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3 Free Alternatives to Microsoft Excel Every Fantasy Baseball Manager Should Know

3 Free Alternatives to Microsoft Excel Every Fantasy Baseball Manager Should Know

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Microsoft Excel is my go-to spreadsheet application, but what if you don’t have access to Excel?  After all, it’s expensive to purchase ($100+).  Are you out of luck when it comes to being a data-driven fantasy baseball player?

Hardly.  There are several free options available and they’re more comparable to Excel than you might think.

Microsoft One Drive (Online Access to a Free Version of Excel)

You can set up an online Microsoft OneDrive account free of charge.  This gets you access to a free online version of Microsoft Excel that offers most of the capabilities available in the desktop version.  You can see a screenshot of the program below.

ExcelAlt1

It’s definitely a viable spreadsheet application.  It offers nearly all the built in functions (VLOOKUP, SUM, IF, etc.) of the traditional Microsoft Excel.  It can meet the needs of any basic to moderately complex spreadsheet.

But there are several features I like to include in more advanced spreadsheets (like the sheet created in the SmartFantasyBaseball “Create Your Own Fantasy Baseball Rankings” series), that can’t be utilized in this online version of Excel.  Most notably, you cannot create named cells or named ranges.  Additionally, you cannot set up data validation, like drop down menus.  These aren’t deal breakers, you can likely work around the absence of these items.  But they’re definitely nice to have.

I’m also not aware of a way to link one Excel Sky Drive file to the data in another file saved in Sky Drive.  This would be nice if you have one central Excel file that stores a lot of data and you want to be able to access it from multiple files that will rely upon that data.  I don’t typically link documents together in this fashion, but it’s good to know.  Online Excel files do have certain file size limitations that might make linking necessary (and you won’t be able to do it).

Google Drive (Free Online Access to Google’s Spreadsheet application)

If you have a Gmail account or if you register for a free Google account, you get access to Google Drive and free online file storage.  You then get access to use Google’s free online word processor, spreadsheet, and presentation applications.

ExcelAlt2

In my opinion, Google offers a more comprehensive online solution than Microsoft does. I find file management is a lot easier in Google’s interface.  And within a Google Spreadsheet, you can use some of the advanced features not available in the online version of Excel.  For example, you can create named ranges, link to other Google spreadsheets, and even pull in other content on the web.

I’ve created several complicated spreadsheets within Google documents using named ranges, upwards of 100 tabs, and linking to external Google Spreadsheets documents, and I’ve been very happy with the results.

Open Office (Free Suite Of Office-Like Applications)

I do think Google’s online spreadsheet application is a strong alternative, but no online spreadsheet is going to replace the capabilities of a spreadsheet saved, accessed, and run directly from your own computer.

When working on your own computer (as opposed to a spreadsheet running over the web), the functionality is improved, calculations are processed faster, the program is more powerful, and the usability is much better.  Fortunately, we have OpenOffice, which is a free alternative to Microsoft Office’s product line.  OpenOffice has a spreadsheet, word processor, and presentation application, all available free of charge.

Millions of people use the OpenOffice suite and the look and feel of the programs is similar to older Microsoft Office interfaces.  If you’re used to the Ribbon interface used by Microsoft Office products in the last several years, the menu systems may feel antiquated.  But the program gets the job done.

OpenOffice file formats are generally interoperable with Microsoft file formats, meaning you can save OpenOffice documents and spreadsheets into Office file formats for sharing with Office users.

ExcelAlt3

My Recommendation

I enjoy the more robust experience of running a spreadsheet application from the computer, as opposed to one running of the web, but I really like the experience of using Google Drive and the Google spreadsheet application.  If you’ve read some of my longer posts you’ll know that I’m a fan of using named ranges, and that gives Google a big advantage of Microsoft Excel’s online web app.  I also use Gmail and find the Google Drive app for my phone is very easy to use and access data from.

So I think it comes do to your own preferences and if you prefer a traditional program running on your computer or if you like the mobility, access, and backup benefits offered by a web-based application.  OpenOffice is a very strong (and free!) option to run locally.  And Google wins the web app battle, in my mind.

Conclusion

Don’t think you can’t implement the ideas or use the tools from SmartFantasyBaseball just because you don’t have access to Microsoft Excel.  There are high quality and free alternatives available to you.

Be smart.

 

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Case Study: How To Assess Your Rotisserie League Standings

Case Study: How To Assess Your Rotisserie League Standings

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The case study below looks in detail at how to perform a review of your league standings.  This specific case study is written from the perspective of performing this review in late August, but reviewing and assessing your league standings is a valuable exercise to perform at any point in the season.

This review will guide the moves you make throughout the season.  It’s absolutely critical to have an in-depth understanding of the league standings.  This is not a simple exercise.  It will take time.  But that’s exactly why it’s advantageous and why it can be an advantage for you.

It’s Late August.  You’re In The Middle Of The League Standings.

How many rotisserie points can you legitimately expect to gain in the standings at this point of the season?  If you think you’re out of it, or don’t think you can catch the leaders because you’re in fifth place, I’d encourage you to take a closer look.  You might be surprised at how significantly things can still change.

