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Calculating Rest of the Season Ratios |
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Chance Favors the Prepared Mind
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Written by Todd Zola
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Tuesday, 09 August 2011 00:00 |
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As has been discussed a few times, it is a misconception that it is nearly impossible to gain or lose points in the ration categories (batting average, on base percentage, ERA and WHIP). I will not regurgitate the arguments, but the primary point is everything is dependent upon the distribution in your league’s standings. However, knowing you can make up the ground and actually doing it are two separate things. Something I have found useful in my efforts to gain points in the ratio categories is having a target ratio in mind that is necessary to get the job done. I can then look at the challenge objectively and determine if I truly have a chance at attain that target ratio. So today’s submission is a downloadable Excel spreadsheet programmed to calculate the target ratio necessary to gain the potential points.
All you need is some general data usually available from your on-line scoring service. To determine the target ERA and WHIP, all you need is the present number of innings pitched your staff has accrued along with your current ERA and WHIP. Then all you need to do is estimate the number of innings you expect your staff to throw the remainder of the season and determine your season-ending target, usually based on your league’ standings and how many places you want to gain. You enter these numbers and voila, the tool will compute the ERA and WHIP your staff needs to attain the rest of the season to finish at your target.
Something I like to do is take my present innings and prorate that total to determine an expected number remaining and set the target ERA and WHIP to see what results. I then ask myself a series of questions to set my strategy. Is the ERA and WHIP realistic? If it is not, and I humbly feel there is no chance I can reach them, I consider lowering the innings and using solid middle relievers instead, assuming I can afford the hit in wins and especially strikeouts. The idea here is replacing lower end starts with solid set up men lowers the likely rest of the year ERA. Similarly, I will check out the wins and strikeouts to determine if I need to increase my starting pitchers to make up points in those categories, then estimate how that is apt to impact the ratios. Instead of entering a target ERA and WHIP, I enter the ratio I expect my amplified staff to achieve to see if I lose too many points in ERA and WHIP. The possibilities are endless. For what it is worth, if your league uses a different ratio like K/9, it will still work just fine.
Also included is a similar tool to compute batting average, on base percentage or whatever hitting ratio your league uses. All you need is the year to date at bats or plate appearances along with your current batting average or on base percentage.
Click HERE to download the ratio tool.
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Last Updated on Tuesday, 09 August 2011 04:51 |
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A Look at the July Pitching Numbers |
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Chance Favors the Prepared Mind
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Written by Todd Zola
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Tuesday, 02 August 2011 00:16 |
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Another month has passed so it is time to continue our look at the pitching peripherals. Obviously, offense remains down, but some suggested as the weather warms, the runs will pick up. Check local listings, but suffice it to say the weather was certainly warm in July.
With respect to fantasy analysis, not much can be done now to game the results. The off season is the time to investigate if there are trends that can be applied to projection theory. But, this does serve as an avenue to remind everyone of something I have been preaching since the spring. In fantasy terms, value is relative. The 50th best pitcher may have superior stats than in the past, but he still impacts your team as much as the 50th best pitcher of previous seasons. His ERA and WHIP may be lower, but so are the totals at each point in the standings. The leaders in ERA and WHIP have lower numbers than in past seasons. Okay, I think there is ample text to get us below the pictured advertisement; here is the monthly 2011 data to date in tabular form along with the same numbers since 2007.
