that would be disastrous for the Phillies. The most likely scenario, however, is the simplest: Howard returns to his old form with a slight drop in power, which would leave him as still one of the better hitters in the National League, although not quite a top-5 or necessarily even a top-10 hitter.

During the Media portion at this past weekend’s Live Event, one topic addressed by the panel members was the relevance of the traditional game report.

On this subject, the Boston Herald’s Michael Silverman said something to the effect of: “This is our first year at the Herald without proper game repots. We figured that our time and resources were better spent elsewhere — analyzing the game, etc.”

Allow me, first, to echo vigorously Silverman’s comment. I’ve said it before, will say it again, and will probably have it inscribed on my tomb at Père Lachaise Cemetery in Paris, France, after I die: “The traditional, pyramid-style game report is a Snooze Fest of gigantic proportions.”

*Although, owing to the location of my tomb, the inscription will read more like the following: “Le rapport de match traditionnel du modèle-pyramide est un Snooze Fest des proportions colossales.”

But allow me to offer, secondly, a revolutionary thought: what if, instead of being written “pretty soon after the game” by a “paid reporter” who “watched the whole game attentively” — what if, instead of all that, a game report was written three days after a game by a bespectacled fellow who drank, like, three beers during said game and is generally prone to forming irrational attachment to fringe players?

Well, in that case, it would probably very much resemble the following.

The Game I’m Talking About
It happened this past Sunday night, August 8th, between the Connecticut Tigers and Brooklyn Cyclones of the short-season New York-Penn League. The latter team is a New York Mets affiliate; the former, shockingly, is affiliated with the Tigers.

Connecticut won 6-3. I mean, just in case that sort of info is important to you.

Why I Went There in the First Place
The answer to this question is a little bit of the “N’doy” variety, but still fair. Anyway, here are three reasons:

1. Because I was in New York already. (Live Event in the hizouse.)

2. Because minor league games are cheaper, and generally more accessible, than their major league counterparts.

3. Because it gave/gives me the opportunity to front like a prospect maven. (Which, if you’re gonna front, fronting like a prospect maven probably isn’t the worst. Fronting like a doctor? That’s pretty bad.)

What the Weather Was Like
Silly good. Sunday was a hot day in New York — and humid. But on account of MCU Park is right by the frigging ocean, there was this great breeze.

Pop quiz: How many baseball stadia are right by the ocean? San Francisco’s AT&T and San Diego’s Petco Parks are the only two I can think of. (The latter is on San Francisco Bay, but whatever.) As for minor league stadiums — fuggedaboutit.

What the Crowd Was Like
The box score says that 8,047 were in attendance — this, in a stadium with an official listed capacity of 7,501.

If this is true, then I’m forced to assume that the one or two thousand empty seats around the park were occupied by the Ghosts of New York Baseball Past. And they all paid.

What the Crowd Was Also Like
Like all the tweets from Sh*t My Dad Says being read aloud, simultaneously, over and over.

Read the rest of this entry »

A common adage is that a pitcher needs either good stuff or location to make it in the major leagues. Jeff Karstens is not someone with good stuff. On the best of days his fastball can average a severe wind-aided 90 miles per hour. Hurricanes are uncommon in the greater Pittsburgh area so the righty settles for an average of 89 miles per hour. Karsten’s secondary offerings are superior – including a very good curveball – but the book on him is that he’s not going to get a ton of strikeouts or grounders. What he will rack up – as the adage suggests – is strikes.

Karstens is throwing 66% strikes this season, which places him in a tie with Joe Blanton and ahead of Felix Hernandez, Francisco Liriano, David Price, and a slew of pitchers with superior stuff. He’s amongst the 25 starting pitchers who throw the most strikes on a rate basis which is led by Cliff Lee (72%) and Scott Baker (70%) amongst others. This within itself isn’t too interesting or worthy of adulation because Karsten’s phobia towards throwing balls is yet to result in fantastic performances – minus one heck of a start during the 2008 season versus the Diamondbacks.

The real story to tell about Karsten’s strike rate is really about the reciprocal or his ball rate in this case. Karstens has issued five intentional walks in a little over 100 innings of work. His career total through about 217 innings entering this season was seven. That kind of really free pass rate has the tendency to creep into and distort things like strike ratio. Nobody ahead or near Karstens on the strike rate leaderboard is over more than 2% intentional balls/balls thrown, so his intentional balls are skewing his strike rate the most. What has it meant to his rate of strikes thrown?