The Standings

For the rest of this case study, assume the standings shown in the table below.  Let’s look at things from the perspective of the team in fifth place, E.A.B.O.D.  Does this team have a chance to catch the leader?

The first thing worth noting, besides the fact that I play in a nine team league (I’ve been trying to tell you I’m just a “regular guy”), is the first place team has a sizeable lead over the rest of the pack and sits at 68.5 points.  Then things are tightly bunched with four team near the mid-50s.

Standings1

This Is Just A Battle For Second PLace, Who Cares

We’ll take a look at if catching the first place team is possible in a moment.  But even if this is just a four-team battle for second place, taking this battle seriously, applying a well-devised strategy, and making a full-fledged effort to pass the current fourth, third, and second place teams is a valuable exercise.  What if next year it’s a four-team race for first?  Or even a two-team race?  If you’re able to win a four-team race over the last month of the season, next year’s two-team race will seem simple.

I got the idea for this case study while listening to Todd Zola on the August 9th edition of the BaseballHQ Radio Podcast.  His point was that it really doesn’t matter what place you are in the standings.  The exercise of going through a review of your team and the league standings in order to gain a few points is great practice.  Always seek to improve your team.  You’ll learn a lot from these seemingly unimportant battles.

Let’s Take A Closer Look

Remember, with roughly one month to play, we currently sit in 5th place at 52 points.  If we are to somehow pull this miracle off, we would need to reach 69 points, meaning we must somehow climb 17 points in the standings.

The best way to figure out how many points are possible?  Go category-by-category through the standings and figure out what points can easily be earned and those that could be earned with a little luck.  It’s also worth looking at the categories in which we could lose points (easily or due to bad luck).

Starting with runs, we’ve got a total of 830 runs to this point in the season.  Trying to be realistic about how many runs can actually be made up in about one month, we’ll say making up one run a day is possible, but not likely.  More likely, making up 15 runs over the next 30 days is a realistic possibility.  So anyone within 15 runs of our 830 total can be caught, giving us another rotisserie point.

Looking at the actual standings below, only one team is between our 830 runs and the attainable 845 (that’s SpartyOn with 841).  One additional team, The Naturals, is within 30 (at 857 runs to our 830).

Standings2

So that’s one standing point we can realistically gain (catching SpartyOn) and one more we could possibly gain, but it’s unlikely (The Naturals).  Note, if you’re also concerned about being caught in the standings, tracking the points you could potentially lose is another valuable exercise.  There is one team hot on our tails, with 827 R, and two others within 30 runs (805 and 802).

Summarizing the points we could gain or lose:

Standings13

Now extend this exercise out to the remaining hitting categories.  We’ll say anyone within 12 HR can realistically be caught and within 20 could potentially be caught.  Within 15 RBI can legitimately be caught and 30 RBI is possible but unlikely.  10 SB can reasonable be caught, 20 would be possible but unlikely.  And within .003 BA points can be caught, .006 would be possible but unlikely.

Standings3

Pitching Is A Little More Complicated

This particular league happens to have an innings limit of 1,550 innings.  Innings can be manipulated more easily than games played by hitters.  A team could theoretically start streaming a multitude of pitchers and easily increase innings in the short-term, whereas the limited number of lineup spots and days off for hitters prevents you from increasing at bats in the short-term.  This leads to potentially distorted pitching standings.

Look at the current standings below.  Take for instance, The Heat in seventh place.  The team is clearly ahead of everyone else’s pace for innings pitched and will hit the 1,550 cap soon.  The 1,185 strikeouts in 1,364 innings isn’t nearly as impressive as the 1,145 strikeouts the Warriors (eighth place) have in 1,132 innings.  The Warriors need only 40 strike outs in the next 200 IP to catch The Heat.  So we have to take the innings pitched distortion into account.

Standings14

The innings pitched distortion can only affect raw counting stats like W, SV, and K.  Pitching more or less innings can’t directly affect rate statistics like ERA and WHIP.

Looking more closely at wins, we can calculate the rate at which teams are earning wins by dividing wins by total IP.  This gives us “Wins per inning”.  Granted, this is an odd statistic and it’s not useful for many things, but it will help us remove the distortion caused by teams simply having more innings pitched than others.

Our hypothetical team in this case study is highlighted in yellow with 73 wins, or 0.065 wins per IP.  Looking at other teams, we actually have a higher wins per inning than the team with 1,364 innings pitched.  Even though that team has 86 wins, we are earning wins at a faster rate (0.065 vs. 0.063).  Theoretically we can pass this team simply by continuing to start our current pitchers.  Once we get to 1,364 innings, we should have more than 86 wins.

The other team with 86 wins (in 1st place) can’t be caught.  We have nearly the same number of innings (1,129.33 vs. 1,129.66), but they already have 86 wins to our 73.  And because we are in third place for wins (86, 86, then our 73), there are no more points to be made up in wins.

