I was thinking about the one game wild card playoff that's coming to the MLB postseason structure for the first time in 2012, and about the value of that game: how much is a one game playoff worth, in terms of how likely a team is to win the World Series?
I made the assumption that all 10 teams in the postseason are of equal strength, and that the teams that made it through the wild card game would not be adversely affected by having to play an extra game. I created this chart, based off very simple binomial probability data:
It's relatively self-explanatory; each game in each round of the postseason can be given a value, in a very similar manner to WPA, that corresponds to how big a change it will result in in a team's chances of winning the World Series. The value is dependent on the state of the series heading into it; a game 4 with the series at 2-1 is three times more important than one with the series at 3-0.
The chance that a team wins the World Series if it wins the wild card game is 1/8 (given the assumption that all teams are equal), while, obviously, if it loses, it can't win the World Series. Similarly, the difference between winning and losing Game Seven of the World Series is one championship.
After the jump: some more thoughts about the value of postseason games, and a look at how, by combining this with WPA from playoff games, we can create a metric showing a player's contribution to a championship effort.
what looked like a bad signing now looks even worse. From this hit location diagram of Fielder's homers at miller park, it looks like only 8 of his 24 homers at Miller park would go over the fence in Comerica. 
four of his doubles look like easy fly outs
None of his fly outs would turn into homers
So basically, in Comerica, Prince Fielder is a 22 home run hitter with less doubles and triples, and a worse batting average, this looks like an awful signing by the Tigers.
All of these photos were from Katron.org thank you for your awesome tool.
The Hot Stove League heats up with the inaugural Field of Dreams Barnstorming Series, where anything's possible and everyone's on a first-name basis. It's the Sparkies, managed by the late Captain Hook, vs the Bucks, managed by the the only legend to be nicknamed for his post-game habit of lingering in the clubhouse buck naked.
The rules are simple: Each team brings eight position players and five starting pitchers. Five games will be played. No substitutions are allowed. Each pitcher must pitch a complete game, regardless of the score or pitch count.
Study the rosters. Then, based upon your intimate knowledge of baseball history, statistical acumen, and deep appreciation of the always important intangibles (glove size, will they show up in shape or sober?), let us know in the poll below how this will play out. Click on the links if you need to, ahem, refresh your memory . . . or just downright cheat.
The Sparkies
The Bucks* The earlier one
- Pudge* (C)
- Boog (1B)
- Red (2B)
- Pie (3B)
- Stick (SS)
- Babe** (OF)
- Duke (OF)
- Hack (OF)
- Chief (P)
- Rube (P)
- Rip (P)
- Doc (P)
- Dock (P)
** The lesser one
Updated: Thanks everyone for signing up. We got a nice full 14 team league. Should be interesting. Will keep everyone updated with goodies throughout the season.
Chris St. John and I have been talking this over for the past few days. Anyone interested? Click here and type in League ID and password listed below:
| Setting | Value |
|---|---|
| League ID#: | 21430 |
| League Name: | BtBScore |
| Password: | |
| Custom League URL: | http://baseball.fantasysports.yahoo.com/league/btbscore |
| Season Type: | Full |
| Draft Type: | Live Standard Draft |
| Draft Time: | Sat Feb 25 12:00pm PST [ Add to My Calendar ] |
| Live Draft Pick Time: | 1 Minute, 30 Seconds |
| Max Teams: | 12 |
| Scoring Type: | Head-to-Head |
| Player Universe: | All baseball |
| New Players Become Available: | As soon as Yahoo! adds them View List of Forced Players |
| Max Acquisitions for Entire Season: | No maximum |
| Max Trades for Entire Season | No maximum |
| Trade Reject Time: | 2 |
| Trade End Date: | August 19, 2012 |
| Allow Draft Pick Trades: | Yes |
| Waiver Time: | 2 days |
| Waiver Type: | Continual rolling list |
| Can't Cut List Provider: | Yahoo! Sports |
| Trade Review: | League Votes |
| Post Draft Players: | Follow Waiver Rules |
| Max Acquisitions per Week: | No maximum |
| Min Innings Pitched: | 7 |
| Weekly Deadline: | Daily - Tomorrow |
| Start Scoring on: | Week 1 |
| Playoffs: | Week 23, 24 and 25 (6 teams)Note: Week 25 runs 10 days from Sep 24 to Oct 3 |
| Playoff Reseeding: | No |
| Lock Eliminated Teams: | No |
| Divisions: | No |
| Make League Publicly Viewable: | No |
| Roster Positions: | C, 1B, 2B, 3B, SS, OF, OF, OF, Util, Util, SP, SP, RP, RP, P, P, P, P, BN, BN, BN, BN, BN, DL |
| Batters Stat Categories: | Runs (R), Home Runs (HR), On-base Percentage (OBP), Slugging Percentage (SLG), Extra Base Hits (XBH), Net Stolen Bases (NSB) |
| Pitchers Stat Categories: | Complete Games (CG), Shutouts (SHO), Strikeouts (K), (Walks + Hits)/ Innings Pitched (WHIP), Quality Starts (QS), Net Saves (NSV) |
If you have any questions, leave a comment here or tweet me @cobradave
Projecting a players Runs and RBI’s is a pain, and it’s largely considered contextual. So if you’ve got some good hitters hitting in front of you, you’re going to get more RBI opportunities, or good players hitting behind you, more Run opportunities.