Since we know that five intentional walks equals 20 intentional balls, then we can just subtract those balls from his total (491) and redo the division by his total pitches with those 20 pitches subtracted (1430 after the minus); giving us a real strike rate of 67%. That’s not entirely fair, though, because Karstens would have had to throw pitches versus those batters and we can’t simply pretend they never happened. What if he threw 20 pitches to each, and half were strikes – after all, 10 extra strikes instead of 10 extra balls is better than 20 balls to 0 strikes. Well, then we get a strike rate of 67% again.

67% to 66% is a minute difference; no doubt, but when we talk about strike rates or even walk rates, the amount of intentional balls and walks is often ignored.

In less than two months the regular season will come to a close and the postseason will begin. In each of the past three seasons we’ve had teams go to game 163 in order to decide a tiebreaker. Frankly, those win or go home games rank right up there with some of the best games in recent memory. Whether it be the controversial Padres/Rockies finish in 2007, or the White Sox and Twins in 2008, or even the Tigers and Twins last season; each came down to being decided by a single run. The way the standings are shaping up right now, we might be in store for another tiebreaking game or two.

AL West

You can all but call this race. Baseball Prospectus has the Rangers at 92% likely to make the playoffs. The Angels and Athletics spit the remaining ~8% of simulations, but right now the Rangers hold the league’s largest divisional lead (8 games) which is more than five times the next closest. It really is hard to see the Athletics or Angels make a legitimate push for the crown and a lot would have to happen for Texas to miss the postseason.

AL East

The Yankees are the next surest thing, at 87%. Tampa Bay is on their heels (80%) and Boston isn’t dead quite yet (25%) meaning, unlike Texas, it’s possible to imagine the Yankees not winning the division crown at this point. The goal for these teams need not be much more than to finish in the top two of the division and assume second place guarantees a wild card berth…

AL Central

…which makes this race all the more vicious. The Twins and White Sox are tied for first place at this point. Most would probably give the edge to the Twins, but the White Sox always find a way to surprise everyone. The only wild card involved will be whether Kenny Williams can work some magic on the waiver wire.

NL East

Believe it or not, the Braves are projected to make the playoffs more often than any other National League team despite having an identical win total to that of the Reds and Padres (and Giants). Their lead over the Phillies is slight, but this Phillies team that has Mike Sweeney and Wilson Valdez starting on the right side of the infield most days isn’t too inspiring, even if they have beat up on Florida and New York since losing Ryan Howard.

NL Central

With last night’s defeat, the Reds’ lead over the Cardinals is down to a game and a half. This very well could be the most difficult race to call in the entire league.

NL West

The Padres might be baseball’s best story this year and they still have the division lead and a 76% shot at the playoffs. The Giants, though, are breathing down their necks, with an equal number of wins and three extra defeats. If the season ended today, both would be in the postseason.

In case you missed it, this morning I went over the mathematics necessary to take the four factors of hitting to the next level. Now, it’s time to put it to good use.

As Eric pointed out in the comments section, the way that the math is done, we could figure out how much a change in one of the factors changes a player’s wOBA by taking the derivative of the new formula for wOBA derived from the four factors equations. However, that’s a lot of work, so instead, as he suggests, I’m going to do this analysis numerically using a little program called Microsoft Excel.

Let’s test run this method on the simplest of targets: the league average player. In this case, we’ll use the league average player from 2009 MLB. In 2009, the league average BB% was 8.9%, the league average K% (K/PA) was 17.9%, the league average POWH (XB/H) was .595, and the league average BABIP was .299. The following chart shows how changes in each variable changes the player’s Four Factors Equivalent wOBA (ffwOBA).

In order to more easily visualize these on the same scale, I looked how changing each statistic by one standard deviation impacts ffwOBA. In this case, one standard deviation for BB% is 3.7%, for K% it’s 7.3%, for POWH it’s .257, and for BABIP it’s .049 points.

The slope of these lines tells us how sensitive wOBA is, at least as predicted by the four factors, to changes in each stat. BABIP is the steepest, as changing BABIP by one standard deviation changes wOBA by 41 points. Next is POWH, which although it isn’t perfectly linear, it’s close enough that we can treat it as such. Changing POWH by one standard deviation changes wOBA by 33 points. One standard deviation change in K rate changes wOBA by 26 points. A player’s wOBA is by far least sensitive to BB%, as a one standard deviation change in BB rate only changes wOBA by 13 points.