Standings6

(more…)

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Case Study - Weighted Average Probabilities and Ryan Braun

Case Study – Weighted Average Probabilities and Ryan Braun

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Hindsight is 20-20.  We all know this.  And now that Ryan Braun has been suspended for his association in the Biogenesis scandal, it’s easy to to say that we overvalued Braun in our draft preparation.  But let’s look back to what we knew in the preseason and use this as a learning opportunity to apply a lesson in weighted average probability and expected results.

What Did We Know?

News surfaced in early 2013 that Ryan Braun and numerous other players were associated with Biogenesis.  Documents were obtained that showed an official link between the players and the clinic.   There was speculation that the players involved could face suspensions during the season.

We didn’t know much more than this.  Would players miss 50 games?  100 games? Would the suspensions come down during the 2013 season?  Or after?  Could MLB even uncover enough evidence to support suspensions?

What Could Happen?

For Braun, we could reasonably assume he’d be the target of a 100-game suspension. He was nearly the recipient of a 50-game suspension in the fall of 2012, but managed to avoid it on a technicality.  So new evidence could push him from a first-time offender to a second-time offender (and a 100-game penalty).

Let’s Start A Basic Projection For Braun’s 2013 Season

If we are to build a projection for Braun’s 2013 season, a reasonable place to start would be to look at career averages.  Braun played a partial season in 2007 and played at least 150 games in 2008-2012.  So let’s use these last five years of “full seasons” and figure out the average production as our baseline estimate:

WAP1

These average to 154 games, 672 plate appearances, 34 home runs, 105 runs, 109 RBI, and 22 SB.

But What If This Isn’t An Average Season?

We know Braun was nearly caught as a PED user in 2012. So what if he was scared into stopping his use of PEDs?  Can we build this into our estimate?

We don’t have any scientific data to understand the exact effect of PEDs.  So let’s throw out a rough guess and say we think the effect of stopping the use of PEDs would slightly decrease his production.  We’ll say his numbers would remain at 154 games and 672 plate appearances, but he drops to 25 HR, 90 R, 90 RBI, and 20 SB.

To summarize our two scenarios:

WAP2

How Likely Are These Scenarios To Occur?

You might have your own beliefs about the likelihood of each, but for the sake of example let’s say we think Braun is 90% likely to have another year in line with his past five seasons and 10% likely to experience a year where the effect of no PEDs drags his performance down some.

WAP3

And What If He Gets Suspended?

Again, for the sake of illustrating a simple example, assume a 50% chance Braun does not get suspended during the year and a 50% chance Braun misses half the season.

These 50-50 alternatives are subsets of our previous two scenarios.  So the 90% chance Braun has another average year now becomes a 45% chance (90% * 50%) he has a career average year and does not get suspended and a 45% chance he has a career average year and does get suspended.

Likewise, the 10% chance he sees a drop in productivity due to coming off PEDs is split into a 5% bucket of not being suspended and a 5% bucket of being suspended.

Regardless of the scenarios we lay out, we must remain at 100% total probability for all the possible outcomes.  Something has to happen.  And with 45, 45, 5, and 5, we’re still at 100%.

WAP4

Weighted Average Probability, Expected Results

Once you have probabilities for each possible outcome, it’s easy to calculate the total expected result.  We simply multiply the expected statistics for each scenario by the likelihood of that scenario.  This is the “weighting”.

Look at the 5 Year Avg – No Suspension example.  We have determined this scenario has a 45% chance of occurring.  45% multiplied by 672 plate appearances is 302.40.  45% multiplied by 34 home runs is 15.3.  And so on.

Here are the weighted averages of all scenarios:

WAP5

Our overall or actual expectation is the sum of each different weighted scenario.  You can see this total at the bottom of the table above.  After taking all possible scenarios and their probabilities into account, we estimated Braun for 25 HR, 78 R, 80 RBI, and 16 SB.

The Bigger Point

This approach of calculating weighted average probabilities can be used in many different scenarios.  Do you think there’s a 25% chance Troy Tulowitzki plays a full season, a 50% chance he plays 120 games, and a 25% chance he plays 80 games?  Do you think a rookie has a 25% chance of being called up in May, 25% in June, and 50% in July?  Do you think there’s a 50% chance a player will bat leadoff during the year and a 50% chance he’ll bat 9th?  Is there a 25% chance a rookie call-up will break onto the scene and be very productive, a 50% chance he’ll be an average player, and a 25% chance he’ll be sent back to the minors?

In any of these situations, calculate an estimated outcome and weight it using the probability of that outcome occurring.

Be Smart

Thanks for reading and continue to make smart choices.

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Trading Strategy - Take Advantage of Misperceptions

Trading Strategy – Take Advantage of Misperceptions

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What’s done is done.  April, May, June, and July are behind us and we’re heading into the stretch run.  If you’re still able to make trades in your league, here’s a strategy you can employ to squeeze a little extra out of a deal or to get a player at a discount.

Leagues are going to be decided by what happens over these last two months.  Today’s standings are based upon the past, but they will only change due to the statistics that will be earned going forward.  

