The development of SCOUTscore started with the theory around Average Player Scores. In today’s Fantasy Baseball market, it is extremely difficult to determine a baseball player’s value when drafting when you have multiple positions never mind multiple scoring categories. The average player theory is a way to compare players at similar positions. Once we have a baseline of the average player, we can determine which players have the biggest edge. The next step after establishing these scores at each position is then comparing the best option at other positions.
Each season the player pool changes. Some positions will have more depth and others will only have a couple of strong options. When a Fantasy owner is preparing to do his draft prep, he wants to find the hidden values at each position. By doing this, he can select the strongest options at the other positions early in the draft.
Scout Fantasy Sports has developed a way to determine each player’s value within each category relevant to their production. Hitters have five offensive categories (batting average, runs, home runs, RBI, and stolen bases). Pitchers also have five categories (wins, ERA, WHIP, strikeouts, and saves).
With these scores, a Fantasy owner can quickly look at stats to see which players have the most value either by last year’s stats or this year’s projections from any source. When using projections, a Fantasy owner’s success will only be as strong as his/her ability to interpret information. Finding the best source for that information is essential.
Our SCOUTscore is built for 12-team, 5 by 5 Roto leagues with once a week pitching moves. In the future, we could modify the options for 10-team and 15-team leagues, and we may even add bi-weekly pitching move leagues.
The toughest part for any Fantasy owner to understand is draft rankings or cheat sheets. This is due to the underlying information behind each player’s profile. At any position in baseball, I may only like a handful of players. When I rank them, I can’t leave players I don’t like off the cheat sheet, and it wouldn’t be fair to rank them poorly just based on my opinion.
Here’s a look at the medium value in 2017 in a field of 1,788 teams in all ten categories:
BA: .2668, R: 1072, HR: 314, RBI: 1035, SB: 126, W: 89, SV: 73, ERA: 3.990, WHIP: 1.269, K: 1329
In today’s Fantasy Baseball market, owners use ADPs (average draft position) to better prepare for the upcoming draft season. ADPs give Fantasy owners a feel for a player’s value in the open market. This is a great tool, but a Fantasy owner must understand the value of the information. ADPs from mock drafts have less value as many drafts aren’t completed by a full roster of owners, and many drafters may lose interest at some point during the drafts. I believe the best information in Fantasy Baseball comes from owners playing for real money or owners competing in a real league that will be played out during the season.
Our SCOUTscores can work with any projections to deliver results. This season, we did all the research on all 30 baseball teams. We then did our team profiles for each team’s projections. With this information, we delivered rankings based on the SCOUTscores. Also, we can back check the results from the previous season to see how each player stacked up against their competition.
At the same time, we can deliver weekly rankings based on playing time and opportunity. We break the season into 26 weeks to come up with the weekly results. If a player is projected to play in seven games, he’ll have a better chance to produce stats in the counting categories. This doesn’t necessarily mean he’ll have a higher score than a player with the much higher skill set with five games.
Note: Each season the SCOUTscore equation is adjusted for the current playing field in major league baseball. If HRs are declining, a big power hitter will be rewarded for his edge in home runs. If steals are scarce, an elite base stealer will have plus value in the SB category.
Once we have each player’s projections matched up with the SCOUTscore, we have a way to compare values of all players. For this information to have more value, we really need to compare players at like positions. We know Mike Trout is an edge over every other player in most recent seasons, but how much is he an edge over all outfielders? How much is Clayton Kershaw an edge over the pitching inventory? Is Kershaw more of an edge in pitching than Trout is in hitting? This is when ADPs and player’s draft value comes into play. Once a Fantasy owner has this information, he then must decide how much he trusts or agrees with a player’s projections. He then should compare that player with other players at the same position in the projected ADPs.
The bottom line here is that a Fantasy owner is trying to gain an edge with each of his first few picks in the draft while filling as many categories as possible. Each decision takes a Fantasy owner on a different path.
