The Two Flavors of Trade
by Brad Johnson
December 15, 2017
There are only two types of trades – those of necessity and arbitrage. Let’s talk about them today.
Archive for Strategy
Counting Stat Estimator For Hitters On The Move
In leagues with Runs and RBIs as categories, predicting how a player’s mix will change with a new team can be guessing. Some clown at Fantrax yesterday wrote the following:
“As for Headley, his value drops by going to a worse offensive team in a pitcher-friendly park. Part of the decline could be offset by a move up in the lineup since he mainly batted seventh for the Yankees last season.”
It could go up, it could go down, who really knows? While writing the statement, I needed a better answer so I created a couple quick and simple tool. If an owner can estimate a few stats, they can predict changes in plate appearances, Runs, RBI when a hitter moves from one team to another.
The key was to be simple and quick. For simplicity, only the following stats are needed.
- New likely lineup location
- Estimate of projected home runs
- Estimated games played such 150 out of 162 games as a percentage.
- Estimated Runs scored by a team. Used over on-base percentage because team level runs scored is easier to find and remember.
The estimated runs scored is the toughest value to come up with. I’d just go to FanGraphs team projection page to get a decent idea. Just take that year’s RS/G and multiply it by 162. Another method is to take the previous season value and plug it into the following regression equation:
`RS in Y2` = .575 * `RS in Y1` + 311
The goal is just to get a basic idea of possible changes.
The Ohtani Rule
The Japanese sensation Shohei Ohtani is finally coming to MLB (and more specifically to the Angels), and in doing so will become the trailblazer that sets a new expectation for the future of the (possible) “two-way” player. Because salaries and injuries continue to escalate in the game, a true double threat major leaguer is still hard to imagine in baseball, but if the 23 year old Ohtani does become the first player since Babe Ruth to make a regular impact on both sides of the ball, he will change the landscape of fantasy baseball, too.
Ohtani 😱 pic.twitter.com/YXJJ8954Hs
— Vladimir Guerrero (@VladGuerrero27) December 8, 2017
A Potent Odor: Rougned’s Return
About a week ago, I compared rankings with some actual ADP. One player which stood out was Rougned Odor. He ranked 47th overall (AVG vs OBP league) and it’s tough to rank a person so high who hit only .204 last season. Steamer projections currently have him back up to a .255 AVG. Acceptable but not great.
Additionally, Odor comes to the plate hacking and rarely walks (4.2% for his career) so almost all of his value comes from his BABIP. If his batted balls don’t fall for hits, he’s not getting on base. Since his value is so BABIP driven, I decided to see what the BABIP bounce-back chances were for low-walk hitters.
Value vs. ADP: Players 51 to 100
In my last article, I examined the potential value differences between the top-50 rank players and their average draft position (ADP). Today, I will examine the next 50. While the first list contained quite a few players moving up, today’s list is a little more balanced with over and undervalued players.
One of the biggest takeaways from the first article was the extra replacement value catchers receive in a 2-catcher format. To simply explain the idea, I will turn to Joe Bryant who goes through a fitting example but with football.
The league’s bottom catchers are so bad so any catcher who can hit has good value. Evan Gattis being ranked #17 got most of the scrutiny in the rankings. As was pointed out, the projection may be high on the plate appearances but the process was still sound. Here is how Gattis compares to the last catcher ranked (Yan Gomes) and Francisco Lindor compared with the last middle infielder (Kolten Wong).
