So I decided it was time to take a look at how lucky or unlucky the Orioles were on balls in play. So I decided to take a look at each player's BABIP and compare it to their simple xBABIP (expected BABIP although this version is the quick version)
This fanpost was inspiredon Andy Hellicksonstine's article at DRayBays xBABIP Adjusted Lines for Rays Batters in 2009. So after reading it I figured it would be interesting to try and do the same thing for the Orioles. And so I did...in my own way. I ended up using Chris Dutton and Derek Carty's simple xbabip because I do have excel on my computer and mainly because I'm not ready to try using Google Docs. If somebody were to use B Ray's translation it probably would end up slightly different.
So basically I calculated each batter's xBabip (the quick version which uses easily accessible stats to compute) and compared it to the player's actual babip. The results went under the difference column. Than to calculate the number of hits a player gained or lost due to luck you multiply the difference by the at bats. So which players were the unluckiest on the Orioles?
The top 3 unluckiest players were Lou, Robert Andino,Cesar Izturis . However Lou and Andino both had very small sample sizes which means that they are more likely to have more variation with their luck. Anyway I created a table with all the 2009 Orioles players with 30+ at bats. This arbitrary cutoff removed all the pitchers as well as players like Ryan Freel, Justin Turner and Guillermo Rodriguez who all had fewer than twenty at-bats. Table after the jump.
| Player | AB | HR | SO | SB | LD% | #FB | #PU | #GB | xBABIP | BABIP | Diff | #H |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Nick Markakis | 642 | 18 | 98 | 6 | 16.6 | 225 | 15 | 237 | 0.312 | 0.323 | 0.011 | 7 |
| Brian Roberts | 632 | 16 | 112 | 30 | 21.6 | 220 | 16 | 190 | 0.325 | 0.323 | -0.002 | -1 |
| Adam Jones | 473 | 19 | 93 | 10 | 16.5 | 107 | 6 | 211 | 0.335 | 0.310 | -0.025 | -12 |
| Melvin Mora | 450 | 8 | 60 | 3 | 18.8 | 149 | 15 | 167 | 0.308 | 0.285 | -0.023 | -10 |
| Luke Scott | 449 | 25 | 104 | 0 | 17.1 | 150 | 20 | 137 | 0.305 | 0.284 | -0.021 | -9 |
| Aubrey Huff | 430 | 13 | 74 | 0 | 15.6 | 134 | 16 | 170 | 0.309 | 0.280 | -0.029 | -12 |
| Ty Wigginton | 410 | 11 | 57 | 1 | 17.8 | 139 | 18 | 152 | 0.304 | 0.295 | -0.009 | -4 |
| Cesar Izturis | 387 | 2 | 38 | 12 | 20.3 | 104 | 13 | 170 | 0.318 | 0.280 | -0.038 | -15 |
| Nolan Reimold | 358 | 15 | 77 | 8 | 14.4 | 106 | 17 | 137 | 0.313 | 0.320 | 0.007 | 3 |
| Matt Wieters | 354 | 9 | 86 | 0 | 18.5 | 107 | 8 | 113 | 0.316 | 0.359 | 0.043 | 15 |
| Felix Pie | 252 | 9 | 58 | 1 | 20.9 | 73 | 8 | 78 | 0.315 | 0.314 | -0.001 | 0 |
| Robert Andino | 198 | 2 | 47 | 3 | 16.8 | 45 | 2 | 79 | 0.330 | 0.282 | -0.048 | -10 |
| Gregg Zaun | 168 | 4 | 30 | 0 | 19 | 55 | 4 | 56 | 0.310 | 0.276 | -0.034 | -6 |
| Michael Aubrey | 90 | 4 | 10 | 0 | 13.8 | 42 | 3 | 27 | 0.284 | 0.289 | 0.005 | 0 |
| Chad Moeller | 89 | 2 | 16 | 0 | 21.3 | 34 | 5 | 25 | 0.293 | 0.296 | 0.003 | 0 |
| Lou Montanez | 82 | 1 | 16 | 0 | 20.9 | 27 | 1 | 26 | 0.314 | 0.215 | -0.099 | -8 |
| Jeff Fiorentino | 64 | 0 | 16 | 2 | 28 | 13 | 2 | 23 | 0.327 | 0.375 | 0.048 | 3 |
| Oscar Salazar | 31 | 2 | 4 | 0 | 7.4 | 8 | 0 | 17 | 0.325 | 0.440 | 0.115 | 4 |
So looking at this table one might ask why are all these various stats such as stolen bases, home runs being presented here. Basically all the stats before xBABIP are what are used to calculate the xBABIP. At bats are used instead of plate appearances because we want only the data surrounding balls being put into play via contact with a bat (hence the name batted balls in play or BABIP). Strikeouts are included for the same reason. I'm not totally sure about homeruns, it might be an easy way to include power. SBs are used to calculate the rough speed of a player. This means that some players on the Orioles are probably being discounted as slower than they are, in particular I'd guess Wieters and Nick. The rest of the numbers are batted ball types whose use should be obvious in calculating expected BABIPs.
in reading the table one should note that the positive difference and hits mean that the player was that amount lucky this season. Negative hits are the number of hits that player lost due to luck. For players who played with other teams like Zaun I only used the partial season that they spent with Baltimore. This means that we don't see Salazar's regression from being a hall of fame hitter to being an above average hitter during his entire season but we can tell how well our players played while as Orioles
Anyway if one totals up the numbers one will find that the Orioles lost 55 hits due to poor luck. Most of the Os were victims of poor luck. In fact it seems to be easier to look at which players were lucky. Matt Wieters appears to have been the luckiest of our player although since he didn't steal a base his speed may be discounted a wee bit. Nicky and Reimold were slightly lucky too. That accounts for all three regulars who were lucky. Oscar Salazar had an incredibly lucky week (what else can you say when a player has half as many homeruns as strikeouts and batted over 400). Fiorentino was also somewhat lucky. We should see some regression from them next year. Fortunately we should also see the rest of our lineup improve their luck. The good news is that Derek Carty at the hardballtimes showed that quick xBABIP does a pretty good job at predicting a player's babip the next year. It was second-tier on par with marcels projections. This means we should see some luck bounce our way this year.
A few key players who stand out:
Melvin Mora: Looking at Melvin Mora's xBABIP makes you feel bad for the guy. If he hadn't been unlucky his batting average and on-base percentage would have been right in line with the last few years. With that he might have been able to catch on somewhere. Hopefully he'll end up playing for a contender and have a lucky year babip-wise.
Cizzy: Our light-hitting shortstop should have provided a bigger boost to the lineup than he did this year. Expect a slightly better year out of him next year. If we get that we may have a decent-hitting bottom of the lineup instead of the rally-killing black hole we had in 2009.
Adam Jones: In the first half of the season fangraphs pointed out Adam Jones as a player being fueled by an artificially high BABIP. In the second half he regressed becoming unlucky for the year. Bummer. Part of this could have been because of his injuries slowing him down.
Special thanks to FlimtotheFlam's post on how to make nice-looking tables over at vivaelbirds (I probably could do it by hand but I always hated making tables. Plus the last time I made them was probably about 5 years ago. So thanks again)




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