We also had access to multiple other events with large amounts of teams competing for an overall championship. The information we used is from a league with once a week transactions for pitching.
The midpoint for wins last season was 89, which was divided by nine (the number of pitching slots) to come up with 9.889. I then used the overall standing in the 1,788 leagues to determine the points gained for a win or lack of a win. From the midpoint of wins, I used +/- 400 spots in the standing to get a range of points gained or lost. It was amazing to see 800 teams fall between 82 and 96 wins. I divided 800 overall points by 14 wins to come up with 57.143 overall points for each win. There were 149 leagues with 12 teams in this competition, so each win within a single league environment was worth .39216 league points.
For the ERA and WHIP category, I did some research in a few leagues that I had the results in. I determined that a competitive team would need about 1550 innings over the course of the season. I then found the medium ERA (3.990) and whip (1.269) in this 12-team format in 2017. I then subtracted the innings pitched by the pitcher from 1550. I multiplied that number times (.4433 = 3.990/9). This gave me the total number of runs allowed for the remaining innings of the medium ERA by inning. I then added the total number of runs allowed by each starting pitcher, and I divided that number by 1550 innings. This delivered the +/- impact of each pitcher based on the number of innings pitched or projected to pitch. The range was 800 league points divided a gap of .377 in ERA. This number was then divided by 149 leagues. I used a -14.24 as a lower ERA awarded more points.
I repeat this same process for the WHIP. The range was 800, which I divided by .067 (gap in WHIP from 1.236 to 1.303). I then divided into 149 leagues to deliver 80.14. Again, I used a negative number as a lower WHIP is the desired result.
For strikeouts, the medium total was 1329 Ks. Pitchers are created equal in Roto formats, but I still need to divide 1329 by nine pitching spots. This came to 147.667 strikeouts per starter. The range of strikeouts for 800 teams came to 161 with a low of 1244 at the 1294th position and 1405 at the 494th position. Each strikeout was worth 0.033348 points in the standing.
The midpoint for saves was 73 in this event. A Fantasy owner typically will get saves from two to three roster spots in their starting lineup, but we need to base the target goal on nine pitchers. This leads to a negative score for each starting pitcher. Over 800 spots in the standings in a 1788 team league, there was a difference of 28 saves. This came to 0.19175 points in a single league per save. Many Fantasy owners play the saves category differently, creating a wide range of results. A format with an overall prize does lead to more teams competing in this category.
For batting average, I used the same theory for ERA and WHIP. I determined by looking at some of my completed leagues that I needed 7800 at bats to be competitive in all the offensive categories. The midpoint for batting average was .2668 in 2017. For each player, I subtract their at bats from 7800 then multiplied that number by .2668 to give the total number of hits to deliver a medium batting average. I then added the total hits by the player to this number, and I divided that total by 7800 at bats. This gave me the impact of each player as far as +/- in batting average. The range of 800 spots in the standing was 0.0084 points in batting average or 65.5 hits over 7800 at bats. So, 800 divided by .0084 divided by 149 leagues = 639.18 points for batting average.
The midpoint for runs was 1072. The range was 79 runs over 800 spots in the standings, which delivered 0.06796 points per run in a single league.
The medium point for HRs was 314. The gap between 494th place and 1294th place in a 1788-team format was 39 home runs or 0.13767 points per home runs in a single league.
Runs Batted In
The midpoint for RBI was 1035. The difference in 800 points in the overall standing in RBI was 93 RBI. This worked out to .0577 points per RBI in a single league.
A team needs to get 126 SBs to finish at the medium point last season. The gap between 400 spots in the overall standing in either direction was 33 stolen bases leading to each steal being worth 0.1627 points in the standings.
By using these totals, a Fantasy owner can easily see which players had the most value last season. It is a tool that will help you when you are making future decisions. The real trick is to create these values for this year’s projections. By understanding the player pool and each player’s value within each category, a Fantasy owner can make better draft decisions. Here’s a look at the chart for both batters and pitchers to show power points gained or lost in each category within a league environment: