The Great Fantasy Baseball Invitational (TGFBI) drafts have now approached their conclusion. Avid readers of this website will already be familiar with the invitational’s format. TGFBI (created by our own Justin Mason) is the compilation of 390 industry experts across 26 leagues. Each division runs as NFBC-style 15-team leagues, with the collection vying for an overall prize – to win industry bragging rights. The only operational difference is that TGFBI drafts are run with a 4-hour clock – i.e., TGFBI is a slow draft. During the season, the format is virtually identical to the NFBC main event.

Check out TGFBI central and follow your favorite fantasy analysts’s teams at TGFBI.com.

As a bonus, I am honored to host the Great Fantasy Baseball Invitational Podcast – Beat the Shift – along with my friend and fantasy partner, Reuven Guy (@mlbinjuryguru). Last season, Reuven managed to win his league while finishing second in the overall TGFBI competition.

Check out the latest episodes of The Great Fantasy Baseball Invitational Podcast – Beat the Shift, found here. Follow me on Twitter at @ATCNY.

This is the 3^rd year of the Great Fantasy Baseball Invitational, and I have participated ever since its inception. In 2020, with so many talented fantasy analysists in my division of TFGBI – my league (#14) was tabbed by many as the “League of Death.” Using the ATC projections, as well as my Replacement Level Drafting (RLD) method, I drafted what will hopefully be a championship caliber team.

Today, I will provide a few observations on the TGFBI drafts, review my personal team makeup, and highlight some of my player selections along the way. My goals of this article are to use the TGFBI experience to convey information to you about the drafting landscape of 2020, as well as to illustrate my team construction process. Hopefully, you will be able to take some nuggets of wisdom from my recap to assist you with your draft preparation.

Before we get further into it – draft standings analysis based on projections are generally irrelevant. But just for fun, here is what FantasyPros had to say about my team.

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Let’s dive into another Pod Projection! As a reminder, the 2020 forecasts are available now and include over 500 player lines. The projections follow the same process that resulted in the most accurate non-aggregate system of 2019 as calculated by FantasyPros.

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In a pair of recent columns, I looked into what factors have impacted flyball BABIP (or FB BABIP) and ground ball batting average for pitchers, and those analyses were linked by a common finding. Whether pitchers are allowing balls that are in play in the air or on the ground, the launch angles of those batted balls go a long way towards explaining whether they become base hits. Now I am turning my attention to flyball BABIP for hitters, and the trend continues. While flyball pull rate, average flyball distance and average exit velocity, both on flyballs and line drives combined and on flyballs alone, did not have significant relationships with FB BABIP for hitters, average flyball launch angle (FB LA) turned out to be a statistically significant factor yet again (p < .0006, r = .19)
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Now let’s try to identify hitters who in 2019 were lucky or unlucky, and consider what to do about them in 2020. We use the same factors we discussed last week in our look at lucky and unlucky pitchers, but we invert them. Thus, a lucky hitter is one with a high 2019 BABIP and a high HR/FB ratio but a low hard-hit percentage, while an unlucky one had a low BABIP and a low HR/FB ratio but a high hard-hit percentage. This method didn’t cover itself with glory last season—it got the unlucky guys mostly right, but was 0 for 3 on the lucky ones—but It’s had better success in the past. Let’s take it out for one more spin: Read the rest of this entry »

Here we go again! Every season there’s at least one mega-hyped player expected to make his much anticipated debut during the year, and his market price reflects the unbelievable excitement. The last time we did this, it was Vladimir Guerrero Jr., who I specifically called out at the end of February last year for being insanely priced. Now, it’s White Sox outfielder and seventh overall ranked prospect Luis Robert.

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Yesterday, I compared my Pod Projections to Steamer in the stolen base category and identified and discussed five hitters with upside. Today, I’ll flip to the hitters I have forecasted for a lower rate of stolen bases than Steamer. I’ll stick to only including players projected for a reasonable number of plate appearances.

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Last week, I compared my Pod Projections to Steamer and calculated which hitters I was more bullish on and more bearish on for home runs. Today, I’ll do the same for stolen bases. Similarly to homers, I’m going to calculate a PA/SB rate first and then extrapolate that projection over 650 plate appearances so we’re only comparing stolen base projections and playing time forecasts don’t factor in.

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Yesterday, I compared my Pod Projected home runs per 600 at-bats to Steamer’s forecast to identify and discuss a slew of hitters my projections are far more bullish on in the dinger department. Today, I’ll flip to the opposite end, those hitters who Pod forecasts for fewer home runs than Steamer, given 600 at-bats.

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Every year, I pit my Pod Projections against the Steamer projections in various categories. Today I’m going to continue the annual smackdowns by calculating AB/HR rates and then extrapolating them over 600 at-bats. At that point, I’ll compare how many home runs each system is forecasting, given a 600 at-bat projection. I’ll start by sharing the names of hitters Pod is projecting for significantly more home runs than Steamer. Many of these players figure to be part-timers, so consider them sleepers in deeper leagues.

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Finally, it’s Pod Projections time! The 2020 forecasts are now available and include over 500 player lines. As usual, I’ll dive into my projection methodology (detailed in Projecting X 2.0) by sharing my process on several hitters and pitchers.

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