So as we stand here today, we only care about the future.  This sounds obvious.  You know this.  I know this.  But many owners are unduly influenced by the past, by year-to-date statistics.  It’s impossible to avoid a player’s accumulated season-long statistics.  Visit player X’s profile page online or watch their game on TV and you’re bombarded with graphics showing they have 23 HR, 72 RBI, and 8 SB.  

There’s an opportunity here.

PAST PERFORMANCE IS NOT INDICATIVE OF FUTURE RESULTS

That player with 23 HR, 72 RBI, and 8 SB could very easily be less productive down the stretch than a player that currently has 8 HR, 27 RBI, and 2 SB.  There are players out there that have depressed counting statistics at this point in the season.  Maybe they were injured.  Maybe they have underperformed.  Or maybe they weren’t in the Major Leagues all season.

This is an opportunity for arbitrage.  It’s about finding your own 23 HR-72 RBI guys (especially if you smell a decline coming) and swapping them for other teams’ 8 HR-27 RBI guys.

What To Look For?

If you have a tradeable commodity, a player with impressive accumulated statistics, target players that are due, or are already experiencing, increased opportunity. Additional opportunity can come in many shapes and forms.  It can come from being injured early in the season and now playing regularly.  Or being a bench player early in the year and being pushed into a starting role due to injuries.  Moving to a more valuable spot in the lineup.  Being traded to a more productive lineup.  Being called up from the minor leagues.

It is this opportunity you should be looking for.  Skills remain relatively constant.  But opportunity can change significantly in a short period of time.

On draft day, players thrust into starting roles see their value sky rocket.  They’re termed sleepers.  Everyone in the league battles for them.  When the same thing happens in mid-August, many managers won’t notice.  And if they do, they won’t react in the same rabid manner.

Give Me Names

Here are some examples of players that will have strong opportunities to play the rest of the 2013 season and have depressed counting statistics for some reason (due to injury or being called up during the year).  If you offer up player(s) that have been healthy and played all season in exchange for players like those from the list below, the perceived difference in counting statistics may allow you to earn a slight “discount”.

  • Aaron Hill
  • Brett Lawrie
  • Jason Heyward
  • Curtis Granderson
  • Giancarlo Stanton
  • Carl Crawford
  • Brad Miller
  • Bryce Harper
  • Austin Jackson
  • Nick Franklin
  • Wil Myers
  • Jonathan Villar

A Real Example

You’ll have to determine your team’s needs.  But look at the potential trade below.  To this point in the season, Leonys Martin has stolen 27 bases, good for 10th best in the major leagues.  Jonathan Villar has only been in the major leagues since July 22nd and stolen 11 already.

Granted, Villar could hit .200 and be sent back to the minors in a few weeks.  But you should easily be able to trade a Leonys Martin for a Jonathan Villar AND get something else.  Heck, you could get something significant and Villar might be a throw in.  If you’re trying to gain ground in the standings, this is the type of risk you need to take on.

AccStats1

Don’t Fall Victim

So what can you do if you’re offered a trade like this?  How can you properly evaluate the offer?

The answer is to be forward looking.  Consider completely ignoring the statistics accumulated to this point and use one of the free and reliable rest-of-season projection systems that are available.  These are updated each day and give you only the projected stats for each player going forward.

Conclusion

This won’t always work.  A skilled manager might be as disciplined and forward looking as you.  But many managers can’t help but be overly influenced by the past.  If you can combine the tactic above with other strategies to engineer a trade, you’ll be well on your way to pulling off a deal that can help you down the stretch.

Make smart choices.

 

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Selling Pitcher Wins – Why and How

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At this point in the 2013 season, the Detroit Tigers are 68-45.  The Los Angeles Dodgers are 64-50.  Max Scherzer has a 2.84 ERA and a 0.90 WHIP.  Clayton Kershaw has a 1.91 ERA and a 0.88 WHIP.  So these two pitchers are having phenomenal years and play on teams with similar won-loss records.  We could expect similar won-loss records for the pitchers, right?  You’re smart enough to know that’s not the case.

Scherzer is 16-1 and Kershaw is only 10-7.  In fact, 19 pitchers have more wins than Kershaw.  Heck, Joe Saunders has 10 wins, a 4.58 ERA, and a 1.50 WHIP.  All the while playing for the 53-61 Seattle Mariners.

Need another one?  In 2012, Cliff Lee started 30 games and went 6-9 for the 81-81 Phillies.  At this point in the 2013 season the Phillies are 52-62 and Lee already is 10-5.  In 2012 he had a 3.16 ERA.  To this point in 2013 his ERA is 3.11.

You Can’t Predict Wins

Of course, I cherry-picked these examples.  But they illustrate a very important point.  You can’t predict pitcher wins.  Wins are by far, the most unpredictable of any common fantasy baseball category.

Exploit This Knowledge

Most semi-experienced fantasy baseball players know wins are unpredictable.   But what other choice does a manager chasing a title with a weak score in the wins category have?  They’re faced with the choice of chasing wins or having blind faith that their fortunes will reverse.  This is an opportunity for you.

