17 Jan

The WAR Room is back again, bringing you the 2014 advanced stats for every Cleveland minor leaguer. With the minor league seasons at an end and the seasons in review finished, The WAR Room moves to ranking the top-100 prospects in 2014 based on performance, with a twist to make the rankings more relevant. Join Jim Piascik as he brings you part five.

Over the past three months, IBI rolled out the year-end rankings for every minor league affiliate in the Cleveland system. Next up, we will be running down the top-100 performers based on those WAR rankings, albeit with a slight twist.

Simply ranking each player based on the raw numbers would have some value, but not nearly as much as when the stats are adjusted for how old the prospect was compared to his minor league level. For example, older prospects like Anthony Gallas, who did well at 26 years old in High-A and Double-A, are downgraded, while younger prospects like Francisco Lindor, who did well at 20 years old Double-A and Triple-A, are upgraded (as if Lindor needed anymore help).

Naturally, if Gallas — or anyone else in his situation — continues to hit like he did in 2014, it will not matter that he was old for his level, and vice versa for young prospects. But overall, accounting for a player’s age relative to level is critically important for judging a prospect’s performance.

Before moving on to the honorable mentions of The WAR Room’s performance-based rankings, first some reminders on what these numbers are, their uses, and their limitations:

It is always important to keep context in mind, just like with scouting. A pitcher who is old for his level using that experience to succeed against young, inexperienced hitters must be taken with a grain of salt; the same goes when looking at these WAR totals.

But it is a useful tool to put each player’s performance into context and look at where they sit in regard to the rest of the league.

For reference on how I computed WAR, a reminder on the problems inherent in the stats, and everything else you need to know, click here. For a refresher on WAR and what it is, click here.

As a reminder, a 0.0 WAR per 162 games is replacement level — otherwise known as the kind of performance an average player from the level below could offer — a 2.0 WAR per 162 games is average, and a 5.0 WAR per 162 games is All-Star level.

Also, the lack of good defensive metrics for the minor leagues means we have to adjust for a range of defensive abilities. To account for this, I will give you each player’s WAR with a qualifier: either poor-defense WAR for a poor defender (-10 runs below-average per 162 games), average-defense WAR for an average defender (0 runs per 162 games), or great-defense WAR for a great defender (10 runs above-average per 162 games).

Additionally, note that pitchers have FIP-based WAR — which is based on peripherals like strikeouts, walks, home runs, etc. — and RA-based WAR — which is based on runs allowed.

One more thing, all “+” stats are averaged at 100. Anything over 100, like 110, is higher and means that player is 10 percent better than the league average. Anything under 100, like 90, is lower and means that player is 10 percent worse than the league average. In the case of any “-” stats — when lower is better, like with ERA — a 90 ERA- means that player is 10 percent better than the league average.

The 2014 year-end season in review for every affiliate is listed below:

And here are the previous editions of these rankings:

Before moving on to #60 through #51, first, a little housekeeping.

A Microsoft Excel snafu messed up the rounding on some players, along with switching a few player’s number of plate appearances. The result of that was a need to reorder the previous players on the list, along with adding a few new writeups to the previously released lists. The old writeups are still accurate, but the ordering of the players is slightly different.

Each of these spots are so close together that the difference between, say, #90 and #89 is essentially negligible. The bigger key is looking at big buckets, like the difference between #50 and #100. But nevertheless, here are the corrected rankings with the writeups of players who had been missed:

#100 Jacob Lee, RHP

Name Lvl Age IP ERA ERA- FIP FIP- K% K%+ BB% BB%+
Jacob Lee A+ 24 72.1 2.99 76 3.82 97 17.40% 88 5.90% 69

Carolina had more than its fair share of older relievers pitching well in 2014, with Lee joining pitchers like Josh Martin, Louis Head, and Grant Sides in that respect. The 3.82 FIP (97 FIP-) as a 24-year-old reliever in High-A is cause for concern, but if Lee can maintain his 2.99 ERA (76 ERA-) and 5.9 percent walk rate (69 BB%+) as he climbs the ladder, the right-hander will be alright. Lee could use a few more strikeouts (17.4 percent strikeout rate, 88 K%+), but as it is, the right-hander was effective in 2014 and should get a chance to try to bring that effectiveness to Double-A this season. Read More…

From Indians Baseball Insider, January 12, 2015

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Posted by on January 17, 2015 in ZX. January 2015


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