My explanation for the small changes in wOBA brought upon by BB rate changes is that increasing BBs, at least in this model, reduce all favorable outcomes (all hits) as well as reducing outs. The reduction in outs is enough to mean that an increase in BB% is a good thing. However, decreasing K% only means decreasing outs, increasing POWH means increasing 2B, 3B, and HR at the expense of 1B, which is a high net increase, and increasing BABIP means increasing all hits at the expense of outs, which is clearly the best of all results.

Through the rest of the week, I’ll be taking a look at some interesting players, hopefully examining how this method performs at the extremes.

In a move more inevitable than surprising, Jack Zduriencik fired Manager Don Wakamatsu, Bench Coach Ty Van Burkleo, Pitching Coach Rick Adair and Mental Coach Steve Hecht from the Mariners yesterday afternoon. Several coaches received promotions to fill the vacant roles, including Triple-A Manager Daren Brown becoming the Mariners’ interim manager.

It seems that whenever a manager is fired, the question of whether he deserved it will arise and usually the first point brought up will be the team’s record to date — usually a poor one — followed by someone countering that a manager rarely has much of an effect over a team’s record. For instance, the Mariners were 42-70 at the time of Wakamatsu’s firing. Was he responsible for that? He wasn’t at fault for all 70 losses. He was probably to blame for more than zero. He was also probably to credit for more than zero of their wins. Where does the scale balance out? I don’t know, but I do find it odd that this sort of back-and-forth is almost exclusively applied to coaches only.

Sticking with the Mariners, earlier this season Eric Byrnes earned his release after a brutal stretch of play. There was some discussion about whether he deserved that release given the roster make up and what his future projections looked like, but I do not recall anyone stating that the Mariners were 11-14 at the time and thus he deserved to be let go.

We don’t apply the same expectations for managers as we do for players, and we shouldn’t. Players are paid to produce on the field and we’ve gotten pretty good at isolating one player’s contributions to a team’s wins so we generally disregard the team’s overall record when talking about a single player. We do not have a good way to evaluate the impact of a manager, though, and so a team’s overall record becomes sort of the default metric.

On its own, using a team’s record as justification for firing the manager implies that he had direct control over said record. I would contend that no matter who helmed the Mariners this season, they were unlikely to post a meaningfully different record. I think most people agree with that. I think most people agree that the brunt of the blame falls on a combination of random variation, the players themselves for not producing up to expectations and on the front office for assembling said players. To those that disagree, however, to those that believe that a manager has — or can have — a major impact on a team’s wins and losses, I have a question. Why are managers paid so little?

We assume that all teams seek to maximize their number of wins for their expenditures. If managers could routinely positively or negatively affect their teams by more than a few wins, then it would stand to reason that they deserve exorbitant salaries.

We do not have good up-to-date data on manager salaries, but as recently as 2007 the average manager made $1.4 million and the median salary was just $850,000 due to Joe Torre’s $7.5 million really busting the curve. Torre no longer makes that much and I doubt there’s been any major inflation in the salaries paid to managers during the past three years. If we apply the same dollar-to-win conversion that we use for players, then front offices are valuing a manager’s contributions to the team’s won-loss record at around a quarter of a single win on average and even the highest-paid managers clock in around a single win worth of salary.

Front offices should have the best insight into how much chemistry and leadership in the clubhouse matters. If it’s too unpredictable to judge, then why use that to justify hiring and firing of managers? If it matters and is predictable, then my question is, why aren’t they paying for it?

Look around the American League and you’ll see teams using the DH spot in a few different ways. Some, like the White Sox and Tigers, use it, or have used it, as a rotating spot that can afford a veteran a half day off. Others, like the Blue Jays, use it for a player without a position, whether the position is filled by someone else or the player himself isn’t particularly good at any one spot. Yet it seems like a good number of teams reserve the DH spot for an aging slugger who, freed from the physical rigors of playing defense, can save their energy for the one thing at which they excel. The Red Sox, Yankees, Rangers, Angels, and Twins employ this strategy.

This past off season four of those teams signed a veteran to fill the DH spot on a more or less full-time basis. The Twins signed Jim Thome with designs of him being a bench player, but knowing that he could fill the DH on a more permanent basis if necessary. The Angels brought in World Series MVP Hideki Matsui to fill the spot vacated by Vladimir Guerrero, who signed on with the Rangers to handle DH duties. The Yankees brought back Nick Johnson, a defensively capable first baseman who moved to DH in an attempt to reduce the physical toll on his oft-injured body.