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2011
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ERA
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WHIP
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K/9
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BB/9
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HR/9
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BAbip
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April/March
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3.903
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1.311
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7.09
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3.28
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0.91
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0.290
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May
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3.801
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1.316
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6.92
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3.23
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0.87
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0.292
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June
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3.780
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1.293
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6.91
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3.01
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0.88
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0.291
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July
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4.002
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1.322
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7.23
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3.03
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0.91
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0.299
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2010
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ERA
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WHIP
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K/9
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BB/9
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HR/9
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BAbip
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April/March
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4.199
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1.379
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7.13
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3.66
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0.95
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0.296
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May
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4.174
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1.365
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7.00
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3.40
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0.94
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0.298
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June
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4.137
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1.362
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6.97
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3.17
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0.93
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0.303
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July
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4.100
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1.343
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7.03
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3.12
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1.03
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0.297
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August
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4.012
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1.327
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7.21
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3.10
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0.97
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0.297
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Sept/Oct
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3.894
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1.314
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7.40
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3.27
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0.95
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0.291
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2009
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ERA
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WHIP
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K/9
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BB/9
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HR/9
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BAbip
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April/March
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4.583
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1.440
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6.96
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3.87
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1.07
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0.299
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May
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4.354
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1.395
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6.88
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3.47
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1.01
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0.300
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June
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4.045
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1.342
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6.81
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3.35
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1.05
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0.289
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July
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4.265
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1.373
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6.98
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3.35
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1.04
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0.299
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August
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4.532
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1.406
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7.12
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3.29
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1.17
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0.306
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Sept/Oct
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4.205
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1.391
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7.14
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3.49
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0.97
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0.302
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2008
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ERA
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WHIP
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K/9
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BB/9
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HR/9
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BAbip
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April/March
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4.165
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1.388
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6.41
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3.64
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0.90
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0.291
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May
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4.135
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1.370
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6.82
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3.32
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0.97
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0.298
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June
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4.179
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1.380
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6.81
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3.32
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1.07
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0.297
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July
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4.583
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1.395
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6.93
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3.23
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1.09
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0.304
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August
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4.407
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1.403
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6.92
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3.34
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1.05
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0.305
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Sept/Oct
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4.511
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1.412
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7.10
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3.48
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1.00
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0.306
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2007
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ERA
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WHIP
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K/9
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BB/9
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HR/9
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BAbip
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April/March
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4.123
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1.369
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6.60
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3.52
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0.92
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0.291
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May
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4.375
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1.378
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6.39
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3.25
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0.99
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0.297
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June
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4.512
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1.405
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6.70
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3.24
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1.05
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0.304
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July
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4.497
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1.415
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6.50
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3.31
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0.99
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0.305
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August
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4.596
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1.419
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6.78
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3.26
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1.11
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0.307
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Sept/Oct
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4.699
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1.445
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7.05
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3.44
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1.10
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0.313
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Even though the overall ERA is highest in July, in terms of skills, pitching actually improved this past month. The increase in runs is due to a higher BABIP, resulting in more hits. Hurlers in fact fanned more and walked fewer batters that earlier in the season. Note that homers also remained consistent. There have been some recent instances of a power spike in July.
As alluded to, it is too early to determine why pitching remains improved, but at least in terms of the root skills (K/9, BB/9, HR/9), the Year of the Pitcher continues. Could it be that it is poorer hitting as opposed to better pitching? Sure, especially since there can be a cause and effect dynamic happening. Teams feel they need better defense and they better defenders are weaker hitters. Obviously, PEDs cannot be ruled out. But again, this is a chore for the off season to help hone projection accuracy.
For now, the take home message is the top power hitters are even more valuable than before as they can really impact the delta in the standings since the hitting categories are so tightly bunched. That is, as we have discussed previously, depressed offense results in compressed categorical distribution, meaning the top players can really move the needle, depending of course on the gaps in your unique league.
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Last Updated on Tuesday, 02 August 2011 10:39 |
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Debunking the Myth of the Second Half Player |
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Chance Favors the Prepared Mind
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Written by Todd Zola
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Tuesday, 19 July 2011 00:21 |
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One of the favorite discussion points at this time of the season is what players historically have strong second halves and are therefore acquisition targets and the flip-side, what players usually crash and burn so it is best to get rid of them. This is a concept that has long bothered me as it is my belief that while examples of such players likely exist, the fact they have done it for a few years is not predictive of it continuing to happen. That is, I do not feel it is salient analysis to label a player as “first half” or “second half” and strategize accordingly.
The example I have used in the last involves the flipping of a coin. My argument is if 32 people flip a coin five times, probability dictates that one will flip five heads. One person flipping five heads is therefore expected within the range of possibilities. I use this metaphor for the fantasy baseball population. There are 750 active players at a given time and well over 1200 that are active over the course of the season. Based on sheer randomness, one of 32 could have a better first (or second) half five years in a row. That is somewhere between 25 and 35 players which is a pretty decent amount. And no doubt, the list fantasy enthusiasts come up with each season are replete with these 25 to 35 players. If you want to extend the metaphor further, one of 64 players will repeat their first or second half performance six consecutive campaigns. So, I would even contend that if a player displayed a trend for six or even seven years, it fell within the realm of statistically anticipated outcomes.
The thing is, this sort of analysis is done on players who fared better the second half of LAST season, let alone two or three seasons. If the analysis is spotty over multiple years, it is certainly suspect based on three months of data. Again, I am not contending such a player does not exist. There very well may be players that for one reason or another take a few months to get it going or peter out at the end. All I am saying is it is not sage to look at what Gordon Beckham or Stephen Drew did the second half of last season and target them now, just as it would be a bad idea to get rid of Dan Haren because he always collapses in the second half.
