‘Unskewing’ the Polls in the Hall of Fame Election

Vladimir Guerrero is right on the cusp of being inducted in his first year of eligibility. (via Keith Allison)

Vladimir Guerrero is right on the cusp of being inducted in his first year of eligibility. (via Keith Allison)

By now, you’ve probably heard of Ryan Thibodaux’s BBHOF Tracker. The Tracker (and its predecessor at Baseball Think Factory, the Gizmo) has changed the way fans follow the annual election to the Baseball Hall of Fame. Instead of guessing at the final vote totals based on the imperfect baselines of the previous year’s results, Thibodaux compiles actual, preliminary results from this year by scouring Twitter for voters who have already shared their ballots with the general public. In essence, the Tracker provides a real-time exit poll of the Hall of Fame electorate, the 400-plus eligible writers of the Baseball Writers’ Association of America (BBWAA).

However, as you may have heard somewhere recently, polls can be wrong. The BBHOF Tracker pointedly is not to be taken literally as a clone of the eventual results; it is merely a snapshot in time of one fraction of the electorate. To make actual predictions, you need to pull a Nate Silver and develop a model that smooths out the polls’ inherent error and separates the signal from the noise.

For five years running now, I’ve employed such a model to predict Hall of Fame election results based on Thibodaux’s “polling.” Last year, the model correctly predicted every candidate’s vote totals within 3.5 percentage points or fewer; its average error was only 1.5 points. Most importantly, it successfully eliminated many of the red herrings in the raw polling data, where historical errors of eight or more points are not uncommon. This year, I’m bringing the same model—explained in excruciating detail below—back to bear on the 2017 election.

And its preliminary forecast is great news for those who believe the 10-vote limit has created a harmful backlog of deserving players on the ballot. The 163 ballots collected in the BBHOF Tracker as of Jan. 3 augur a record-tying year for the Hall. Although the numbers below can and will change, as of this writing, the model forecasts that five players—the biggest class since the very first one in 1936—will be elected to the Baseball Hall of Fame: Jeff Bagwell, Tim Raines, Iván Rodríguez, Trevor Hoffman and Vladimir Guerrero. Almost as notably, Edgar Martínez, Barry Bonds and Roger Clemens will see significant (~20-point) jumps from their 2016 support, putting them in line for eventual election. Meanwhile, Curt Schilling’s support will slip noticeably, and Lee Smith will drop off the ballot in his 15th year of eligibility. Although Jorge Posada will be a close call, the model currently does not expect any serious candidates to fall beneath the five percent support threshold. Here is the full rundown of the model’s projections; the chart below will automatically update as more data is collected.

The model operates on a simple premise: certain players consistently over- or underperform their polls. The type of voter who reveals his or her ballot in advance is a member of a self-selected demographic: the BBWAA’s forward thinkers, those who believe in transparency and are active on social media, where they often share their ballots. These same traits tend to overlap with a liberal approach to Hall of Fame voting: the use of advanced stats, a forgiving stance on performance-enhancing drugs (PEDs) and a preference for a big Hall over a small Hall.

As a result, public ballots tend to overestimate players like Raines and Mike Mussina, whose Hall of Fame cases are best appreciated sabermetrically. They overstate support for the most infamous villains of the steroid era, especially Bonds and Clemens. At the same time, public ballots undershoot the final vote totals of candidates whose cases rely on narratives or traditional statistics such as saves. In recent years, relief pitchers like Hoffman and Smith have seen the biggest gains from public to private ballots. Here is a full list of last year’s numerical shifts from ballots made public before the results were announced to the final tallies:

Player Public Ballots Private Ballots Final Results Priv – Pub Final – Pub
Ken Griffey Jr. 100.0% 98.7% 99.3%  -1.3% -0.7%
Mike Piazza  86.4% 79.7% 83.0%  -6.7% -3.4%
Jeff Bagwell  77.5% 66.1% 71.6% -11.4% -5.9%
Tim Raines  75.6% 64.3% 69.8% -11.3% -5.8%
Trevor Hoffman  62.9% 71.4% 67.3%   8.5%  4.4%
Curt Schilling  60.1% 44.9% 52.3% -15.2% -7.8%
Roger Clemens  51.2% 39.6% 45.2% -11.6% -6.0%
Barry Bonds  51.6% 37.4% 44.3% -14.2% -7.3%
Edgar Martinez  46.9% 40.1% 43.4%  -6.8% -3.5%
Mike Mussina  50.2% 36.1% 43.0% -14.1% -7.2%
Alan Trammell  44.1% 37.9% 40.9%  -6.2% -3.2%
Lee Smith  28.2% 39.6% 34.1%  11.4%  5.9%
Fred McGriff  18.8% 22.9% 20.9%   4.1%  2.1%
Jeff Kent  17.8% 15.4% 16.6%  -2.4% -1.2%
Larry Walker  14.1% 16.7% 15.5%   2.6%  1.4%
Mark McGwire  12.2% 12.3% 12.3%   0.1%  0.1%
Gary Sheffield  11.3% 11.9% 11.6%   0.6%  0.3%
Billy Wagner   8.9% 11.9% 10.5%   3.0%  1.6%
Sammy Sosa   7.5%  6.6%  7.0%  -0.9% -0.5%
Jim Edmonds   2.8%  2.2%  2.5%  -0.6% -0.3%
Nomar Garciaparra   0.5%  3.1%  1.8%   2.6%  1.3%
Raw Ballots Cast   213  227   440             