With the huge free agent signings this winter, and also with the release of the top 100 prospects (For MLB.com's rankings, http://www.mlb.com/mlb/prospects/watch/y2012/) it got me to thinking, "Is Prince Fielder really only worth two draft picks, even if they're first rounders?" Of course Fielder, Albert Pujols, and C.J. Wilson are worth more than that. So how much is a first rounder worth? Note: All WAR numbers are from Baseball Reference.
Analysts and commentators frequently rave about a player’s ability to hit to the opposite field. Extreme pull-hitters are often knocked by many fans who consider hitting to the opposite field a key indicator of a great hitter. However, some of the best hitters in the game - Albert Pujols, Alex Rodriguez, Ben Zobrist, Carlos Beltran, Paul Konerko, Mark Teixeira, and Ken Griffey Jr. - could be considered pull-hitters: hitters who have pull rates above the 84th percentile, or one standard deviation above the mean, among all players. Thus, I wanted to understand the value of hitters with extreme split tendencies versus hitters without any extreme split tendencies, (spray hitters).
In an earlier fan post at http://www.beyondtheboxscore.com/posts/preview/2049891, StrikeThree! made an error by ascribing Washington JFK Stadium (29,200 sq. ft) foul area to Washington's Griffith Stadium (33,900 sq. ft). for the years 1954-1961. This increase of 1.8% foul area has required an adjustment in data, analyses, and charts. However, the error has had little effect on the general message to date: there is statistical evidence that foul area affects strikeouts by hitters, and by inference, pitchers as well. The magnitude of the effect is yet to be accurately measured, however.
In addition, the error will require a small adjustment in a number of subsequent posts, including those regarding overall foul area, SO/ square foot, etc. These will be performed as time allows.
By adjusting the high-strikeout, high foul area Senators of '54-61 in the analysis, an interesting observation comes to light. If you're a poor club playing in a big stadium at that time (e.g., Kansas City, Washington), the effect of high SO by hitters plus the effect of more foul balls caught on the field (larger foul area) and not going into the stands, isn't a good recipe for success. Only exceptional team pitching might theoretically overcome it. Washington....highest in hitters' SO..... high in foul area....lowest in the American League standings!
I am trying to build a fielding metric using gameday, but I'm not very good with computers. I have mySQL installed, and I want to use baseball on a stick because I can get minor league data for BBOS too and Mike Fast's parser script dosen't work for me. Does anyone know how to use baseball on a stick? I have python installed, but when I try to run the scripts that load the games, nothing happens. Please can someone help me, as I can't use computers for my life.
It is tough to compare two completely different players like Michael Bourne and Albert Pujols. There is no easy way to have all of the categories weigh in and you can just add up there stats and compare them. Homeruns are more difficult to come by than a RBI, so therefore should have more value to each one that a player hits. So what I have created is a method that weighs each individual stat for the players. The stat is called PAR.
I am basing this stat off the average stats ,of my main fantasy league's 8 team standard format, over the past couple years and I found the following averages, 1040 Runs, 1038 RBIs, 272 HRs, 164 SBs, and a batting average of .272. These come from your standard league roster of C, 1B, 2B, 3B, SS, CI (corner infielder), MI (middle infielder), and 5 outfielders. So for the statistic I am going to say that Runs and RBIs have the same weight of 1. I am going to give HRs, a weight of 3.8 (average number of runs/ average number of hrs (1040/272)). So this means if player x hits 26 homers he will have a PAR of 100, you must forget about his other stats for the example. I then used the same method for figuring out the weight of stolen bases which is 6.3 (1040/164).
So as you can see homers and stolen bases contribute more to a player’s PAR than that of RBIs and Runs. So for example a player that posts the line of 10 HRs, 100 Runs, 65 RBIs, and 35 stolen bases will have a PAR of roughly 424. A player who hits 30 Hrs, 100 Runs, 110 RBIs, and 5 SBs will have a PAR of roughly 365. I know there are some of you who are saying that the stat puts too much emphasis on stolen bases, and yes if you draft a team solely based on PAR you may have team that has a good number of base stealers. But you have to think, a player who gives you 50 stolen bases is a huge asset, but his PAR contribution from HRs and RBIs will likely be lacking.
So overall the stat gives you a good idea on how the player performs in the four offensive categories, and how he will contribute to your team.
Preliminary Top 20 Projected PAR
527.1 Jacoby Ellsbury 526.4 Matt Kemp 471.3 Jose Reyes 465.3 Justin Upton 455.3 Hanley Ramirez 422.7 Jose Bautista 416.1 Carlos Gonzalez 413.9 Albert Pujols 403 Dustin Pedroia 395.3 Joey Votto 390.9 David Wright 380.1Miguel Cabrera 374.7 Troy Tulowitzki 372.1 Evan Longoria 366.2 Mark Teixeira 356.9 Prince Fielder 354.4 Josh Hamilton 347.3 Adrian Gonzalez 346.6 Robinson Cano 297.7 Ryan Zimmerman
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