A year or so ago, I made this point in the forums at our friends at Baseball HQ and a couple of guys much smarter than me in this area had their interest piqued and did some of their own analysis. The forum is private so I cannot share every intimate detail, but using Bayesian probability analysis (Google it, I had to), they concluded that for at least an individual season, some first and second half splits feel outside of the expected range of performance level. The player studied was Adam LaRoche, long considered a second half monster. The study did not perfectly address my specific hypothesis, but it was enlightening in that for at least one season, it could be strongly argued that LaRoche was statistically better in the second half and it was not just a case of skills not translating into results, which is so often the case in these instances.
I will conclude this discussion by doing something I often frown upon and deem hack analysis, and that is providing selected anecdotal examples to illustrate my point. The difference is others cite a couple of examples as proof of their argument. I only want to highlight some rather well known players as a means to help convince those not believing the argument that I at least could be correct, as well as point out how some of this due to perception and not reality in terms of skills not wavering, but rather surface stats not being reflective of said skills.
The first player that piqued my personal interest in this realm was Ichiro Suzuki. Those of you that have played this game for several seasons might recall that when he first came over to the States, Ichiro enjoyed better first halves, thus the smarts always advised getting rid of him at the All Star break or thereabouts. Here are his first half and second half numbers, using March to June and July to Oct as the cutoffs.
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2001
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HR
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R
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RBI
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SB
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AVG
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1H
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3
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70
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36
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27
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0.349
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2H
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5
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57
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33
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29
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0.350
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2002
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HR
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R
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RBI
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SB
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AVG
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1H
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2
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62
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28
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21
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0.359
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2H
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6
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49
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23
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10
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0.286
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2003
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HR
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R
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RBI
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SB
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AVG
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1H
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7
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59
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26
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21
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0.340
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2H
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6
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52
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36
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13
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0.284
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2004
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HR
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R
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RBI
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SB
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AVG
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1H
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3
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39
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29
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19
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0.315
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2H
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5
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62
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31
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17
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0.423
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2005
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HR
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R
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RBI
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SB
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AVG
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1H
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6
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51
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27
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18
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0.294
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2H
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9
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60
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41
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15
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0.312
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2006
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HR
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R
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RBI
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SB
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AVG
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1H
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4
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61
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27
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25
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0.350
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2H
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5
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49
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22
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20
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0.295
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2007
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HR
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R
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RBI
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SB
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AVG
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1H
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5
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56
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39
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23
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0.368
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2H
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1
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55
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29
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14
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0.336
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2008
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HR
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R
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RBI
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SB
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AVG
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1H
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3
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57
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21
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33
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0.293
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2H
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3
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46
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21
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10
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0.328
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2009
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HR
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R
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RBI
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SB
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AVG
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1H
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6
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38
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18
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16
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0.373
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2H
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5
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50
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28
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10
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0.333
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2010
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HR
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R
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RBI
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SB
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AVG
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1H
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3
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31
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24
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21
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0.333
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2H
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3
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43
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19
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21
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0.299
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So in his rookie campaign, Ichiro did not display any difference. But in his second and third seasons, he indeed had markedly better first halves. I distinctly recall the pundits suggesting he be dealt before the crash and burn in 2004. Why you might ask? Simple – I looked at his first half and determined he was snake-bit and was more than willing to take advantage of others hastiness and acquired him everywhere I could, and 2004 was a very good year for me. Keep in mind, BABIP had yet to become a household acronym. My point is, I was more focused on what was happening in 2004, and not at all what transpired the latter part of the two previous seasons. I felt a low BABIP with a still-stellar contact rate was a more reliable indicator of future performance, in this of the improved variety than the fact Ichiro struggled the second half of ’02 and ’03.
