2013 NBA Playoff predictions:The final tallies

The Heat in seven was a popular prediction with the experts on ESPN, so we have a lot of predictors whose record improved with the last series.

Experts with 15 predictions
Arnovitz: 77.1%
Haberstroh: 76.0%
Wallace: 74.0%
Pelton: 72.7%
Adande: 72.0%
Windhorst: 69.3%
Gutierrez: 68.0%
Elhassan: 68.0%
Abbott: 67.3%
Stein: 58.0%

If I'm grading this strictly, that's five grades of C, four grades of D and an F.

I am not trying to insult these people, though I would certainly drop Stein from the list of experts next year if I was the boss. My point is that there are a lot of random factors in games and prediction is tough.

Experts with less than 15 but more than 10 predictions
Ford: 14 predictions, 85.7%
Legler: 13 predictions, 81.5%
Thorpe: 12 predictions, 77.5%
Palmer: 13 predictions, 70.0%
Barry: 14 predictions, 67.1%

Without question, the part-timers did better than the full-timers, 2 Bs,2 Cs and 1 D. While I would drop Stein, I would want the predictions of Ford and Legler in every series next time playoffs roll around.

2013 NBA Playoffs predictions:Predictions for the finals

Currently on the ESPN website, there are 18 predictions for the outcome of the NBA Finals series between the Miami Heat and the San Antonio Spurs. Earlier in the week, there were two other predictions posted that have since been bumped. Here are all the predictions as well as the records of the experts so far in the first fourteen series match-ups.

Full time
Haberstroh: (14 predictions, 74.3%) Heat in 7
Elhassan: (14 predictions, 72.9%) Spurs in 6
Wallace: (14 predictions, 72.1%) Heat in 7
Pelton: (14 predictions, 70.7%) Heat in 7
Adande: (14 predictions, 70.0%) Heat in 7
Arnovitz: (14 predictions, 70.0%) Heat in 7
Windhorst: (14 predictions, 67.1%) Heat in 7
Guttierrez: (14 predictions, 66.4%) Heat in 6
Abbott: (14 predictions, 65.0%) Heat in 7
Stein: (14 predictions, 62.1%) Spurs in 6

The strong consensus of the people who haven't missed a chance to predict for the entire playoff series is the Heat will win Game 7 and become the champions. Looking at the percentages, I am not filled with confidence they actually know what will happen.


Almost full time
Legler: (12 predictions, 88.3%) Spurs in 6
Ford: (13 predictions, 84.6%) Heat in 7
Thorpe: (11 predictions, 76.4%) Heat in 6
Barry: (13 predictions, 64.6%) Heat in 7
Palmer: (12 predictions, 64.6%) Heat in 7

I put Legler's and Ford's numbers in bold because they are head and shoulders the best predictors so far. If I was grading on straight percentages they would be looking at B+ and B, and grading in comparison to the rest of the class they deserve As.

And they are pointing in the opposite directions.

Prediction is hard, especially about the future.


Part timers
McMenamin: (1 prediction, 70%) Heat in 6
Doolittle: (5 predictions, 68.0%) Heat in 6
Shelburne: (3 predictions, 66.7%) Spurs in 6
Broussard: (8 predictions, 62.5%) Heat in 6
Torres: (2 predictions, 0.0%) Spurs in 6

I put the rest of the predictors in out of completeness sake. This group does not inspire much confidence.

Notice that no one predicts a blowout. A six or seven game series is what to expect between evenly matched teams. A four game sweep is complete domination and five games series is pretty lopsided as well. It should be noted that if the series goes to Game 7, it will be played in Miami.

I am not an expert on basketball, but looking at the patterns, my feeling is that the experts have done a pretty good job of understanding the Eastern Conference and a relatively poor job of understanding the Western Conference. Not one expert thought the Warriors would beat the Nuggets and then underestimated how well they would do against the Spurs. They thought the Clippers were better than the Grizzlies. Surprised the Spurs did not dominate the Warriors easily and underestimating the Grizzlies, they then thought the Spurs-Grizzlies matchup would be a tough struggle. The Spurs won in four.

Personally as a fan, I don't like the Miami Heat. They are the team that looks better on paper, talent in their prime vs. talent that is getting old. It might be that Heat coach Erik Spolestra is at the beginning of a brilliant career, but I'm not convinced he's better than Greg Popovich right now.

One advantage the Spurs have is the leisurely pace of the Finals, with games on Tuesday, Thursday and Sundays. The extra day of rest can help the older players.