Despite having signed similar players for the same position, each team has experienced different results with their DHs. This was the gamble heading into the off-season. The free agents all had something going against them. Thome was headed into his age-39 season and had seen his numbers dip for two years after a strong 2007 season. Matsui had his knees drained twice during the 2009 season and despite quality production still presented an injury risk. Johnson had spent plenty of time on the DL in his career, including missing most of the 2008 season with a wrist injury. Vlad missed time in 2009 and had also seen his numbers decline in the last two years.

Faced with this dilemma, the GMs seeking a full-time DH got to work. Two of them filled their spots with apparent cast-offs from other teams. Matsui signed first, going from New York, which sought a DH, to Anaheim, which had let its incumbent DH, Guerrero, leave via free agency. About a month later Guerrero signed a one-year, $5.5 million contract with a $9 million mutual option and $1 million buyout. New York, seeking to get a bit younger, let Matsui walk without a counter-offer, opting instead to sign Johnson, a player whom they had traded for Javier Vazquez, a player they would re-acquire later in December. The Twins already had Jason Kubel as an in-house DH option, but signed Thome to the curiously cheap salary of $1.5 million, with playing time escalators that could bring it to $2.25 million.

Out of the gate Vlad and Matsui looked like winners. In 93 April PA Vlad produced a .374 wOBA while Matsui was close behind at .357. Thome actually led the pack at .415, but that came in just 52 PA, so he add quite as much value as Vlad or Matsui. The Yankees appeared on the short end of this one, as Nick Johnson produced a mere .308 wOBA, which was almost completely based on his 25.9 percent walk rate. His batting average .138, and his ISO, .086, were downright terrible. He was the youngest out of the four, which is a big reason why the Yankees chose him. That completely backfired.

His season wouldn’t last that much longer, though. After just 17 May PA Johnson complained of wrist pain, which resulted in his second wrist surgery in three years. This was a lesser procedure and his return remains a remote possibility, but the signing was a nearly complete loss for the Yankees. The only consolation is that it opened a spot for them to acquire Lance Berkman. He hasn’t had an easy go in New York so far, but his track record suggests that he could provide ample value.

For Matsui, things have turned south. After his .357 wOBA in April he dropped all the way to .248 in March. He does have a streaky tendency, and in the early goings of 2009 he didn’t hit particularly well. To that end he recovered well in June, producing a .389 wOBA. In July and August, however, that has fallen to around .300. That brings his season wOBA to .323, not the stuff of a DH. Manager Mike Scioscia has defended Matsui while he’s slumped, but he has still kept him out of the lineup a few times in the past week.

Through June Vlad looked to be the best of the bunch, as he continued to hit better and better. From his .374 wOBA in April he went to .405 in May and then .437 in June, making him a big part of Texas’s first place run. In June he also uncharacteristically walked 10.7 percent of the time. But ever since he’s slowed down. In 100 July PA he produced a .275 wOBA that comprised a .282 OBP and .130 ISO. Things have gotten even worse in his 23 August PA, where he’s just 5 for 22 with two doubles and one walk. Joey from Baseball Time in Arlington examined the issue, and noticed that Vlad has been hitting the ball the other way lately, perhaps suggesting a slowing bat or timing issue.

Thome, the elder statesman, has actually been the best of the bunch. His wOBA has been over .400 in each month of the season save for May. He doesn’t have a ton of PA, just 232, so he won’t have standout counting numbers, but given the context his 14 homers looks pretty impressive. So does his .404 season wOBA. The Twins can also afford to play him almost exclusively against righties, as he’s hitting them hard this season. Not only does he have a .336 ISO against righties, but he has also walked in 20.7 percent of his PA.

Since he’s been healthy all season and productive for most of it, you might think Vlad would stand out as the WAR leader of the group. You’d be right, of course, as he’s produced 2.1 WAR. But Thome, despite 212 fewer plate appearances, comes in a close second with 1.8 WAR. There is a contingency of Yankees fans who continually scold the front office for signing Johnson over Matsui, but the two have produced identical WAR values this year, 0.1. It goes to show that when general managers have to make choices among a number of flawed players, there’s no real correct answer at the time. We just don’t know what these oft-injured and aging players will produce.