Positional Scarcity Comparison
| Name | AVG | HR | R | RBI | SB |
|---|---|---|---|---|---|
| Evan Gattis | 0.254 | 30 | 73 | 87 | 2 |
| Yan Gomes | 0.232 | 9 | 26 | 29 | 1 |
| Difference | 0.022 | 21 | 47 | 58 | 1 |
| Francisco Lindor | 0.292 | 26 | 96 | 90 | 14 |
| Kolten Wong | 0.268 | 12 | 58 | 56 | 9 |
| Difference | 0.024 | 14 | 38 | 34 | 5 |
Yan Gomes is such a sink, especially with a total of 55 Runs+RBIs. It’s imperative to understand and value catchers correctly for each league formats. It’s a potentially huge advantage for those owners who spend the time. Read the rest of this entry »
Top 50 Ranked Players: Value vs. ADP
“Long ago, Ben Graham taught me that ‘Price is what you pay; value is what you get.’ Whether we’re talking about socks or stocks,
… or fantasy baseball players
I like buying quality merchandise when it is marked down.” –Warren Buffett
Collecting as much value (talented players) from as little possible resources (draft picks or auction dollars) is the key to starting off a winning fantasy season. From now until each draft, owners should be trying to calculate player values and the possible range of outcomes. With these value ranges in mind, owners can use their draft resources to get the best deals. It’s time to start finding those deals.
To find the bargains, player values first need to be calculated. To create the values, I will use the average final standings from the 32 leagues in the 2017 NFBC Main Event (15 team, 5×5 roto with AVG).
How To Talk Trade 2.0
I once took an excellent training course on effective communication. At the beginning of the course, our teacher started with a game:
In my hand is an envelop with a $10 bill inside. I want one of you in this room to take the deal I’m offering you. I’m going to ask you a simple trivia question and, if you get it right, you get the ten dollars. But if you get it wrong, you owe me two dollars. However, if you don’t know the answer, you can ask one person in the room for help. Who wants to volunteer?
After a few moments of people looking at each other wondering what the catch might be, I volunteered. “How many states make up the United States?”, he asked.
Fixing My Fantasy Weakness: Hitter Evaluation
I was recently asked the following question by Werthless.
Jeff, what are you trying to accomplish here? Are you trying to estimate the volatility in an individual player’s projection? That’s an interesting question, and directly related to the risk of the player. Are you trying to do better than Steamer at predicting performance? That’s a big endeavor. Are you trying to predict injuries? Might be better to do that directly. Are you trying to better estimate number of plate appearances by estimating job security? Might be better to do that directly.
Then, you can combine the models to perhaps better quantify a player’s risk of meeting preseason performance objectives. You can apply your model onto a different year’s data to see how well your predictions match reality (ie. Do the higher risk players actually underperform more often than lower risk players).
I do have a plan I’m implementing but it wasn’t known to my readers. Sorry. I want to understand which hitter traits to concentrate on. If they don’t exist, I created some.
For a few season’s now, my hitters have steadily outperformed my pitchers. In my three main leagues, here are the pitching-hitting splits from this past season.
Read the rest of this entry »
Ground Balls Are Changing.
Major league batters are generally shifting towards a fly ball approach. The idea is to hit more balls in the air. Not necessarily fly balls, in fact there are those who wish to only hit line drives. When I say in the air, I mean ‘not on the ground.’ You want the ball to leave the infield before it bounces, ideally. Preferably this happens at a very high speed.
Duh, no kidding, right? Well, yeah. Obviously hitting the ball out of the infield is the goal for just about everyone. The goal isn’t the key, we’re talking about the approach used to actualize the goal. Read the rest of this entry »
Nuance or Rigid Process
by Brad Johnson
November 13, 2017
Humans are kind of a mess. One of our many failings as a species is a tendency to oversimplify complex issues. I think of it as the “good versus evil conundrum.” I’m sure academia has a better name for it. Basically, we prefer wholesome heroes and fell villains rather than the equivocating mess we typically find in reality.
Good guys sometimes do bad things. The venerable Abraham Lincoln suspended habeas corpus during the Civil War to deal with dissidents. Most of the so-called evil folk in history were trying to make a better world for themselves. They were the good guys in their story. Our tendency to ignore the gray area between good and evil – i.e. the nuance – can be found in baseball (and fantasy baseball) too.