Table of Contents

Thursday, June 05, 2008

Wednesday Night Reds Monitor - Through June 3rd, 2008

Sorry it's been so long since the last update, but between finishing up my dissertation and house-hunting, I've had little spare time of late. Might get better after next Tuesday, but probably will not.

This is my regular look at the Reds' season-to-date statistics, with minimal (for me) commentary.


I've tried to include notes below each table about the meaning of some of the more obscure statistics, and many of these stats are discussed in detail in my player value series (see sidebar). But if you have questions please do not hesitate to ask!

NL Central Update
Team W L PCT GB RS* RS/G* RA* RA/G* Pwins W%for90 XtrapW
CHN 38 21 0.644 0.0 330 5.59 237 4.02 39 0.505 104
STL 35 25 0.583 3.5 282 4.69 254 4.23 33 0.539 95
HOU 31 28 0.525 7.0 269 4.56 279 4.73 28 0.573 85
MIL 31 28 0.525 7.0 256 4.35 263 4.46 29 0.573 85
CIN 28 31 0.475 10.0 265 4.50 285 4.83 27 0.602 77
PIT 27 31 0.466 10.5 288 4.96 316 5.45 26 0.606 75
Remarks: RS, RA, RS/G and RA/G are all park-adjusted. Pwins is the PythagoPat predicted wins for each team. W%for90 is the winning percentage a team will need from now on to reach 90 wins. XtrapW is the extrapolated number of wins the team will get, assuming they maintain the same winning percentage.

Since my last update, the Reds have gone a tidy 13-8 (0.619)...they'll have to keep very close to this pace to get to 90 wins this season...runs scored and runs allowed per game are both improved, but both still just rank 2nd to last in the division...they did finally pull ahead of the defensively-challenged Pirates.....the Cubs are in the middle of a nine-game winning streak, and lead the division in both runs scored and runs allowed...sure looks like they're the best team in the division.....Pythagoras thinks that both Houston and St. Louis have a better record than they normally would have.....the Brewers are in the middle of a minor surge, but they have a long way to go...

Hitting
Last First PA BB% K% %LD BABIP AVG OBP SLG ISO OPS PrOPS lwts_RC R/G RAR
Dunn Adam 227 21% 23% 18% 0.261 0.251 0.410 0.549 0.298 0.959 1.081 39.5 7.74 21.7
Phillips Brandon 248 7% 16% 17% 0.296 0.282 0.331 0.520 0.238 0.851 0.821 36.3 5.74 14.3
Votto Joey D 198 10% 17% 23% 0.299 0.281 0.354 0.506 0.225 0.860 0.910 29.7 6.09 12.7
Bruce Jay A 37 19% 5% 37% 0.542 0.552 0.649 0.966 0.414 1.615 1.409 12.9 26.07 11.2
Hairston Jerry 118 6% 14% 30% 0.375 0.327 0.372 0.462 0.135 0.834 0.751 19.2 6.62 9.1
Keppinger Jeff S 163 7% 5% 19% 0.326 0.324 0.373 0.446 0.122 0.819 0.789 22.0 5.62 8.4
Encarnacion Edwin 228 9% 17% 12% 0.248 0.239 0.311 0.449 0.210 0.760 0.790 28.3 4.73 7.4
Griffey Jr. Ken 237 12% 14% 17% 0.274 0.255 0.346 0.397 0.142 0.743 0.794 26.1 4.41 5.5
Bako Paul 151 10% 26% 20% 0.319 0.244 0.320 0.400 0.156 0.720 0.746 16.2 4.13 2.6
Freel Ryan 143 6% 13% 20% 0.342 0.298 0.340 0.359 0.061 0.699 0.666 15.1 4.18 2.5
Ross Dave 63 16% 17% 20% 0.300 0.250 0.371 0.346 0.096 0.717 0.783 7.1 4.65 1.8
Phillips Andy A 6 17% 0% 40% 0.200 0.200 0.333 0.200 0.000 0.533 0.976 0.4 2.86 -0.1
Hopper Norris S 30 7% 0% 14% 0.240 0.240 0.321 0.240 0.000 0.561 0.730 2.6 3.29 -0.2
Janish Paul 28 7% 21% 30% 0.350 0.269 0.321 0.269 0.000 0.590 0.692 1.9 2.64 -0.6
Valentin Javier 46 7% 17% 11% 0.286 0.238 0.283 0.310 0.072 0.593 0.562 3.6 2.89 -0.7
Castro Juan 11 9% 0% 10% 0.000 0.000 0.091 0.000 0.000 0.091 0.647 -0.7 -1.72 -2.0
Patterson Corey 156 5% 10% 14% 0.198 0.200 0.240 0.352 0.152 0.592 0.708 13.1 2.89 -2.7
Hatteberg Scott 61 11% 11% 19% 0.191 0.173 0.262 0.231 0.058 0.493 0.701 2.9 1.72 -3.0
Remarks: PrOPS estimates OPS based on batted ball data, and deviations between the two are often due to "luck." LWTS_RC are estimated runs created based on linear weights. RAR is runs above replacement player, without a position adjustment (that is done with the fielding data). All runs estimates are park-adjusted.