Look at your roster and see if you have any marketable players in the wins category.  Maybe you can offer a Tillman, Masterson, Lynn, or Latos and upgrade in more steady and predictable categories of weakness.  Or maybe you have an elite Scherzer, Wainwright, Zimmermann, or Verlander and can land an elite player in return.

What To Ask In Return

I love this article by Michael Salfino of Yahoo! where he outlines the pitchers who have been “unluckiest” in the wins category this year.

One strategy you could employ would be to trade a pitcher that has been “lucky” in wins (like a Scherzer) for an “unlucky” player (like a Strasburg) and ask for something additional in return.  Something like an upgraded hitter, a stolen base specialist, or a closer.

Look at your team needs and try to convert the unpredictable wins into a steady and reliable producer in your own category of need.

Follow the principles outlined by Fred Zinkie in “Smart Elsewhere #6“.  Review the league standings and see which teams can benefit the most from a few more wins.  Reach out to them and let them know that your “lucky” wins pitcher is available and may be able to help them climb in the standings.

Conclusion

You can trade away wins even if you don’t have a strong hold on the category.  This is all about converting a very fickle and volatile statistic into one that you can more reasonably predict.  Don’t chase wins.  Let others do it.

Be smart.

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Fun With URLs and Player IDs

Fun With URLs and Player IDs

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Here’s a quick tip that can save you a lot of time if you maintain a spreadsheet of player projections, a list of player rankings, or if you’re simply looking for a more efficient way to do player research.

Hypothetical

URL4Let’s say you have a list of ten free agent pitchers you want to look up at BrooksBaseball.net.  You have a preference for pitchers that limit fly balls (thus limiting home runs), have a variety of pitches at their disposal, and you also want to see if they have an effective strikeout pitch(es).  You also want to view the mix of pitches used by the pitcher over time.  Finally, you wish to limit your research to the last two years of major league data (2012 and 2013 seasons, at the time of this article).

You visit BrooksBaseball.net and this example page below (for Clayton Kershaw) displays fly ball percentage, ground ball percentage, the number of pitches and times each has been thrown, and the whiff percentage for each pitch type over the last two years.

URL1

This example page shows you mix of pitches used, by month, over the last two years.

URL2

Between these two pages, we can do all the necessary research to make a decision about the free agent pitchers.

Looks At the URLs For Those Sites

The key to making this player research a more efficient process is to take advantage of the web address (URL) for these pages.  You can locate the web address for a web page by visiting the site and looking at the path shown at the top of your browser.

URL3

The image above is the URL for Kershaw’s “Tabular Data>Sabermetric Outcomes” page at BrooksBaseball.net.  The tail end of that URL has very important information embedded in it that we can use.

www.brooksbaseball.net/tabs.php?player=477132 &gFilt=&time=month&minmax=ci&var=so&s_type=2& endDate=08/04/2013&startDate=03/30/2012

The “player=477132” component of the URL specifies that this search/web page is for player ID 477132, or Clayton Kershaw.

The “endDate=08/04/2013&startDate=03/30/2012” component restricts the search to 2012 and 2013 season data (up to August 4, 2013, the time of writing).

Here’s the typed URL for the “Usage and Outcomes” page at BrooksBaseball.net:

www.brooksbaseball.net/outcome.php?player=477132 &gFilt=&time=month&startDate=03/30/2012&endDate=08/04/2013&s_type=2

The same concepts for player ID and dates apply.  We can now focus in on the bold red text which differentiates the actual type of page being visited.

A Quick Discussion On Player IDs

If you’re not familiar, there are a number of Player ID systems used to track the statistics of major league baseball players.  MLB.com, Fangraphs, and Baseball Reference all have their own player ID system.

Clayton Kershaw’s player IDs for these three systems are as follows:

ID System Player ID
MLB.com 477132
Fangraphs 2036
Baseball Reference kershcl01

Notice that the MLB.com ID for Kershaw is the same as the ID used at BrooksBaseball.net.  So we know that Brooks Baseball uses MLB.com Player IDs.

If you want to know more about Player IDs, look back to part two of the “Create Your Own Fantasy Baseball Rankings” series where we looked at Player IDs, what they are, and how to use them to your advantage when working with large sets of baseball data. (more…)

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Smart Elsewhere #6 – Trading Strategies from Fred Zinkie

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As Major League Baseball’s trade deadline passes, it’s a good reminder to review your league standings and diagnose any weaknesses in your team that need to be addressed before the stretch run.  Once you understand where you are and where you need to go, hit the trade market.  But how do you ensure you’re making the best deal?  How do you avoid getting frustrated by the often aggravating trading process?

Expert Interviews

The Baseball HQ Radio podcast, hosted by Patrick Davitt, is my favorite resource for learning new strategies and to be exposed to different ways of thinking about fantasy baseball.  In each episode, Davitt interviews at least one industry expert.  And we’re talking respected experts like Ron Shandler (creator of Baseball HQ, among many other accomplishments), Todd Zola (creator of Mastersball.com, fantasy author all over the web), Jeff Erickson (senior editor at Rotowire, expert league winner, writer of the year), and Larry Schecter (five time TOUT Wars winner).  There is a lot to be learned from guys like this.