The next guy that got my dander up when he was constantly called a second half pitcher was Johan Santana. What bothered me was his skills remained consistent one half to the next, but his surface stats, most notably ERA happened to be better for a few second halves. My argument at the time was it is not a sure thing that if you acquire Santana at the break, your ERA and WHIP would benefit. Let’s take a look at some numbers:
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2004
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ERA
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WHIP
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K/9
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BB/9
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HR/9
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BABIP
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1H
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4.3782
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1.1959
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9.12
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2.28
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1.46
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0.297
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2H
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1.2526
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0.7114
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11.48
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2.02
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0.56
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0.208
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2005
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ERA
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WHIP
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K/9
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BB/9
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HR/9
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BABIP
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1H
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3.7768
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0.9732
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10.53
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1.69
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1.04
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0.280
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2H
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2.0308
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0.9694
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8.05
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1.81
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0.68
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0.253
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2006
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ERA
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WHIP
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K/9
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BB/9
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HR/9
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BABIP
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1H
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2.586
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0.9634
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9.43
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1.52
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0.91
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0.274
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2H
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2.9654
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1.0318
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9.44
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2.11
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0.94
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0.272
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2007
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ERA
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WHIP
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K/9
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BB/9
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HR/9
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BABIP
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1H
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2.7632
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1.0439
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9.47
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2.21
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1.26
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0.267
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2H
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3.9429
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1.1048
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9.86
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2.06
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1.46
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0.283
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2008
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ERA
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WHIP
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K/9
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BB/9
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HR/9
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BABIP
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1H
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3.0087
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1.2228
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8.16
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2.53
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1.11
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0.292
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2H
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2.0885
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1.0774
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7.68
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2.31
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0.67
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0.265
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In 2004, Santana’s first year as a full-time starter, he had a markedly batter second half. His skills were improved across the board after June. However, there was also some good fortune involved as his BABIP was quite lucky, leading to more opportunities to pitch from the more comfortable wind-up which may have assisted in the better peripherals.
In 2005, the southpaw’s ERA was better in the second half, but his skills were actually better in the first half, at least in terms of strikeouts and walks. What improved was he kept the ball in the yard post break. While this could be part skill, it is also part good fortune. But, since this was now two straight season of a better ERA in the second half, Santana was labeled as someone to go get for the second half.
But alas, look what happened in 2006. He was the basically the same pitcher both halves, though walking a couple more hitters leading to a slightly elevated ERA and WHIP. The key is he did not have a BETTER second half as many that season anticipated. Knowing many would want to potentially overpay for Santana after the break, I drafted him in a couple of trading leagues and indeed got a king’s ransom for him later. I also had a pretty good 2006.
Real quickly, in 2007, Santana had a much better ERA in the first half, but the difference in skills was not sufficient to account for the disparity, he was a bit unlucky the second half. Then is 2008, his second half looked better but was actually just a tad luckier.
The bottom line is these were two famous examples of the herd feeling a player’s second half fate could be anticipated based a two year trend. But that is all it was, a trend, not a pattern. If someone in your league is willing to overpay for your Mark Teixeira because he is a second half stud, oblige them. If Dan Haren’s owner is looking to rid their staff of the impending struggles, help ease their mind and open your arms to the Angel’s ace. You will not regret it. Well, at least you shouldn’t anyway.
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Last Updated on Tuesday, 19 July 2011 08:40 |
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First Half All-Profit Team |
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Chance Favors the Prepared Mind
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Written by Todd Zola
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Tuesday, 05 July 2011 00:21 |
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Today we are going to take a look at the All-Value team based on first half performance. What I did was take the National Fantasy Baseball Championship ADP and assign dollar values per draft spot based on history. I opted to use the NFBC ADP as opposed to our pre-season projections as a “wisdom of the crowd” exercise. You will not find a sharper group of drafters anywhere and the sample is sufficient to weed out those using odd strategies that could skew an ADP. I kept the analysis simple, just calculating the amount the players earned over what was expected based on their draft spot. All reserves were assigned an expected value of $0.
While it is interesting, not to mention fun to draw conclusions from the results to aid in future drafts, it must be noted that we are only halfway through the season, the trends may change, not to mention there is no guarantee next year’s player pool acts in the same manner as 2011. That said, there are some trends I am going to keep my eye on with the hope it gives me an edge come next spring.
Here is your FIRST TEAM ALL-PROFIT FIRST HALF SQUAD:
And your SECOND TEAM ALL-PROFIT FIRST HALF SQUAD:
With the caveat that the following are presently observations and do not yet have any tangible application to game theory, here are some quick thoughts:
1. I am pleased by the fact that there are not as many pitchers at the upper end of each profit list. One of the dictums most preach is value pitching always emerges. At least through the first half of the season, my preseason suggestion that as a populace, we are getting better at valuing pitching may have legs. Though, we do need to keep in mind the specific populace used here is the NFBC drafter, but, so far, so good. It will be interesting to determine at season’s end if this pattern still holds.
2. It is curious that there are no catchers that are significantly outperforming their expectations. I’m not sure yet how to apply this, but it is worth noting.
3. Something not shown form the above data is the vast majority of the next group of high profit players are outfielders. This lends credence to notion of leaving a couple of outfield spots available to be considered fungible, in search of one or two of these value players.
We will broach this again at season’s end. Good luck to everyone, here is hoping you have a bunch of top second half profit earners on your squad(s)! Later this week, we will take a look at those on the opposite end of the spectrum, those earning the most negative value the first three months.
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Last Updated on Tuesday, 05 July 2011 01:12 |
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