Our draft took place last Saturday, so read on to see how everything played out, and then let us know which nerd writer is the pre-season favorite, and which should start making plans for 2010 (poll shows the first five picks for each team)…

Nerdini Alfredo (1st overall pick)

C: C. Iannett
1B: J. Morneau
2B: R. Cano
3B: G. Atkins, E. Encarnacion
SS: J. Peralta
OF: J. Ellsbury, N. McLouth, N. Markakis, V. Well, D. Young
U: A. Huff
P: B. Myers, J. Chamberlain, J. Saunders, J. Santana, J. Beckett, R. Oswalt, J. Maine, O. Perez

Nerdstradomus (3rd overall pick, done by autodraft)

C: B. Molina
1B: P. Sandoval
2B: D. Pedroia, A. Ramirez, B. Roberts
3B: M. DeRosa
SS: H. Ramirez, D. Jeter
OF: C. N. Lee, C. Quentin, J. Hamilton, C. Crawford, I. Suzuki
U: J. Rollins
P: B. Lidge, B. Fuentes, C. Marmol, F. Rodriguez, J. Soria, J. Broxton, J. Papelbon, J. Valverde

Vorpy McNerd (4th overall pick, autodraft)

C: B. Inge
1B: C. Blake, R. Howard, C. Delgado, C. Pena, C. Davis, D. Lee, P. Fielder
2B: K. Johnson
3B: A. Beltre, M. Reynold
SS: T. Tulowitzki
OF: J. Francoeur, N. Swisher, R. Ibane
U: M. Teixeira
P: A.J. Burnett, A. Pettite, B. Arroyo, Cliff Lee, J. Lackey, J. Verlander

Nerdzah Ball Soup (6th overall pick)

C: V. Martinez
1B: K. Youkilis, P. Konerko
2B: B. Phillips
3B: J. Cantu, T. Glaus
SS: J.J. Hardy
OF: M. Ramirez, M. Holliday, V. Guerrero
U: J. Thome, S-Soo, Choo, C. Hart
P: B. Webb, C. Billingsley, D. Matsuzaka, F. Carmona, G. Mecho, M. Pelfrey, A. Reyes, M. Parra, E. Santana

Prof. Nerdtron (7th overall pick)

C: K. Shoppach, J. Mauer
1B: A. Pujols
2B: H. Kendrick
3B: R. Zimmerman, A. Rodriguez
SS: K. Greene
OF: C.B. Young, C. Granderson, M. Ordone
U: E. Andrus, J. Upton, X. Nady
P: C. Sabathia, C. Carpenter, J. Cueto, M. Rivera, M. Cain, S. Kazmir, B. Jenks, C.R. Young

I Love Nerd York City (8th overall pick)

C: R. Doumit, M. Wieters
1B: M. Cabrera
2B: M. Aviles
3B: E. Longoria, A. Gordon
SS: S. Drew
OF: A. Dunn, A. Soriano, R.J. Braun
U: J. Bruce
P: J. Vazquez, J. Lester, M. Garza, R. Johnson, R. Dempster, Y. Gallardo, C. Kershaw, D. Price, K. Wood

Nerdicus Finch (10th overall pick)

C: B. McCann
1B: T. Helton, N. Johnson
2B: C. Utley
3B: C. Jones
SS: R. Furcal
OF: A. Ethier, B. Hawpe, J.D. Drew, J. Dye, M. Bradley
U: D. Ortiz
P: D. Lowe, R. Harden, R. Nolasco, R. Halladay, T. Lilly, Z. Greinke, M. Buehrle, M. Scherzer, J. Smoltz

Tomorrow is the day we look forward to all winter.  Tomorrow is like Christmas, the 4th of July, and Arbor Day all rolled into one.  Tomorrow is Draft Day.

Some of us will draft a team that provides us with a misguided feeling of self-worth, a false reassurance that we know a little bit about baseball, and one year of bragging rights.  Others will draft a team that provides them with six months of teeth-gnashing and self-loathing.

Join us in the coming week for a recap of our draft, a look back at some memorable draft blunders, and the chance to let us know how awesome or horrible our picks are.

For today, study up on our scoring system…

Scoring System: Head-to-Head Total Point
Positions: C, 1B, 2B, 3B, SS, OF, OF, OF, U, P, P, P, P, P, P

Did they misspell “fantasy” or is there actually a brand of goggles named “Famtasy?”

Were they searching for fantasy baseball and goggle-wearing players?

Do they have a fantasy that can only be fulfilled through a particular pair of goggles?

Was this somehow Chris Sabo related?

Post your ideas in the comments section.

My goal here is to propose a 4×4 roto league that uses only exciting statistics.  After some comments to account for my obvious omissions, I’ll create the league on Yahoo! (which in itself is pretty exciting with that !).  The winner of the league will be the most exciting nerd, a title for all to envy.  Finally, I’ll name the league the Factorial Cup, after the most exciting mathematical operation (too much?  I thought so, but it’s Nerd Baseball so I’m allowed).

Offense

1. Inside the park home runs

I can’t think of a single baseball event more exciting than inside the park home runs.  They always end with a play at the plate, and the drama of being safe or out.  Of course, there can’t be too many of these over the course of a season, but rarity is a key component of excitement.

2. Triples

Last Summer, I finally made it to Shea.  Jose Reyes led off the bottom of the first, as in 2008 the Mets had not been completely drawn in by the idea of Luis Castillo batting lead-off (one man’s banshee is apparently Randolph’s siren).  Reyes promptly knocked the ball the right field wall, and ended up on third.  As the ball rolled to the wall, with Reyes rounding first, the crowd around me rose and started calling ‘triple! triple! triple! triple!’  Triples are exciting.