During the interviews, Davitt inquires about the week’s hot players and current news, but most interestingly to me, he also ask about strategies and approaches the visiting experts use.  The topics can cover things as minor as FAAB usage techniques to as more significant topics like the July 5th trading discussion between Davitt and fantasy expert Fred Zinkie.


Talking Trades

Fred is a participant in the respected TOUT and LABR rotisserie mixed leagues and he is an extremely active trader (it sounds like he’s made more than 20 trades between the two leagues).  At the time of the interview, he was also leading both of these expert leagues.

Someone able to make that many trades, in expert leagues, and use the trades to push him into first place, must have some extremely interesting insight into how to make a trade.

How To Engineer a Trade

I’ll cherry pick some of Zinkie’s recommendations on how to engineer a deal and increase your likelihood of successfully making a trade.

  1. Don’t think about your team first.  Always start with the other team in mind.  
  2. Look over the rosters of the league and identify weaknesses for each particular team.
  3. When contacting the other team, use phrasing like, “It looks like you could use this…”.   Make it about them.  
  4. Verify that they’re interested in making some kind of trade.
  5. Then move forward and identify specific players to be involved in the trade.
  6. If you receive an insulting offer or insulting counter, take a step back and approach the deal realizing there may be a fundamental difference in how they value the players involved.  Maybe they’re really asking for another player or to address another weakness.

Other Thoughts

Fred also had an interesting thought about targeting inherently flawed players, whether it be in the draft or via trade.  Players that might be elite in one category but below average in many other, players with terrible batting averages, players proven to be injury prone, players coming off of P.E.D.  suspensions.  These flawed players will have something about them that certain managers won’t touch, no matter the price.  If you’re in a 15 team league, and because of flaws, at the draft, you’re then only competing against 10 teams instead of 15 for a player, you will end up paying less.  The law of supply and demand, if you will.

Highly Recommended

I highly recommend subscribing to or regularly checking in on the Baseball HQ Radio podcasts.  You can even go back in time and just listen to the expert commentary from old episodes.  The shows are scheduled in such a way that you can easily skip forward to Davitt’s discussion with that week’s expert and then bail on the episode once they move on to discussing only current topics.

Links To The Podcast

 

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Test Yourself - Are You a Stat Chaser?

Test Yourself – Are You a Stat Chaser?

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We’ve all been there.  A player gets hot and hits several home runs in a week or a rookie gets called up and goes 3-for-3 in his first game.  But one of the most dangerous things a fantasy owner can do is “chase” these stats.  When adding players, you don’t get credit for yesterday.

The challenge is to be ahead of the curve.  Pickup the players before the big opportunity comes.  Accumulate the good stats.  Sense when a turn has been made and bail.

The worst thing you can do is continually chase today’s “hot” player, hold him for the next two weeks when he does nothing, and then repeat the cycle.

This is extremely difficult to do.  It’s against human nature.  It makes us feel warm and fuzzy to pick up that hot player.  It’s stressful and fraught with uncertainty to pickup a struggling player that may soon come into opportunity.  How can we fight these urges and determine how well we do at this?

Look Back

Wouldn’t it be great if there were an easy way to look back at every player you’ve owned over the course of the year to see the statistics they earned for your team?  You could see if you’ve owned a bunch of players that performed well below their season averages.  Then you’re likely a “stat chaser”.

Or maybe the majority of players performed in line with the rest of their season statistics and you’re displaying the patience and foresight necessary to succeed at this game.  Regardless, a restrospective review of your players’ performances can indicate if a change is necessary or confirm you’re on the right track.

The Good News Is…

There is an easy way to do this (at least in Yahoo! and CBS leagues).  In Yahoo!, access the “Team Log” link on your page.  In CBS leagues, look up player stats and filter them to show “fantasy” stats, meaning those actually accumulated for your team.

How To View Accumulated Stats In Yahoo!

  1. On your “My Team” page, locate the “Team Log” link.
    retro1
  2. You’ll then be presented with the list of every player you’ve owned over the course of the season and the statistics they’ve accumulated for your team (Forgive the small images.  Click on pictures below to see a full-size image).
    retro2
  3. You want to see players with stat lines consistent to their season averages.  The rate statistics like batting average, ERA, and WHIP are easy to compare.  You’ll have to adjust counting stats for games played, at bats, or innings pitched.   If you stream pitchers or selectively start those on your team, you hope to see an ERA and WHIP below season averages (under the assumption that you’re cherry picking the good matchups).
    retro3
  4. You don’t want to see pitchers with stat lines well worse than season averages.  This indicates one of several things.  You’re either failing at selecting good matchups.  You overreacted to one or two bad starts, accumulating the bad stats and not having the patience to wait for the regression.  Or you’re unlucky.
    retro4
  5. Be on the lookout for stat lines like the one below.  They’re not necessarily problematic if done in the right fashion.  I will often speculate very early on a player that I think will soon come into a favorable situation or opportunity, hoping for a huge payoff.  For this approach, hopefully I’ll also see a handful of “hits” to offset “misses” like this one on Martin.
    retro5

 

How To View Accumulated Stats in CBS

The process to get these statistics on CBS’ website is a little more convoluted, but it’s not difficult to do. (more…)

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Case Study: How I Increased Team Batting Average 30 Points

Case Study: How I Increased Team Batting Average 30 Points

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It was this article by Tristan Cockroft in early May that jolted me.  I was sitting in the middle of the overall rotisserie standings in my mixed league, but was last in batting average by over 10 points.