The Reds' linear weights total 276, which is 7 more than they've actually scored (after park adjustments).....Thanks to a spectacular second-half of May, Dunn has taken his typical place as the Reds' top offensive player, and by a considerable margin...perhaps even more impressive is Jay Bruce's debut, which has him at 11 runs above replacement in just 37 plate appearances...I'm choosing to believe that he can continue to have a 37% line drive percentage and a 0.500+ BABIP for the rest of the season--he is Jay Bruce, after all.....Phillips continues to hit well and show nice power, despite his OBP issues.....major drop-off from Encarnacion, who had been the Reds' best hitter the last time I checked in...hopefully he can snap out of it soon......PrOPS thinks that Votto and Griffey have hit slightly better than they've shown.....Jerry Hairson has done a heck of a job as a sub at shortstop...expect that 30% line drive rate to drop though, and his BABIP along with it.....Bako finally cooled down.....Finally, Corey Patterson returns to the roster tonight with (the struggling) Freel headed to the DL...it's worth noting that PrOPS thinks that Patterson's been hitting better than Freel this season, though neither have been good...

Total Player Value (Hitting + Fielding)
Last First Pos RAR Fielding PosAdj TtlValue
Dunn Adam LF 21.7 -1.9 -1.9 17.9
Phillips Brandon 2B 14.3 3.0 0.3 17.7
Votto Joey D 1B 12.7 6.1 -2.6 16.2
Bruce Jay A CF 11.2 1.4 0.0 12.6
Hairston Jerry SS 9.1 -1.4 0.5 8.2
Bako Paul C 2.6 2.3 2.4 7.3
Encarnacion Edwin 3B 7.4 -1.1 0.3 6.6
Keppinger Jeff S SS 8.4 -3.2 1.2 6.3
Freel Ryan CF 2.5 -1.4 0.2 1.3
Ross Dave C 1.8 -1.9 0.9 0.7
Phillips Andy A 3B -0.1 0.3 0.0 0.3
Hopper Norris S LF -0.2 0.2 0.0 0.0
Castro Juan SS -2.0 1.5 0.1 -0.4
Janish Paul SS -0.6 -1.0 0.2 -1.4
Valentin Javier C -0.7 -1.0 0.3 -1.5
Griffey Jr. Ken RF 5.5 -5.7 -1.9 -2.1
Hatteberg Scott 1B -3.0 0.4 -0.5 -3.2
Patterson Corey CF -2.7 -3.3 0.8 -5.1
Remarks: RAR is the same as above, and is park-adjusted. Fielding is the average runs saved estimate between ZR and RZR. Position adjustments are adjustments of the run value of a player's positions, pro-rated for playing time. Total value is just the sum of all of these numbers, and is an estimate of total run value above a replacement player.

Total fielding numbers for the Reds come in at 7 runs below average, which matches up really well to THT's estimate of 10 plays below average.....Dunn tops the list of valuable Reds position players, thanks to his resurgent bat and better-than-typical performance in the outfield thus far.....Phillips is right behind him, however, and his fielding numbers are finally showing his more typical plus performance at second base.....Votto's fielding continues to be rated highly by zone rating and revised zone rating, despite his recent error problems.....Encarnacion showed a heck of a surge in his fielding over the past three weeks, which helped him maintain some value despite his offensive woes.....Hairston's done remarkably well at short by these numbers, despite playing out of position.....It's June, and Ken Griffey Jr. still rates as a sub-replacement player despite being generally healthy.....Finally, Corey Patterson's defensive numbers took a big hit...those skills had been the only value he'd provided to the team, but he can't even claim that anymore...