3. Stolen bases

If I were a klepto, I would say something about the rush of stealing.  I’m not, so I’ll note that Ocean’s 11 is a very entertaining movie built around the concept of stealing.  Not all thefts are quite so classy, but in the end there’s a certain excitement in stealing a base.  The bigger the risk, the more exciting the theft.  Stealing home = ultimate excitement.  Since we’re going for pure thrill in this league, we of course will ignore the consequences of getting caught.

4. Grand Slams

Nerds should take note that walks are not the way to a woman’s heart.  Grand slams, on the other, hand are.  In a  friend-of-a-friend type situation, I once watched a Red Sox game with two women from El Salvador.  This was in 2007, and Papi was on top of his game.  He came to the plate, bases loaded, and I was told “watch Papi right here.”  Sure enough, he hit the long ball.  What I remember is the way Papi was pronounced; chicks dig the long ball.

Pitching

It turns out that pitching isn’t as exciting as hitting.  Defense has some exciting plays (outfield assists/plays at the plate), but this doesn’t fit into the fantasy baseball format.

1. Perfect games/no-hitters

Perfect games are awesome.  But given that odds are there won’t be one this year, I’m content to count the slightly less exciting no-hitters.  No-hitters are even more exciting when they are attached to a beating cancer situation.  I didn’t realize this at the time, but not only did Lester beat real cancer, he also overcame the enormous burden of having (per Papelbon) figurative-cancerous Manny on his team when he threw his no-hitter.

2. Saves

Saves can be really boring.  A three run save in the ninth inning?  Boring.  Game on the line, one run save?  That is tense.  That is exciting.  Unfortunately, I don’t think I can redefine saves on any of the fantasy baseball sites.

3. Strikeouts

See here

4. The Fastball

Okay, I’m kinda stumped here.  So the best I can do is to say that pitchers who can throw the ball really fast are exciting, so average velocity it is.

While looking at the ESPN average draft selections, it’s become apparent that the A-Rod slide has begun.  After having surgery on Monday, his average draft position has fallen from 2nd or 3rd overall to 29.9.  It will almost certainly fall to somewhere within the 3rd round (or below) before the drop ends.

How long you let him slide may go a long way in determining the final standings in your league.  While the risk is certainly real, this feels a little too much like the great Pujols elbow scare of 2008.  The fantasy draft for my main league fell right at the height of the speculation about Pujols missing most of the season…and because of this, he fell to about the 25th pick overall.

Needless to say, that turned out to be possibly the best 3rd round value in the history of fantasy baseball.

At least we know in this case that A-Rod will be missing some weeks. But as long as you can identify a late-round backup that will produce at a reasonable level for the first few weeks, I’ve got to think that letting him slide past the 3rd round will help deliver a steal for someone else.

It also turns out that I’ve been tasked with learning R, an open source statistical package, for work.  Namely, I need to figure out how to do a multiple regression.  This is a statistical technique that allows you to model an outcome based on multiple inputs.  So, to learn how to use the software, I decided to model offense in baseball, and finally figure out how good our league’s scoring system really is (for offense, at least).

Here’s a warning.  It gets really nerdy from here on out, so if you’re just interested in the answer, here it is.  Our method is pretty good.  We overvalue walks.  If you’re for some reason interested in R vs. SPSS, R is an adequate replacement.

So what is this scoring system?  It’s point based for various baseball events.  We’re only talking about the offense, so here we go:

To figure out how our weights stack up, I looked at the 2008 run scoring for each of the teams as a measure of offense (i.e., the outcome variable).  The planned inputs were everything shown above, plus strikeouts.  However, some of the measures ended up being dropped.  Strikeouts didn’t make the final analysis because it’s bimodal (what’s going on there?), and regression demands normal distribution.    Triples are positively skewed, but I kept them in anyway without a transform.  RBI and GDP I dropped because they’re context dependent.  Obviously, RBI and R are closely correlated.  There is nothing Earth shattering by saying that the trick to scoring runs is driving them in. GDP is equally misleading.  A team with a high GDP has a lot of runners on base, which is actually a good thing.  SB and CS didn’t end up being a significant predictor of runs in 2008, so they’re not in the final analysis.  A league that treats steals as anything more than a footnote is interested in Fantasy baseball, not fantasy Baseball.  If your real-life MLB team is built around steals, take a moment and go weep.

I’m sorry I’ve offended the member of the Willy Tavares fan club.  The output of the modeling is in the table below.

What does this mean?  This is a linear model, of the form y=mx + b.  Y, in this case, is predicted runs.  B is the intercept, and listed under each model.  Don’t read into the negative intercepts, it’s mostly a statement that real baseball teams don’t have zero offense.  The rest of those numbers are the coefficients for each event.  In model number five, where all five events are used, we predict that a homerun will produce 1.5 runs, and a double will produce 0.94 runs.  Triples are also productive, but we have to take that 1.46 with a grain of salt because the original data was skewed.  Finally, a walk is not as good as a single, but getting on base at all is still very valuable. (Don’t worry about something being more significant than something else.  Significance is a yes/no proposition.  If something is reported as more significant, that speaks to the confidence in the coefficient, not the magnitude of the coefficient itself).

None of this is actually new, and all it really does is confirm that we’re on the right track with our league weights.  We could stand to knock BB down a bit, I guess.  It’s also pretty amazing that these 5 stats describe 90% of the variance in run production.  Finally, the Twins scored 60 more runs than the model predicts.  They were the only over-productive outlier.   I would expect fewer runs out of them this year.   San Diego and St. Louis under-produced by about 40 runs.  The SD result shows that not including park factors could be a real problem if this were anything more than just fooling around.  STL will probably just score more runs this year.

Now how often can I get nerdly baseball pursuits to count as work?