If I told you coming into this season that Derrek Lee was going to have the worst season of his career offensively aside from one half season stint as a twenty-three year old, you probably wouldn’t be shocked to hear that the Cubs were in the lower percentile of runs scored in Major League Baseball. But the Cubs have gotten steady production from a bunch of regular players this year. Geovany Soto, Alfonso Soriano, Marlon Byrd, and Tyler Colvin all have wOBA’s of over .350, with Kosuke Fukudome and Starlin Castro not too far behind. Unfortunately for those who bleed Cub blue, this hasn’t been enough to keep them competitive, and the down years of Lee and Aramis Ramirez are large contributors.

Lee, in 2009, was coming off of his second-best offensive season in the majors when he put up a .412 wOBA (153 wRC+), and his impending free agency led many to believe this would be another huge season for the thirty-four year old slugger. Let’s dig deeper into some of the peripherals behind Lee’s struggles with last year’s corresponding number in parentheses:

BB%: 11.2% (12.4%)
K%: 23.8% (20.5%)
GB%: 39.0% (35.1%)
FB%: 38.3% (45.7%)
IIFB%: 1.7% (4.6%)
LD%: 22.7% (19.2%)
HR/FB%: 10.0% (17.9%)

Some interesting stuff. While it may be obvious to notice a lack of fly balls by Lee this year, which seems to be dangerous for a first baseman playing at Wrigley, the loss has been mitigated by an increase in line drives and a decrease in infield flies. Take those into account and Lee is actually doing better than he was last year in that regard. His HR/FB rate has been a huge problem, which is a career low for Lee. If we use the wisdom behind xFIP on Lee and adjust his HR/FB rate to his career average (16.4%), then he’d be at ~19.7 homers this year rather than just the twelve at which he currently sits. But we know that for hitters, unlike (generally) pitchers, HR/FB is not just a matter of luck but is deeply rooted in skill.

Also, Lee’s BABIP is currently at .292, almost forty points below his career average and with an even wider margin than that for any year he has had since 2005. The disparity is particularly odd considering his LD rate is higher while his infield-fly rate is lower. Here are the breakdown’s of Lee’s BABIPs on batted ball types this season with last year and career averages following:

Grounders: .246, .267, .252
Fly balls: .120, .163, .134
Line Drives: .634, .756, .759

So Lee is “underperforming” on his BABIP on each batted ball type with the worst offender being line drives. Sure, it’s nice that Lee is hitting more of them, but if they’re not going for hits, and especially extra bases, then it’s not as important. I wish we had some Hitf/x to see if Lee is just hitting the ball less hard as of late, but he’s still probably been unlucky to a certain extent. How much of that decrease in batted ball performance is due to bad luck, and how much is due to skill, is a question that well have to wait for more data to roll in to answer.

Mike Minor is a perfect example for why draft day armchair analysis doesn’t work. In 2009, the Vanderbilt lefty went seventh overall to the Braves, amid fairly consistent criticism from pundits. His fastball, at the time, graded out below average for some scouts, and his breaking ball was inconsistent at best. Everyone agreed that Minor had a good (great?) change-up, but while the comparisons people made to Jeremy Sowers would have once been a compliment, Minor seemed more like a late first round pick than someone that should be drafted ahead of Aaron Crow, Alex White, or Kyle Gibson.

Then, suddenly, Minor wasn’t the same pitcher anymore. Or, maybe he was exactly who Braves scouts thought he could be. This kid that wasn’t “dominant” in college — striking out just one batter per inning, and holding an ERA around 4 — was leading the minor leagues in strikeouts. Once a command specialist, who had a 1.89 BB/9 as an SEC freshman, Minor was now wild, with a walk rate of 3.5. Explanations were hard to come by. I assumed it was a mastering of his curveball, a pitch that college coach Tim Corbin told me on draft day last year was quickly becoming a weapon for him. It wasn’t until even later in the season that we found out his velocity had taken a step forward. In the Futures Game, he touched 95 mph. And by that point, Minor was dominating Triple-A.

