Digging for Gold: Analyzing Data for Undervalued Players - Shortstop

It is absolutely crazy how stacked the SS position is!  As I was doing this post, I kept thinking to myself on how the first 10 SS on the board are very, very good for the most part.  Outside the top 5 or so it goes down a bit, but the position is loaded.  The two players that I will be doing a blind analysis on are again, two players who are far apart in the rankings posted on many websites.  But anyways, let's get digging!

The first chart we will look at will focus on the batter's plate discipline and exit velocities.

	BB%	K%	Z-Swing%	O-Swing%	SwStk%	LA (degrees)	EV 95 MPH+	E.V (mph)	Barrels/BBE	GB%	FB%	LD%
Avg.	8.5	22	67	30.5	10.6	12.3	34.3	87.1	6.4	44.9	22.7	25.1
A.	4.2	11	67.6	35.2	6.1	13.4	23.5	83.9	2.5	36.5	38	25.5
B.	3.4	22.4	72.9	39.3	12	10.4	45.1	90.3	7.8	43.2	33.2	23.7

The first thing you may notice when looking at this chart is that Player B is not a very patient hitter.  They have a well below average in BB% and their SwStk% is also above league average.   On top of that, they also like to chase balls out of the zone.  Not a very good combination.  Player A also doesn't have very good plate discipline, but they also don't strikeout too often.

However, what sets these two apart is how hard they hit the ball.  For instance, Player B is in some elite company with his exit velocity.  He ranks 3rd at his position behind Manny Machado and Xander Bogaerts!  Pretty impressive!  Also, almost half of the balls he hits are over 95 mph!  For Player A, they are one of the weakest at the SS position when it comes to exit velocity and barreling up on the ball.  Not too exciting.

Moving on to Batted Ball data.

	BABIP	GB%	FB%	LD%	HR/FB%	Pull%	Center%	Oppo%	Soft%	Med%	Hard%
Avg.	.300	44.9	22.7	25.1	10	40	35	25	20	50	30
A.	.307	36.5	38	25.5	6.8	35.3	36	28.8	18.8	51.8	29.5
B.	.326	43.2	33.2	23.7	17.5	45.1	26.9	28	15.5	53.9	30.6

As I mentioned previously, Player A has a high tendency to hit fly balls, however due to his weak exit velocity, many of these turn into routine popups.  This plays into the strength of Player B as he has strong exit velocities which result in a higher BABIP.  It is harder to stop a ball coming at you 97 mph than a weak ground at 80 mph.  

Lastly, the Expected Outcomes data.

	BABIP	BA	xBA	OBP	SLG	xSLG	wOBA	xwOBA	wRC+
Avg.	.300	.248	.243	.318	.409	.396	.315	.311	100
A.	.307	.288	.271	.326	.416	.370	.319	.297	97
B.	.326	.281	.273	.309	.446	.448	.322	.321	103

If we were to take out the defense and park factors, Player A actually was expected to have a lower BA than Player B.  Not only that, but xSLG and xwOBA drastically go down as well.  Player A had a good year, but I don't think that will replicate it.  I feel that they hit their peak when it comes to fantasy.

Time for player reveal and final analysis.  Player A is Jose Peraza and Player B is Lourdes Gurriel Jr.  Jose Peraza is ranked higher in my opinion because he steals more bases (premium), but that is about it.  I don't think that he will replicate his 14 home runs and I don't think he will be at a .288 average.  With the better lineup, he might have better counting stats as far as runs and maybe RBI, but that is about it.  Again, I am all about upside.  If I can take Gurriel as my backup SS, then I am pretty happy about that.  Heck, if I load up on other positions, I wouldn't feel bad taking him as my starter.  I am excited to see what he can do in his 2nd year and I hope he makes a leap in his patience at the plate.  If he can do that, we could have something special.

References:

www.fangraphs.com

https://baseballsavant.mlb.com/statcast_leaderboard

www.wikipedia.com