Edgar Renteria, Not as bad as you think

There are calls for Edgar Renteria's head from the peanut gallery. Here is a sampling of comments made over at the Extra Baggs blog when Renteria is in the lineup:

"Why don't we just release Renteria and eat his contract? I would much rather have a downs or Rohlinger up here knowing at least we get some speed and young blood. Renteria is finished."

"I think Bochy has slipped into some fantasy world where he is a coach of a tee-ball team and he makes sure everybody plays. Renteria is the kid who wanders off from his shortstop position, blowing spit bubbles and picking dandelions. "Don't worry little Edgar! You're doing great! Edgar! C'mon back. We'll go for ice cream soon."

"Renteria needs to retire already. I predict at least two double plays from him."

I am not sure exactly what is causing this hatred, maybe it was his poor performance last season because this season he has been better then most shortstops in the National League this season.

To prove it let's play a little game I will call "Where's Edgar?" look at the following list of NL Short Stops with at least 190 PA and try to find Renteria:

Name	BB%	K%	BB/K	AVG	OBP	SLG	OPS	ISO	wOBA
Player 1	8.90%	14.50%	0.68	0.326	0.387	0.504	0.890	0.177	0.391
Player 2	9.40%	17.00%	0.63	0.306	0.375	0.502	0.877	0.196	0.385
Player 3	10.90%	15.70%	0.79	0.293	0.373	0.459	0.831	0.166	0.364
Player 4	7.50%	15.10%	0.56	0.307	0.359	0.445	0.804	0.139	0.343
Player 5	9.40%	15.30%	0.69	0.300	0.365	0.376	0.742	0.076	0.336
Player 6	9.60%	20.00%	0.54	0.268	0.341	0.408	0.749	0.140	0.333
Player 7	9.10%	19.30%	0.53	0.265	0.338	0.401	0.738	0.136	0.330
Player 8	13.70%	18.20%	0.92	0.281	0.379	0.325	0.704	0.044	0.326
Player 9	8.60%	18.40%	0.53	0.252	0.319	0.436	0.756	0.184	0.325
Player 10	5.20%	11.80%	0.48	0.278	0.318	0.410	0.729	0.132	0.325
Player 11	7.90%	17.30%	0.51	0.251	0.318	0.380	0.698	0.129	0.303
Player 12	4.70%	23.70%	0.21	0.255	0.295	0.381	0.676	0.126	0.299
Player 13	7.00%	14.00%	0.56	0.252	0.310	0.355	0.665	0.103	0.293
Player 14	12.30%	11.90%	1.19	0.238	0.334	0.284	0.618	0.046	0.291
Player 15	4.60%	21.70%	0.23	0.247	0.287	0.377	0.663	0.130	0.289
Player 16	5.20%	11.90%	0.48	0.258	0.299	0.339	0.638	0.080	0.288
Player 17	4.80%	12.00%	0.42	0.281	0.318	0.318	0.636	0.037	0.287
Player 18	6.80%	12.70%	0.59	0.252	0.304	0.342	0.645	0.090	0.284
Player 19	2.90%	14.40%	0.21	0.237	0.264	0.366	0.630	0.129	0.278
Player 20	8.00%	15.50%	0.58	0.196	0.261	0.282	0.543	0.086	0.247
Player 21	4.80%	30.20%	0.18	0.212	0.259	0.254	0.513	0.042	0.230

I have sorted by wOBA* and you can see that there are certainly a very wide range of caliber of hitter that have seen significant playing time this season. The leader is at .391 with the player bringing up the rear at a measly .230 the average for an NL shortstop is about.312.

So where does Renteria end up?

He is player number 5.

He hasn't been a spectacular player this season but I don't think that there were any expectations that he was supposed to be. With the comments that are made about him you would think that he would be at the bottom of every measurement that you can come up with for a shortstop.

I think that for a large part the comments are carry over from last season where he was a very poor player and the performance this season has largely been quite especially with Renteria only starting 2-3 days per week.
So to the critics out there, I agree that Renteria has lost a step or two and that he is no longer an elite shortstop. However he is still a valuable player that this season has done something that many Giants hitters in the last few years could not and that is get on base. He has played well enough that he deserves to start 2-3 or games a week and with his current line should perhaps be getting more playing time in the two whole.

Here is the full list of shortstops:

Name	BB%	K%	BB/K	AVG	OBP	SLG	OPS	ISO	wOBA
Rafael Furcal	8.90%	14.50%	0.68	0.326	0.387	0.504	0.890	0.177	0.391
Troy Tulowitzki	9.40%	17.00%	0.63	0.306	0.375	0.502	0.877	0.196	0.385
Hanley Ramirez	10.90%	15.70%	0.79	0.293	0.373	0.459	0.831	0.166	0.364
Starlin Castro	7.50%	15.10%	0.56	0.307	0.359	0.445	0.804	0.139	0.343
Edgar Renteria	9.40%	15.30%	0.69	0.300	0.365	0.376	0.742	0.076	0.336
Felipe Lopez	9.60%	20.00%	0.54	0.268	0.341	0.408	0.749	0.140	0.333
Stephen Drew	9.10%	19.30%	0.53	0.265	0.338	0.401	0.738	0.136	0.330
Jamey Carroll	13.70%	18.20%	0.92	0.281	0.379	0.325	0.704	0.044	0.326
Juan Uribe	8.60%	18.40%	0.53	0.252	0.319	0.436	0.756	0.184	0.325
Jose Reyes	5.20%	11.80%	0.48	0.278	0.318	0.410	0.729	0.132	0.325
Clint Barmes	7.90%	17.30%	0.51	0.251	0.318	0.380	0.698	0.129	0.303
Ronny Cedeno	4.70%	23.70%	0.21	0.255	0.295	0.381	0.676	0.126	0.299
Jerry Hairston	7.00%	14.00%	0.56	0.252	0.310	0.355	0.665	0.103	0.293
Yunel Escobar	12.30%	11.90%	1.19	0.238	0.334	0.284	0.618	0.046	0.291
Ian Desmond	4.60%	21.70%	0.23	0.247	0.287	0.377	0.663	0.130	0.289
Orlando Cabrera	5.20%	11.90%	0.48	0.258	0.299	0.339	0.638	0.080	0.288
Ryan Theriot	4.80%	12.00%	0.42	0.281	0.318	0.318	0.636	0.037	0.287
Alcides Escobar	6.80%	12.70%	0.59	0.252	0.304	0.342	0.645	0.090	0.284
Wilson Valdez	2.90%	14.40%	0.21	0.237	0.264	0.366	0.630	0.129	0.278
Brendan Ryan	8.00%	15.50%	0.58	0.196	0.261	0.282	0.543	0.086	0.247
Tommy Manzella	4.80%	30.20%	0.18	0.212	0.259	0.254	0.513	0.042	0.230

*A little more on wOBA for those who may not know. wOBA was created by Tom Tango for a stat that combined hitting for average, power and plate discipline. The advantage of wOBA over things like OPS is that wOBA weights them in proportion to their actual value instead of evrything weighted equally.

Not all hits are created equal. Batting average would have you believe they are, but think about it: what's more valuable, a single or a homerun? Batting average doesn't account for this difference and slugging percentage doesn't do so accurately (is a double worth twice as much as a single? In short, no). OPS does a good job of combining all the different aspects of hitting (hitting for average, hitting for power, having plate discipline) into one metric, but it weighs slugging percentage the same as on-base percentage, while on-base percentage is actually much more valuable than slugging. To account for all these differences in run values, Tom Tango created wOBA to combine all the different aspects of hitting into one metric, but to weigh them in proportion to their actual value.

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