Not just to be different, I'm going to predict the Spurs win the series on their home court in Game 5, four games to one. I make this prediction looking at the 2-3-2 schedule and the extra day of rest between games 1 and 2 and games 4 and 5, which should help the older players recover.  I fully admit this prediction is nearly equal parts math and wishful thinking, but given the unimpressive record of conventional wisdom in the playoffs so far, I'm happy to go out on a limb with this one.

2013 NBA Playoffs predictions: Grade after the Heat-Pacers series

All the basketball experts from ESPN who have an opinion  predicted the Heat would win the conference final against the Indiana Pacers, so all of them get some improvement in their overall records. Here are the percentages for the people who have put forward an opinion on all fourteen contests so far.

Abbott 65.0%
Adande 70.0%
Arnovitz 70.0%
Elhassan 72.9%
Gutierrez 66.4%
Haberstroh 74.7%
Pelton 70.7%
Stein 62.1%
Wallace 72.1%
Windhorst 67.1%

If this were a math class I was teaching, I would not be happy. The median score is 70%, which is to say that nearly half the class is failing. The last question - Spurs or Heat - should be the toughest question of all.

To be fair, if we look at people who have had predictions in more than ten of fourteen series, we have some better students.

Barry (13 of 14 series) 64.6%
Ford (13 of 14 series) 84.6%
Legler (12 of 14 series) 88.3%
Palmer (12 of 14 series) 67.5%
Thorpe (11 of 14 series) 76.4%

I don't publish this stuff to mock the participants. When there is as much randomness as we have in sporting events, prediction gets much harder than it is in American elections that drag on for months and months.

I will return to this topic at the end of the final series, which should be over in a week or two at the most.

Evaluating the Moneyball draft eleven years later: Part 3: the first round draftees of the Oakland A's and their competitors

A substantial portion of the book Moneyball concerns itself with the 2002 baseball draft. Due to trades and compensation for free agents taken from their roster, the Oakland Athletics had seven of the first forty draft picks in this draft and figuring out who to pick was of great important to general manager Billy Beane. Both in the book and the movie, it is noted that Beane was drafted straight out of high school and did not live up to his potential. The A's that year did not draft a single high school player, preferring to get players from the college ranks.

It makes for a more dramatic story line to say that Billy Beane was doing all he could to not draft another Billy Beane, but there is another explanation that should be considered. As is noted in both the book and the movie, the A's were cheap. (And they still are, for that matter.) If you were trying to cut corners in a scouting organization, you could decide to only focus on college players or only focus on high school players. Because there are less colleges, the thriftiest decision would be to just scout the colleges.

The A's seven choices were four position players and three pitchers.

Position players: The A's first pick in the draft was the 16th pick overall and has to be seen as a great success, Nick Swisher. Their next two picks, John McCurdy (26th overall) and Jeremy Brown (35th overall), did not suceed, McCurdy never making it to the big leagues and Brown getting six total bases in 10 official at bats and one walk. Their last pick in the first round was Mark Teahen (39th overall), who is a solid major leaguer but not a big star.

It's hard to compare the A's picks of position players over this stretch because from the 16th to 39th pick, only the A's were looking at college position players. It's not fair to look at the high school players they could have picked up, since we can assume they didn't scout them at all. In hindsight, the best college prospects that they didn't take in these early round picks include the major league successes from the second round, Joey Votto (44th overall), Christopher Snyder (68th overall) and Curtis Granderson (80th overall). As evidence of what a crap shoot the draft can be, the greatest college success in the late rounds is Howie Kendrick, the 274th overall pick with a respectable 1490 total bases in his career so far.

Pitchers: The A's got one major league pitcher in their three first round picks, Joe Blanton, the 24th overall pick. Their other two picks did not make the majors, Ben Fritz (30th) and Steve Obenchain (37th). They could have done much worse, as the Chicago Cubs demonstrated. Like the A's, the Cubs were going only for college players and they had a total of four first round draft picks. The went entirely for pitchers and non of them made the major leagues.

If the A's decided to eschew high school drafts due to Billy Beane's worries about getting another kid like himself, the numbers don't back this up. High draft picks are hit or miss regardless if they come for high school or college ball. As it happens, the very first pick in the 2002 was a pitcher out of college, Bryan Bullington, whose overall major league record was 1-9 with and ERA of 5.62. On the opposite side, the entire first round produced some great players out of high school, including pitchers Matt Cain, Cole Hamels and Zack Greinke. For position players, the high school draftees from the first round include Prince Fielder, Jeff Francoeur, B.J. Upton and James Loney.

To conclude, the A's draft that year wasn't stellar and completely ignoring high school players is not a good strategy overall, but it might be the best strategy if you are trying to cut costs in the scouting department.