One of the main takeaways from Cockroft’s article is that if you’re in trouble in the batting average category, you need to recognize this and make changes earlier in the season to address the problem than you do for the counting categories.  This is because batting average is a ratio statistic in which the denominator of the calculation (at bats) continues to steadily grow as the season goes along.  It’s much easier to nudge the batting average 5 points in May than it is in August or September.

I Needed To Act

On April 24th I sat in last place with a .236 team batting average.  Pretty pathetic for a fantasy squad in any format.  At the All-Star break I’ve managed to raise the average to .266 and climb into 6th in the category.  Here’s how I did it.

Date Move Verdict
April 24 Before even reading Cockroft’s article, I made a key move that has really paid off.  Added Matt Carpenter.  Dropped Kyle Seager.  Win
April 28 Still hadn’t read Cockroft’s article.  Took a shot on a potential batting average stud.  Added Nolan Arenado. Dropped Andrew Bailey (he had just gone on DL).  Draw
May 2 Read Cockroft’s article.  I realize it’s time to start making some bold moves to address the problem.
May 5 I’m also last in SB.  Added Dee Gordon.  Dropped Ike Davis. Nothing to lose here.  If Gordon could have hit .220 and stolen bases he would have improved my team average simply by not being Ike Davis.  Draw
May 10 Dropped Wil Middlebrooks.  Added Norichika Aoki.  Win
May 16 Nobody wanted to believe in the hot start.  Couldn’t believe he was still a free agent.  Dropped Josh Rutledge. Added Josh Donaldson.  Win
May 27 Decide it’s time to cut ties with Dee Gordon.  Dropped Gordon.  Added Leonys Martin.  Win
May 28 My dearth of hitting is at least offset by riches in the pitching categories.  Decide I’m willing to overpay for hitting because of significant leads in pitching categories. Trade away Prince Fielder, Adam Wainwright, Mariano Rivera, and Hyun-Jin Ryu.  Received Miguel Cabrera, Brett Gardner, and Matt Cain.  Win
June 9 Painful to look at this one in retrospect.  Decide to go for more proven batting average and SB possibilities.  Dropped Leonys Martin.  Added Shane Victorino.  Loss
June 15 Still need SB too.  Dropped Norichika Aoki.  Added Nate McClouth.  Win
June 21 Still need average and steals.  Cain had started to turn a corner.  Still had a lead in pitching categories.  Traded away BJ Upton, Aaron Hill, and Matt Cain.  Received Hanley Ramirez and Hunter Pence.  Win
July 5 Realize my DL slots are unoccupied.  In preparation for their pending returns, dropped speculation pick of Johnny Giovatella and added Adam Eaton and Derek Jeter.  TBD

Other Items Of Note

It wasn’t just who was added and dropped that made a difference.  We are also constantly making the decision of who to keep.  Who you choose to hang on to, especially during their times of struggle, is just as important.  Here’s a list of players that remained on my team from April 26th to July 14th and their batting averages at those end points:

BattingAvg

Evaluating The Approach

Looking back, you might argue that this was really all based on luck.  And to some extent luck has played a very important role.  But there was also a concerted effort to accumulate strong batting average plays and also a few “lottery tickets”, many of which have paid off.  And in the end, that’s what fantasy baseball is.  Collecting a bunch of assets that we hope will pay off.

I was acquiring Miguel Cabrera for a .330 average and wasn’t expecting .360.  I’m didn’t expect Josh Donaldson to continue to hit over .300, but he seemed like an upgrade over Josh Rutledge.  I continue to look for more “tickets” in Adam Eaton and Derek Jeter, both potential batting average stars (especially in relation to what else you can find at this point in the season).

I made mistakes along the way.  I was in on Leonys Martin very early.  Too early to catch the recent hot streak, and not patient enough to wait around for it to play out.

In hindsight many of these moves seem obvious.  I swapped a bunch of players hitting below .240 and replaced them with guys having the potential to hit for much better average.  But in the moment, it can be difficult to make moves like this.  You want to believe in the potential of guys like Ike Davis, Wil Middlebrooks, and Josh Rutledge.  The key is in realizing when the detriment of a .240 average is outweighing the possible 30 HR from a Davis or 15 SB from a Rutledge.  Recognize when the .280 hitter that will only hit 20 HR is the better fit for your team.

Takeaway

If you have a lot of ground to gain in a category, a concerted effort and a series of thoughtfully guided moves, all carefully aimed at improving that weakness, is your best move.  These don’t all have to happen in a short period of time, but you must constantly be monitoring your team and your place in each category.  Make steady and continuous effort to address weaknesses.