Pitching

Last First IP K/9 BB/9 HR/9 HR/F %GB BABIP ERA FIP OPSa BsR BsR/G RAR FIPRAR
Volquez Edinson 68.0 11.0 4.8 0.4 6% 55% 0.280 1.46 2.85 0.584 21.5 2.84 22.4 19.6
Harang Aaron 88.7 7.9 2.0 1.2 11% 33% 0.313 3.86 3.53 0.772 45.3 4.60 12.0 18.9
Cordero Francisco 25.7 10.9 5.6 0.7 9% 37% 0.211 2.10 3.62 0.552 7.9 2.78 10.1 3.8
Cueto Johnny 68.7 8.1 2.6 1.8 18% 37% 0.278 5.11 4.59 0.798 38.6 5.06 5.7 6.6
Burton Jared 30.7 9.7 2.6 0.9 10% 53% 0.326 2.93 2.99 0.701 14.5 4.26 2.0 5.1
Bray Bill P 15.7 7.5 5.7 0.0 0% 35% 0.319 2.87 3.25 0.696 7.3 4.19 1.2 2.2
Lincoln Mike 25.7 7.0 1.8 1.8 28% 60% 0.263 5.61 4.46 0.764 12.9 4.52 1.0 0.1
Majewski Gary W 1.7 5.3 0.0 0.0 0% 50% 0.250 0.00 1.82 0.400 0.1 0.70 0.8 0.5
Mercker Kent 13.7 3.9 5.3 0.7 7% 40% 0.279 3.29 4.75 0.750 6.6 4.35 0.8 -0.4
Herrera Daniel R. 1.0 18.0 9.0 0.0 N/A 100% 0.000 0.00 2.00 0.250 0.0 0.28 0.5 0.3
Affeldt Jeremy 26.0 10.4 3.8 1.7 30% 56% 0.319 4.15 4.25 0.785 14.8 5.13 -0.8 0.7
Coffey Todd 15.3 2.9 3.5 1.8 26% 55% 0.278 6.46 6.06 0.879 10.4 6.14 -2.2 -2.7
Belisle Matt 29.7 4.2 1.8 1.2 14% 51% 0.364 7.28 4.27 0.914 23.5 7.13 -4.4 3.9
Weathers David 19.7 6.4 5.9 1.8 18% 35% 0.302 4.58 6.13 0.889 15.2 6.96 -4.6 -3.6
Arroyo Bronson 69.0 8.5 3.7 1.4 15% 36% 0.356 5.61 4.32 0.880 49.2 6.41 -4.6 8.6
Fogg Josh 28.3 5.4 3.2 2.2 17% 38% 0.317 9.85 6.02 0.964 24.1 7.67 -8.9 -4.8
Remarks: BsR are base runs for a given pitcher, based on hitting events (not earned runs). RAR is base runs above replacement player, using a different standard for starters and relievers. Relievers with saves get a leverage-index boost in their RAR value. FIPRAR is a DIPS-based estimate of runs above replacement, using Tom Tango's Fielding Independent Runs as the runs estimator.

It really has been remarkable watching Volquez's season thus far.....Harang continues to be the machine we all know and love, especially if you look at this FIP.....Jared Burton finally has his ERA down to where his FIP said it should have been all along.....Now if only the same could be said for Arroyo and Belisle.....impressive debut appearance by Daniel Herrera--always fun to root for the underdog...

The Reds' pitchers' base runs total 292, which is actually 7 more than they've actually allowed....Using that along with the lwts-estimated 276 runs scored projects the Reds to a 0.472 winning percentage--almost an exact match of their actual record. Neat. Let's hope they can continue to improve now that Bruce and Bailey are here.

Thanks to the Hardball Times, who supplied most of the data used to generate the above reports. ZR data came from ESPN.com.

6 comments:

  1. Justin, if PrOPS thinks Patterson has hit better than Freel, I would count that as a strike against PrOPS. Batting average has its flaws, but a hundred points difference is a heck of a lot, and OPS is not without its flaws, as well. OPS thinks Adam Dunn's career .248/.382/.520 is better than Bill Terry's .341/.385/.506. There's something wrong with that, and it's not just due to the fact that they played in different eras. I'd take Terry's numbers over Dunn's in today's environment as well.

    Maybe a Hegelian synthesis is possible. I'm pushing a stat I call Absolute Average, or ABSO (Average of Batting, Slugging, and On-base). Since OBP is undervalued in OPS, and walks are overvalued in OBP, it makes sense to correct the discrepancy by increasing the weight of the most valuable component of OBP, i.e. hits. Do you think this idea has any merit?

