A few moments ago, I read a tweet from an old high school nemesis – Sean Doolittle. The topic of the tweet didn’t have anything to do with this post. His comment sent me down a mental rabbit hole, wondering what I’d say to him if we were to meet again. Sean was always an approachable rival, and there were a few occasions when we trained together at an indoor facility (it’s bothering me that I can’t remember the name of it). However, I was awkward, shy, and probably not very memorable. I don’t foresee a budding bromance in our future, even if we were to be re-introduced.

That got me thinking about who I was as a player back in my prime, and what I wish I knew then. I played competitive baseball through college. I attended a D-III school in St. Paul, Minnesota not known for sporting prowess. My recruiting class consisted of me, a lazy catcher, and two walk ons. The others all quit after freshman year. The best I can say about myself is that I contributed. For the first half of my junior season, I was actually quite good. I spent most of my college career pitching through arm injuries. I’m still pitching through those same, slowly worsening injuries.

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Over my many years of fantasy experience, I’ve come to recognize two methods of building a roster. Method 1: an owner targets very specific players and fills around those as needed. Usually, the owner aggressively shops those filler players. Method 2: Every player is treated as a generic asset, sorted into classes. Today, we’ll talk about the pros and cons of both approaches.

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Yesterday, I participated in a 12-team NL-only auction league hosted by CBS (full analysis available soon from CBS). To add a wrinkle to the experience, I decided to try to construct an average team. No studs, but especially no scrubs. Just spend as close to $11.3 per player as possible. The main reason for this approach is that I wanted to stay away from the bottom feeders common in “Only” auctions. I was looking for regulars across the board. The strategy fell apart as my fortitude and simple rules failed.

First off, I wasn’t able to do much auction planning since I found out about it less than a week ago. Additionally, I didn’t want to use the traditional spread-the-risk approach of a bunch of $20 players. Mine idea was a No Scrubs approach. With $20 players, several $1 players enter the team. I wanted semi-talented players with jobs for every position.

After creating projections using the SGP method, I had to come up with an auction framework. In their book, Simple Rules, Donald Sull and Kathleen Eisenhardt go over how to create and utilize simple rules. Here their basic premise.

You want to make the rules as simple as possible to increase the odds that you will follow them. You can also limit your rules to two or three … to increase the odds that you will remember and follow them.

All right, I decided to go with just two rules.

1. Targets players between $5 and $17 ($11 +/- $6). I would not be able to get every player for exactly $11, so I was going to need some leeway.
2. Don’t overpay or reach for players.

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Many years ago, before I ever dreamed of becoming a fantasy sports analyst, I dreamed of competing in industry leagues. I had no idea how people were chosen and no idea how exclusive they were, but I had a dream that one day I would win Tout Wars, LABR, or CBS. I never thought it would actually happen, but when I joined the industry in 2014, that dream returned. I then learned that there were tons of industry leagues. Many were not exclusive, but those big three were. I figured it would take me the better part of a decade to get in. So, I started my own, the Bay Area Roto Fantasy league (BARF), which drafts its second season in about ten days. However, I still dreamed of being in one of the big three. Read the rest of this entry »

My Tout Wars prep continues. I have already examined the league’s historical aspects which I have used to create initial auction values and a draft outline. With the initial projections out of the way, I am refining them. One step in this process is to find the replacement level player and adjust players who will miss time accordingly.

The concept behind the replacement level player is fairly simple. If a good player is expected to miss significant time, his fantasy value is based on just the games he is expected to play. For the games he misses, some lesser player (replacement level player) will fill. The better player’s total value will be both his and the replacement player’s contribution.

For example, I don’t expect Yoan Moncada to get called any earlier than the Super Two deadline around June 1st. For the months he’s in the minors, a less talent replacement level player will be subbing in for him. The same idea works with pitchers. Tyson Ross is expected to miss at least a couple of months so a replacement is needed until he gets healthy.