Yesterday, the Braves called up Minor to open their series against the Houston Astros. I’m a geek for Major League debuts, and seeing as though Mike Minor was opposite Bud Norris — a former breakout prospect of mine, and current xFIP underachiever — it was must watch television for me. Ultimately, and probably unsurprisingly, it was a pretty sloppy game. The Astros won 10-4 after a seventh inning Braves bullpen implosion. Minor certainly gave the team a chance to win: six innings, one walk, five strikeouts. He did find that even Major Leaguers aren’t immune to ball-in-play variance, as two bloop hits and one Alex Gonzalez error were responsible for three of his four runs allowed. Given the overall success of the outing, his FIP (2.44) tells a better story for the start than his ERA (4.50). But that’s hardly a surprise.

Minor was a good study in the difference between control and command: he wasn’t wild, but he wasn’t hitting Brian McCann’s glove behind the plate, either. In Minor’s problem inning, the fourth, his first run came on a bloop double by Carlos Lee. McCann set up further in and up than where the pitch ended up, and while Minor probably didn’t deserve the run, 92 mph belt-high and middle-in won’t get it done at the highest level. Two batters later, his worst pitch of the night came to Brett Wallace, and by his reaction, Minor knew it. Wallace stung the down-the-middle offering, but with topspin, preventing the first home run of both their careers.

Even with the addition of velocity — Minor was 92-94 mph early on, touching 95, before pitching at 89-91 in the 5th and 6th innings — it’s hard to see it becoming a dominant Major League offering. According to Texas Leaguers (I should note that I have some problems with their pitch classifications after one start — what they list as two-seam fastballs were actually changeups), Minor’s whiff rate on his fastball last night was just 3.4%. In multiple at-bats, the southpaw struggled to put batters away with his fastball, giving up a huge percentage of foul balls. Perhaps if he can maintain consistent 92-95 mph, that will change, but we’ll first need to see it to believe it. This was an Astros lineup, after all, that featured Angel Sanchez and Jeff Keppinger hitting second and third, respectively.

But there are positives to take away from this start; namely, that Minor showed a fantastic change-up. The whiff rate of that offering was somewhere north of 25%, and, while he elevated a few, had pretty solid command of the pitch low and away to right-handed hitters. It’s a weapon, and dare I say, it has the opportunity to be one of baseball’s best. He’s a better pitcher than Jason Vargas or Wade LeBlanc, and a different pitcher than Ricky Romero or Jaime Garcia, but the strength of those change-ups is what I’m trying to convey.

In conclusion, while we have to adjust Minor’s long-term projection as a result of the first four months of his minor league season, I don’t want the numbers to have expectations too high. Minor is still more of a #3 starter than anything else, and there’s work to be done on his game. His breaking ball needs work, even though there are signs of a plus pitch there. His fastball is a bit of a tweener: not consistent-enough velocity to blow people away, not good-enough command to hit all his spots. He is close to being pretty damn good, but there is still work to be done. And with the Braves in the height of a playoff race, I’m not sure now is the time to be learning.

I feel like my Four Factors series, which has covered a few interesting hitters, has gone over well here. I felt that it could be more, however, and I believe I’ve taken the first step into making it more than a simple tool or rule of thumb. The following is more of a reference post than an analytical post, and as the title suggests, there will be some math involved here. What I put forth here also suggests a possible addition of a fifth (or sixth) factor, albeit one (or two) that appears to be much less important than the other four.

For the four factors to have more use besides as an at-a-glance hitter evaluation tool, it would have to mean something in terms of runs. For hitting, that means wOBA. A bridge between the Four Factors and wOBA would mean that we could find how meaningful it is that Ryan Howard has seen his strikeouts drop if his power returns to previous form, or how much better my boy George Kottaras would be with a respectable BABIP instead of his current .195 mark.

Of course, BB% and K% can give us raw (or, even better, per plate appearance) numbers for walks and strikeouts. Working to figure out the other four events – 1B, 2B, 3B, and HR – would give us a working estimate of wOBA. This can be done with the use of POWH (XB/H), the version of Isolated Power that only looks at slugging percentage on hits, and BABIP (H/BIP), the other two factors. These four relatively isolated hitting skills can almost completely account for a player’s overall line.

The tricky part comes with estimating home runs, because of the four stats we have, only two of them deal with contact, and of those, one deals with balls in play, excluding home runs. But we can solve for home runs as follows. Follow the jump for the math.

POWH*BABIP = (XB/H)*((H-HR)/BIP) where BIP = PA-BB-SO-HR, or balls in play. Now, it’s time to use some “fancy algebra,” which means a lot of steps. Note that instead of using PA, I use 1, as instead of calculating raw PA totals, I prefer per plate appearance totals for the results.

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