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  2. Well, remember, PrOPS uses batted ball data instead of scorebook data to predict OPS. Batted ball stats tend to stabilize before scorebook data (like hits per AB), so it tends to be a good indicator of who has been luck or unlucky in a given season. It's not perfect, but it's analogous to FIP...and in my experience, is usually pretty reliable.

    The Patterson vs. Freel difference probably breaks down like this: Patterson's line drive rate is almost the same as Freel's, his walk rate is just a tick behind Freel's, he's struck out less often, and he's hit for more power. So by those measures, Patterson's been hitting the ball better than Freel. He's just gotten unlucky, as his 0.198 BABIP would indicate (compare that to Freel's 0.342 BABIP...again, line drive rates are very similar). Even so, PrOPS only has Patterson as a 0.700ish hitter, which isn't particularly good.

    Your critique of OPS is perfectly valid, of course. It works pretty well most of the time, which is why I keep using it around here. But it will miss on some players more than others. That's why I also report a "linear weights per out" stat (R/G), which properly weights all offensive events for the current runs environment.

    As for your absolute average stat...honestly, I don't see any advantage it has over R/G or wOBA. I like to use OPS most of the time because it's easy to calculate, reasonably accurate, and widely used (communication is important). But if you're going to use something else, I don't see why you wouldn't just go ahead and use the most accurate stats, and those are the ones based on linear weights.
    -j

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  3. Even if I admit that PrOPS could be correct that Freel has been lucky to sneak as many line drives through the infield, and Patterson has been unlucky more of his weak fly balls haven't fallen in, so that Patterson's OPS should be higher than Freel's, I could still argue that a higher OPS doth not a better hitter make. (Just wanted to make that point more explicit.)

    My reasons for preferring ABSOlute average over RC/G or wOBA (other than the fact that the linear weights on which they are based will change over time) are similar to the reasons you continue to use OPS. In your own words, it is "easy to calculate, reasonably accurate," and has the potential to be "widely used". The casual fan or broadcaster will never adopt RC/G or wOBA because they are over-complicated, black-box type stats that are difficult to wrap one's head around. Look how long it has taken them to start using OPS. But everyone can see that a complete hitter should hit for average, hit for power, and get on base, and this complete-package quality is what ABSOlute average attempts to quantify.

    Are there websites or databases which would allow me to calculate historical leaderboards for ABSO and other thus-far-unrecognized stats? Baseball Reference appears to only allow you to sort by existing data elements rather than by calculated results.

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  4. Again, though, OPS is widely used and correlates well to team runs scored. So it's pretty good for most purposes. If you're going to improve on its accuracy to any significant degree, you probably will need to go to something that's more complicated to calculate, like wOBA.

    I think a first step with your stat might be to demonstrate that it does indeed correlate to runs scored better than OPS... If it isn't clearly better, then I don't see much point in adopting it, especially given that there are already better alternatives to OPS available.

    As for linear weights being a black box, I'm not sure I see that point. It's pretty simple--take the average number of runs scored per offensive event, multiply by the number of times a batter does each event, divide by PA or outs (depending on how you're setting it up), and tada, you have your statistic. I do see that it takes more time to calculate simply because you have separate multipliers for each event. But in concept, it's pretty simple. And who (aside from people like you and me) actually sits down and calculates OBP or SLG (or wOBA) by hand anyway? Most people just look at tables in their newspaper or on b-ref.

    I don't know of any sites that allow you to sort by calculated results either. But it's pretty easy to download the lahman database, calculate it yourself, and then post the results...
    -j

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  5. Justin,

    What do you think about Dunn's surgery and his better-than-usual fielding thus far? Is it possible that his knee problems were affecting him more than he thought?

    He just seems to be half a step faster and track balls better than he has in the past. That's likely biased sampling, but I don't know how else to evaluate it.

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  6. That's a really interesting point Brad. I have no idea how to tell... His fielding did seem to take a big hit in 2006-2007, though it was never good. So if that's when his knee started bothering him, it might explain his drop in range.

    ...I'm a bit cynical about Dunn's defense, so I think the safest bet is that his fielding will return to his 2006-2007 levels as this season goes on. But your comment gives me at least some hope that it might not, which would be pretty awesome. :)
    -j

    ReplyDelete