Evaluating the Moneyball draft eleven years later:Part 2: Value of the major leaguers, college vs. high school draftees

If you read the book or saw the movie Moneyball, a strong impression you could come away with is that Billy Beane had helped make the Oakland A's a better team than their payroll predicted they should be by using modern approaches for scouting talent. The book pays a lot of attention to the 2002 baseball draft, a draft where Beane chose only college players and left out the high school stars. The emotional reason behind this decision is that Beane himself had been drafted out of high school and did not turn out to be productive at the major league level.

Obviously, a sample size of n = 1 is not a basis for science. Let's look at a statistic from the high school and college players among the first 50 drafted position players and the first 50 drafted pitched.

I admit that a single statistic measures only a single dimension and baseball is not a one dimensional game. For position players, I'm using total bases, which means adding up the hits and walks and stolen bases, giving one extra base for each double, two extra bases for each triple, three extra for a home run and subtracting the number of times the player was caught stealing.

For the pitchers, I use innings pitched as the measure of their value over their career. It's not perfect, as it tends to favor starting pitchers over relievers, but in general it does show over a career how much value a pitcher had for his club.

Total base numbers for the players from the 2002 draft that made the majors
High school draftees 
===============
2902, 2114, 2111, 2062, 1629, 1243, 907, 527, 476, 179, 98, 54, 19
Average: 1101.6
Standard deviation: 846.5
n = 13

College draftees
===========
2670, 2649, 1928, 1292, 1270, 1100, 829, 541, 424, 124, 6, 3, 2
Average: 987.5
Standard deviation: 951.0
n = 13

For these numbers, the high schoolers are better prospects on average than the college players, due in large part to the most productive hitter on the list, Prince Fielder and his 2,902 career total bases so far. The top two college recruits were Nick Swisher and Curtis Granderson, who are also both still active.

The reason I included the standard deviation and the sample size is to find out if the difference we see is statistically significant and the answer is no. The simplest formula for statistical significance is the z-score method, and the big standard deviations are in the denominator of the formula, which overwhelm the numerator by a lot.

Innings pitched numbers for the players from the 2002 draft that made the majors
High school draftees 
===============
1537, 1492, 1377, 1163, 1022, 473, 450, 233,180, 164, 120, 15, 10
Average = 633.5
Standard deviation = 529.3
n = 13

College draftees
===========
1438, 1202, 1179, 1161, 1141, 495, 166, 157, 114, 82, 68, 20
Average = 602
Standard deviation = 491.2
n = 12

Once again, the big standard deviations mean the difference isn't significant, but the high school draftees did slightly outshine the college.

Generally, Beane's decision to ignore high school talent appears to be counter-productive. On average, they are no more likely to wash out than college players and the most talented can be in the major leagues at a younger age with a chance to have a longer career if they can stay healthy and productive.

One of the reasons the book focused on the draft was that the Athletics had negotiated a large number of first round picks in 2002, the highest being the 16th overall and the lowest being the 39th. Tomorrow, we will look at those picks and how the A's did against their competitors.

Evaluating the Moneyball draft eleven years later.Part 1: Making the majors or not

Michael Lewis' book Moneyball concentrated on the Oakland A's in 2002, more on the front office than on the players on the field. The idea was that general manager Billy Beane and his employees were looking at new and better ways to develop talent and use it, giving them a chance to be competitive with teams whose payrolls were several times higher than what the frugal A's ownership was willing to spend.

Beane and his team used sabremetrics, a word coined from the acronym SABR, the Society of American Baseball Research. The idea was that he would be able to draft players under-appreciated by other clubs and build a nucleus of young talent, though the best would be lost to free agency within a few years.

Beane's method really wasn't that scientific. What Billy Beane wanted to avoid was drafting another Billy Beane. He was much sought after out of high school. He debated whether he would go to college or go straight into baseball out of high school. He was drafted out of high school and he made the major leagues eventually, but he wasn't the All-Star the scouts had hoped he would be.

Beane the general manager drafted no high school players in 2002, worried there was a high probability he might find too many kids like himself who crumbled under the pressure of professional baseball.

Using the 2002 draft as our data set, let's ask the question: Is there a significant difference between the success rates of high school and college draftees?

The null hypothesis: There is no significant difference.
Data set #1: The first 50 position players drafted
Data set #2: The first 50 pitchers drafted
How we split the sets: A player was either drafted from high school or college and the player either made the major league roster or did not.
We will perform a chi-square test to see if the differences we see are significant.

Problem with this test: We are lumping together some players with very good careers so far with some guys who just barely had a cup of coffee in The Show. That problem will be addressed in the test used tomorrow.