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Last week, our own Brad Johnson discussed unpredictable auction values in “Rationality Will Ruin You”. I 100% agree with his premise. Unexpected inflation exists but so does a solution. By charting out the desired and the potential outcomes before an auction, an owner can remove a ton of auction frustration.

Brad examined the elite player section of the draft where the actual auction values are higher than most people’s predicted values. Owners refuse to pay these high values but instead end up spending their resources on near replacement level talent. The following simple chart helps an owner deal with the problem along with uneven hitter/pitcher mix and outlining a personal auction strategy. The process is similar to the one used in Winning Fantasy Baseball by Larry Schechter but with a few more additions. Here’s the procedure.

Step 1. Get auction values

This step could be as simple as using our auction calculator or creating your own projections like our own Mike Podhozer does. To set the pitcher/hitter mix, use the league’s historic mix or just go with standard 70/30 split.

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So far in my Tout Wars preparation series, I’ve documented the league’s draft tendencies and the stats needed to win. Today, I’ll create the framework for player pricing. Along the way, I will show how there is no position scarcity except with catcher. At least for this league

Completing this step brings the preparation is laborious, but necessary. Once it’s done, I can spend most of my time evaluating players and their projected playing time.

For evaluating players, I utilize the Standings Gain Points (SGP) method. I previously outlined the procedure and it‘s the same method Larry Schechter recommends in his book, Winning Fantasy Baseball. Normally, this procedure is fairly straight forward since I’ve historically used three-year average values. Last year’s offensive explosion complicates the math. With more offense available, home runs, Runs, and RBIs become less important. Predicting 2017’s run scoring environment is impossible so I won’t for now. I feel I need to use a weighted average system with 2016 getting the most weight but I am just not sure how much to weight them. To get the process started, I will use the average standings from 2014 to 2016 for this work.

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I’m continuing to step through my Tout Wars auction prep. Last week, I broke down the league’s draft including the pitcher/hitter mix and some ownership trends. Today, I am going to examine the league’s final standings to see what it takes to win.

Every owner may try to win every category but that approach is completely unrealistic. I believe an owner should never win a category if they are behind in any other one. Every bit of distance between them and second place is a waste. Get to second in every category and then starting taking over the top spots. There is no reason for an owner to win RBIs by 50 if they’re 8th in Runs.

To find what it takes to win the Tour Wars league, here are the average points per category for the past three winners. As a reminder, the league is a standard 15-team 5×5 league with OBP instead of AVG.

Season: Average Points per Category (1st place = 15 points, 2nd place =14 points, …, 15th place = 1 point)
2014: 12.1
2015: 11.3
2016: 12.7
Average: 12.0

A fourth place finish in every category puts me in good shape to win while averaging third place almost guarantees me a win.

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The Low Investment Mound Ace (LIMA) has been dead for years. It’s a classic roster building technique aimed at dominating the hitting categories and doing just enough with low cost pitchers. As recently as a few years ago, it was the linchpin of my drafting strategy. It’s still talked about as a common and successful approach. Judging by the title, I probably disagree.

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Just yesterday, I mentioned I was happy to get Michael Pineda in the 19th round in Lindy’s mock draft. I am not a believer he can quit getting hit around so hard and therefore lower his ERA near his FIP. I do though want the pitcher with a +9 K/9 and a walk rate under 3 BB/9.

Using NFBC average draft position data, Pineda’s is getting picked as the 230th player off the board but he has gone as early as 184th. A spread of 46 picks is about three to four rounds depending on league size. I created a simple spreadsheet to help an owner know the chances a player is still available at each of their picks thereby knowing when to wait on a player or immediately pick them up.

Merging an owner’s personal projections and the current ADP is probably one of the most important processes in a preparing for a draft. It takes some time (which I understand not everyone has) but it can give an owner a nice leg up on competition. These owners understand when they can get 5th round values in the 12th round.

In past articles, I demonstrated how to go through each round and use ADP to see which players may or may not be available. I would sort of gamble on when a player may go using the earliest and average pick. By setting up a spreadsheet to calculate the normal distribution using the draft pick data from NFBC.

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