All the model needs to do, then, is estimate how much each candidate will rise or fall (usually fall) in private balloting. It turns out that these changes are fairly consistent from year to year. The model takes a straight average of the public-private differential over the past three elections to calculate a polling adjustment factor for each candidate. (If the candidate has been on the ballot for only one or two years, it just takes the average delta of those one or two years.) The model then adds or subtracts that adjustment to or from the player’s current percentage of public ballots to arrive at an estimated performance on private ballots—i.e., those yet to be revealed.

Those two performances—public and private—are then combined in the proper proportions to arrive at a projected overall vote total. For example, on Jan. 3, the 163 known public ballots were combined with the model’s projections for an estimated 272 yet-to-be-revealed private ballots to arrive at a final forecast. (Based on last year’s turnout of 440 voters, the knowledge that a certain number of voters were “purged” this year, and his expectation of several first-time voters, Thibodaux anticipates that 435 ballots will be cast in this year’s election.) As a result, the model is currently heavily reliant on its predictions for private ballots, but as more ballots are made public, the forecast will become more accurate.

Unfortunately, this method doesn’t account for players making their first appearances on the Hall of Fame ballot. This year, that list includes two serious threats to be inducted, Rodríguez and Guerrero, as well as two other debatable candidates in Manny Ramírez and Posada. Because these “rookies” have no voting history of their own, the model finds “veteran” candidates with whom the rookies’ votes are well correlated and adjusts their exit polls proportionally.

For example, in the public ballots thus far, Posada’s results correlate most strongly with Smith’s. To estimate Posada’s support on private ballots, the model assumes that the catcher’s same strong performance with known pro-Smith voters and weak performance with known anti-Smith voters carry over to private ballots. Of course, as we learned above, the ratio of pro-Smith to anti-Smith ballots is different among private ballots than on public ones, so Posada will rise or fall in tandem (in this case, rise—just as Smith is expected to gain ground when private ballots are revealed, so too should Posada, ever so slightly).

By contrast, Ramírez loses ground by this method. It should come as no surprise that his strongest correlations are with the comparably controversial Bonds and Clemens; almost everyone who has voted for Ramírez so far has also voted for Bonds and Clemens. Since past experience with those two has shown us that PED users are unpopular with private voters, we can be confident that Ramírez will drop in private balloting by a handful of points.

Rodríguez also correlates pretty well with Bonds and Clemens, but there’s another candidate from Hall of Fame elections past who’s an even better match. Like Rodríguez, Mike Piazza was a catcher well above his position’s standards for enshrinement but dogged by the shadow of PED accusations; it’s little surprise that his and Rodríguez’s supporters strongly overlap. Rather than settle for a less robust correlation, I opted to treat Rodríguez as if he were simply Piazza reincarnated on the ballot; his −8.5 percent adjustment is what Piazza’s would have been had he not been elected last year.

Finally, Guerrero is this year’s trickiest call. Not only is he the player closest to the 75 percent threshold for induction, but he isn’t a clear statistical doppelganger for any other candidate on the ballot. His strongest correlation is with Hoffman and his old-school supporters, but it’s not as dramatic as the other rookies’: 81 percent of Hoffman voters so far have opted for Guerrero, but 67 percent of non-Hoffman voters have too. That currently calculates out to a slender 1.2-point gain for Guerrero on private ballots, but there’s a large margin of error. For the candidate over whom there is the most suspense this year, that’s not ideal.

With luck, time will demystify the situation. Based on past experience, Thibodaux still expects to add 50 ballots or more to his Tracker before the full results are officially announced on MLB Network on the evening of Jan. 18. I’ll be updating my projections in real time as more ballots become known, and you can follow along on Google Drive or just by revisiting this article as the election draws near.

References & Resources

Nathaniel Rakich writes about politics and baseball at Baseballot. He has also written for The New Yorker, Grantland, The New Republic, and Let's Go Travel Guides. Follow him on Twitter @baseballot.
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5 years ago

Well thought out article. But two points. Models that use historical votes do not include changes in the electorate, nor the shifting “enlightenment” to different subjects, players and “group think” inherent in the votes. Included in that is the “new” metrics versus old. Also, the “crowded” ballot is more driven by how the voters are processing the steroid era.