Take chances.  Overpay, using categories of relative strength, if you have to.  Be diligent.  Be relentless.  To borrow and tweak a quote from Mark Cuban’s foreword in “The Extra 2%”, “No one move is likely to make a difference.  But collectively, those moves make the difference between winning and losing”.

Mistakes will be made.  But because you’re making a series of calculated moves that all have a relatively high likelihood of panning out, you will make progress over all.  The wins will exceed the losses.

Thanks For Reading

I know it’s taboo to talk about ones own fantasy teams.  But I believe this exercise was a helpful illustration of what it takes to make significant progress in the standings.

Stay smart.


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Smart Elsewhere #5 – TINSTAAPP with Paul Sporer and Doug Thorburn

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In this edition of “Smart Elsewhere“, we take a look at the TINSTAAPP podcast started recently by Doug Thorburn and Paul Sporer.



About The Duo

Paul Sporer’s work can be found all over the web, but he’s most known for his Starting Pitchers Guide series, his work at Baseball Prospectus, and his own blog, PaulSporer.com.

Doug has a pitching mechanics background and worked for a time at the National Pitching Association and does great work on analyzing MLB pitchers’ mechanics (you can see a great sample here).

Paul and Doug teamed up this year on the 2013 Starting Pitchers Guide.  This guide, originally started by Sporer several years ago, is a lengthy and in-depth look at hundreds of starting pitchers, Paul’s expectations for the season, statistical analysis and more.  He added Doug’s work on pitching mechanics to the guide this year.

About The Podcast

These two team up about once each week and pump out a three or four hour podcast dedicated exclusively to pitching.  It’s a lot to take in, but it’s great content.  The information is not directly from a fantasy baseball perspective, although Paul will very frequently mix in his thoughts and how their discussions relate to fantasy baseball.

One mission of the podcast is to explain that poor pitching performances are not simply the result of bad BABIP luck, unlucky strand rates, or flukey home run rates.  Poor and inconsistent mechanics result in the inability to locate pitches and problems with command and control.  They seek to diagnose the specific reasons why pitchers are struggling and determine if and how things can be corrected.

The 10% Pitch

In an earlier TINSTAAPP episode the two made a passing reference to the phrase “a 10% pitch”.  It was a quick mention, but the implication was that if a pitcher can add a third pitch that can be thrown 10% of the time, that it can have a dramatic impact on the pitcher’s results.

This piqued my interested greatly because as you may recall, over a month ago we learned that Max Scherzer began using a curveball much more frequently than in the past.  He’s throwing it about 10% of the time in 2013.  With this in mind I then launched a quest to find other pitchers throwing new pitches in 2013.

Hearing Doug and Paul mention this “10% pitch”, I needed to know more.  So I e-mailed them to get a better explanation.

The Response

My e-mail was actually read and addressed on the June 25th episode (links below, my e-mail is referenced at about the 1 hour 45 minute mark if you want to hear the audio).  Sporer and Thorburn offer two explanations as to why adding an effective pitch that can be thrown at least 10% of the time is a big deal:

  • Paul points out that besides the fastball, pitchers need to have at least one more effective pitch for facing opposite-handed batters (typically a slider thrown by a right-handed pitcher is effective against right-handed batters, but not as effective to left-handed batters).  So in effect, a pitcher needs a second pitch that is effective to same-handed batters and a third pitch that is effective against opposite-handed batters.  When a pitcher adds a new “10% pitch”, it’s often indicative that they are adding a pitch intended to face these opposite handed-hitters that they currently don’t have an effective second pitch for.  If you consider that this “10% pitch” will be focused on batters on one side of the plate, it’s more than likely a 20% or more pitch to batters on that side (and closer to 0% to the same-handed batters).
  • Doug answered from a straight probability point of view and his response made great sense to me.  He gives the simplistic example of dividing the strike zone into four even quadrants (from the hitter’s point of view:  up and in, down and in, up and away, low and away).  A pitcher with one pitch can allocate pitch location to each of the four quadrants, giving a 25% likelihood that this one pitch will be thrown in a given quadrant.  If you mix in a second pitch, that increases the available options to eight (pitch #1 in each of the four locations, pitch #2 in each of the four locations).  From a probability standpoint, this means a 12.5% likelihood that a hitter could correctly guess pitch type and location.  And if you now add a third pitch, you have 12 options.  This means only an 8.33% likelihood that a hitter could guess pitch type and location correctly.

Applying This

Not only might it be a good idea to revisit the process to find pitchers throwing new pitches to identify those with a new 10% pitch, it’s a great tool to keep in mind for pitchers to target prior to next season.  Sporer and Thorburn spend a great deal of time talking about how Shelby Miller really only has a fastball and a curveball and has not yet developed another 10% pitch.  But you can see from the usage data at BrooksBaseball.net that Miller is working on a changeup.  If he can add this as a legitimate pitch in his arsenal, he may be a top ace as early as next year.

Make smart choices. If you haven’t already done so, please follow me on Twitter if you find the work on this site worthwhile. Thanks for reading.


 Links To The Podcast

 

 

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