Archive for Meta Analysis

Fastball velocity has seemingly received increasingly greater attention over the past couple of years. Perhaps it’s because it just keeps rising. A quick Google search yielded this interesting article detailing recent trends and confirming that average fastball velocity has risen every year since 2008. For us fantasy owners, velocity is important because a spike is often the precursor to a breakout. So let’s talk about a couple of pitchers and what we have seen from their velocity in the early going. These guys have all started just one game, which is as small a sample size as ever. But, velocity stabilizes very quickly, so it’s still worthwhile to discuss.

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It is often said by those who practice the exalted art and science of oral advocacy in appellate courts that, in any given legal case, there are three oral arguments: the one you plan to give, the one you actually give, and the one you wish you’d given. And so it is with the even more exalted art and science of Fantasy Baseball drafting.

We rediscovered this wisdom last week, as we and some two dozen other similarly soigné gentlemen foregathered in Manhattan for a live draft in our NFBC Main Event League: 15 teams, 30 rounds, standard Rotisserie lineups, twice-weekly lineup substitutions for hitters (weekly for pitchers), plain-vanilla 5×5 categories. We were drafting in fourth position. The ultimate hope: triumph not only in this league, but in the overall Main Event competition, encompassing 30 leagues and 450 teams.

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In late February, Lord Appelman unveiled the FanGraphs auction calculator which is loosely based upon a similar calculator named Last Player Picked. I penned a guide to using said calculator which has proven popular. As we delve deeper into draft season, I find that I’m using the calculator in ways that probably weren’t intended. That’s what we’re here to discuss today.

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My inaugural season in the famed AL-Only Tout Wars league didn’t work out very well last year. Although my team heading out of the draft was heavy on OBP (not by design, but because those turned out to be the most undervalued hitters), I ended up finishing just ninth in the category, en route to a pathetic 10th place finish. My offense was decimated by injuries and despite spending $205 of my $260 budget on hitting, I tallied just 28 of 60 possible hitting points. So after a disappointing first showing, did I plan to do anything differently this time around? Yes, but the strategic change was rather minor.

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On Monday, I discussed the results of my 12 team home league. Rather than spend big money on my rotation, I diversified to acquire 11 starting pitchers. By the time spring training is over, I expect to be comfortable with a six pitcher core, which will free me to search for this year’s Michael Brantleys and Corey Dickersons.

Yesterday afternoon, I joined forces with Razzball’s Paul Singman in the Yahoo Friends and Family League. It’s a 15 team snake draft with standard deep rosters and 5×5 categories. The bench is shallow – only three players, and we also have a low 1400 inning cap. I also drafted for Mr. Singman last year, and we narrowly missed first place. Scott Pianowski outstreamed us in the last week.

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In our ceaseless pursuit of Fantasy bargains, we now consider the Cincinnati Reds—or, as one of us will go to his grave calling them, the Cincinnati Redlegs. (This was actually the team’s name from 1954 through 1959, presumably in order to avoid confusion with the crosstown Cincinnati Communists of the Internationale League.)

But we divagate. The Reds in 2014 lost 38 one-run games, the most in a single season by any team in this century. Their record in such games was 22-38, which is likewise abysmal. You’d figure that such a team would have a weak bullpen, and the Reds sure did. They had the fourth worst bullpen ERA in the majors, and no other team was even close to the bullpen’s 11-31 won-lost record. You might also expect that such a team would have a weak closer, but the Reds didn’t. In fact, as you no doubt know, Aroldis Chapman is perhaps the best closer in baseball, and finished second last season in percentage of saves converted. Moreover, Jonathan Broxton, his replacement for the first month or so of the season, converted five out of his six save opportunities.

No, it was the rest of the bullpen—including Broxton, once he became the set-up guy after Chapman returned—that sank the Reds. Chapman, you see, was used almost exclusively (1) in the 9th inning with (2) either the score tied or the Reds holding a narrow lead. If the Reds, courtesy of the bullpen, couldn’t get to the 9th, Chapman wasn’t a factor. Likewise Broxton, in his capacity as closer. Read the rest of this entry »

The aftermath of The Great Valuation System Test continues! Before reading further, be sure you know what was being tested and our process, along with the results:

The Process
The Results

At the end of the results article, I mentioned that although we now have a good idea of which valuation system proved best at converting a player’s statistical line into a dollar value, that doesn’t necessarily mean that the system does the best job for every individual player or player type. So today I’ll look into different player groups and individual players and see if we could find any patterns.

I will be excluding ESPN because their rating number is on a different scale and only using the Razzball – 0% Pos Adjustment & 100% versions. I also don’t have room to fit all the systems in so had to cut down in some manner.

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Yesterday, I shared the exciting news that my project partner Jason Bulay and I have completed The Great Valuation System Test, which involved a whopping 13 fantasy baseball player valuation systems. As usual, I feel like I could have done a slightly better job of explaining our process and goal. Essentially, we wanted to determine which valuation system most accurately converts a player’s statistical line (accounting for his position or ignoring it) into a dollar value. I eagerly awaited all the data so I could run the correlations and had my fingers crossed that the system I use, the REP method, performed well, if not the best. So it’s time to unveil the results.

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It all began with a comment by Jason Bulay, aka The Stranger, on a post I published in January pitting two popular snake draft strategies against each other — best player available and position scarcity:

I posted this as a comment to Cwik’s article yesterday, but I really want to see everybody put their money where their mouth is with all the draft strategy/player valuation theory. Do a draft (or multiple drafts, because small sample size) where everybody will be scored using 2014 stats (or 2015 projections if you prefer). After the draft, add up everybody’s roster using standard 5×5 scoring. See who wins, and what kind of draft strategy really gets the best roster. See who loses, and mock them without mercy.

Not that I disagree with you – your points make sense. But I think this is something we can actually test and I’d love to read about the results, so why not give it a shot?

His idea was intriguing. We’re all very familiar with the various projection systems and know that the masterminds behind them continually strive to improve them. They are also tested every year and we learn which performed best. But valuation systems get none of this treatment, as there has seemingly been little to no progress made on properly valuing players since the original systems were developed and shared.

Jason eventually followed up with an email and after many back and forth messages, we finally settled on exactly what we wanted to test and how we would accomplish our goal.

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The Steamer and I series concludes as I finish with the last starting pitcher comparisons. Today, I check in on two pitchers of whom the Steamer projections are significantly more optimistic than my Pod Projections.

As per SIERA, Zack Greinke is coming off the second best skills of his career, driven in part by a rebound in his slider usage. He’s managed to post sub-3.00 ERAs for two straight seasons now, which has made him the 10th pitcher off the board on average in NFBC drafts. James Shields hit the free agent jackpot by signing with a National League team and remaining in a pitcher friendly home park. He, too, is loved by drafters, who are nabbing him 22nd among starters in NFBC. Let’s see why Steamer and I disagree on these two fine lads.

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