5 years ago

“The type of voter who reveals his or her ballot in advance is a member of a self-selected demographic: the BBWAA’s forward thinkers, those who believe in transparency and are active on social media, where they often share their ballots. These same traits tend to overlap with a liberal approach to Hall of Fame voting: the use of advanced stats, a forgiving stance on performance-enhancing drugs (PEDs) and a preference for a big Hall over a small Hall.”

They are not forward thinkers. I find them seriously out of touch, disingenuous, and apologists, Populists, grubbers. Are people who are in favour of legalizing rape forward thinkers? People who want child rape decriminalized? People who want disabled people killed? All have “progressive” support, liberal support, but no support from centrists, moderates, or conservatives. Trump is active on social media, is he a forward thinker?

Voting for PED players, for many reason, to me is disingenuous cherry pickers. Do you applaud slaveholders before slavery became illegal? Do you chastise the IOC for banning all Russian athletes from the Olympics?

I find most people who use advanced stats have two issues: they don’t watch games, and they love to oversimplify things. Does WAR tell you anything? Not really. Is a home run in the first inning equal to a HR in the 9th? IS it better to walk and steal a base or hustle and beat out an infield single, and hustle to second on the error you forced? WAR is meaningless, it doesn’t tell you who is can hit a curve, throw a cutter for strikes, consistently lead your team to more wins. WAR darling Trout has lead his team to how many winning seasons?

matt w
5 years ago
Reply to  DSCe

Nathaniel said that the “forward thinkers” were those who believe in transparency and share their ballots. They do seem to be forward thinking on that issue. The other issues that you are discussing are not the ones that Nathaniel described as forward thinking, but merely correlated (as a matter of statistical analysis) with the issue on which he said they were forward thinking, so most of your post is off point.

I also find your analysis of the political valence of legalizing rape and other issues to be questionable. For instance, if you look at the people who minimize the severity of marital rape and acquaintance rape, I think you will find that they are not in general liberals.

You're Just Trolling, Right?
5 years ago
Reply to  DSCe

“I find most people who use advanced stats have two issues: they don’t watch games”

You made that up. Pure hogwash. And…

“and they love to oversimplify things.”

Again, your straw man is probably fun to beat up, but this is completely contrary to reality. I have literally never seen anybody assert that A has more WAR than B and is therefore a better player without getting into the how’s and why’s. WAR is a conversation starter, not a conversation ender.

To paraphrase Bill James from before he became kinda sad to read, when somebody tells you that something is meaningless, he is really saying that he doesn’t know what it means.

Neato Puente
5 years ago
Reply to  DSCe

Hahahah, the “over-simplification” line, given your truly unhinged response that directly equates supporting child rape and tweeting a ballot, is the true satiric cherry on top of your comment.

Johnny Bench Called
5 years ago
Reply to  DSCe

I want to thank you for writing this truly bizarre comment because I know it’s hard to keep uninformed retrograde opinions fresh after so many years and you’ve done an entertaining job of mixing things up with some truly over-the-top craziness. Bravo.

(Or it’s just fantastic satirical hyperbole, which is also praise-worthy.)

5 years ago
Reply to  DSCe

Wut the wut?

5 years ago
Reply to  DSCe

You: “They oversimplify things”

You: “PED use = child rape”

5 years ago

Very enjoyable article.

This bothers me to no end:

“Last year, the model correctly predicted every candidate’s vote totals within 3.5 percentage points or fewer”

You should limit PREDICTIONS to future events. We shouldn’t predict a player’s end-of-season HR total, after 50 games. We should predict his REST OF SEASON HR total after 50 games.

Same deal here. If you have 150 voters ballots in hand, out of 450 likely voters, the prediction should be on the other 300. So, rather than say “3.5”, you should report the error on the ballots you are actually predicting.

5 years ago

It would be emberresed if vladimir dos not go into hall of fame. You should know he was one of the best hitter .318 average and 2590 is too much even thou he did not win a world series. But you gotta respect he was very consistly player.

5 years ago

You write, “However, as you may have heard somewhere recently, polls can be wrong.”
I clicked on the link and it took me to a US Presidential poll. Need I remind you that the most recent poll was RIGHT! Hillary Clinton received THREE MILLION more votes that Putins TrumPet, yet she lost because of the antiquated way the election is decided, by electors rather than by We The People. Simply put, not all votes count the same.

5 years ago

To me the HoF should be about uniqueness and not about amassing numbers (without leading any category) due to longevity. In my opinion the guys below (with or without PEDs) are true HoFs since they revolutionized the game, sometimes in a shorter period of time than the rest of the players on the ballot. The rest were very good players who played the game very well but were not unique.

Tim Raines-Iván Rodríguez-Edgar Martinez-Roger Clemens-Barry Bonds-Lee Smith

Just the humble opinion of someone who loves, understands the game and is currently reading Big Data Baseball by Travis Sawchick. Thanks