Position players
============
High school draft: 13 made the majors, 13 did not
College draft: 13 made the majors, 11 did not

Test statistic: chi square = 0.087, well below even the 90% confidence threshold of 2.706


Pitchers
======
High school draft: 13 made the majors, 10 did not
College draft: 12 made the majors, 15 did not

Test statistic: chi square = 0.725, well below even the 90% confidence threshold of 2.706

These numbers just count whether players will make it to the majors or not, and as we can see, out of the first hundred or so players chosen, about half will see major league experience and high school draftees are not significantly different from college draftees. Another question is how good are those major leaguers when we compare the high schoolers to the collegiates?  Tomorrow, we will use a different statistical test on only one stat per player, not a completely fair test, but it does give an approximate idea of the players' worth to their squads.

2013 NBA Playoffs predictions:Grade after the Spurs-Grizzlies series

The Western Conference final series is now over, concluded quickly as the San Antonio Spurs swept the Memphis Grizzlies in four games. No expert saw this coming exactly and the general consensus was that the teams were evenly matched and it would be a close series.

As of this series, there are ten people who have ventured an opinion on all thirteen series now completed. Unfortunately for the class average, the two best predictors so far, Tim Legler and Chad Ford, both neglected to give their opinions, so the overall quality of the predictions suffers mightily. When the entire playoff season is over, I'll show how everyone who made any predictions at all did.

Abbott: Grizzlies in 6 (0 of 10 points) 62.3% overall
Adande: Spurs in 7 (7 of 10 points) 68.5% overall
Arnovitz: Spurs in 7 (7 of 10 points) 69.2% overall
Barry: Grizzlies in 6 (0 of 10 points) 64.6% overall
Elhassan: Spurs in 7 (7 of 10 points) 71.5% overall
Gutierrez: Spurs in 7 (7 of 10 points) 65.4% overall
Haberstoh: Spurs in 7 (7 of 10 points) 73.1% overall
Pelton: Spurs in 7 (7 of 10 points) 69.2% overall
Stein: Grizzlies in 6 (0 of 10 points) 60.8% overall
Wallace: Spurs in 7 (7 of 10 points) 70.8% overall
Windhorst: Spurs in 6 (8 of 10 points) 65.4% overall

If we were putting letter grades on these numbers, the majority of the class would be failing. Legler and Ford would make the group look better with a B+ and a B grade, both with twelve predictions instead of thirteen, but this group has the star of the class Haberstroh with a C that is close to a C- and seven students in the D range. In the series that remains, everyone is predicting the Miami Heat to win, so they all could pick up some much needed points, but no one in this group can get to an 80% prediction rate over the entire fifteen series and some could dip below 60% if the Indiana Pacers get hot.

I don't do this to mock these people. I do this to show that prediction is usually very difficult and if there is a high degree of variability, even the best don't do very well.

2013 NBA Playoff predictions: Grading ESPN's experts

The National Basketball Association, the NBA for short, has a knockout tournament among the season's top eight clubs from each of the two conferences, the Eastern and Western. This means sixteen teams total start the playoffs and it takes a total of four rounds - conference quarterfinals, conference semis, conference final and league final - before a champion is crowned.

We are now halfway through, down from sixteen teams to four. Each contest to eliminate a team is a best of seven series and twelve of these series have already been played.

ESPN carries the games in the early rounds and the championship is aired by ABC. On their website, they ask a group of experts for predictions about each series. I have taken those predictions so far and graded the experts on how well they foretold the actual result.

Here's the grading system for those who are interested.
1. Predicting the correct team is worth 7 points. Predicting the wrong team is worth 0 points.
2. In each series, the experts also say how long the series will last. Four games is the shortest and seven the longest.
3. If an expert predicted the winner correctly, it is possible to get 0, 1, 2 or 3 extra points depending on the predicted length and the actual length of the series.
Gets the series length precisely: 3 extra points for a total of 10, a perfect prediction.
Predicts either one game too many or one game too few: 2 extra points for a total of 9
Predicts either two games too many or two games too few: 1 extra point for a total of 8
Predicts either three games too many or three games too few: 0 extra points for a total of 7
4. Close but no cigar points: If an expert predicts a seven game series and the series goes seven games but the team predicted to win actually loses, the expert gets 5 points total for getting everything but the last game's result correct.

List of experts: Abbott, Adande, Arnovitz, Barry, Elhassan, Ford, Gutierrez, Haberstroh, Legler, Palmer, Pelton, Stein, Wallace, Windhorst

Results of the twelve series so far and the right-wrong record of the experts:
Conference Quarterfinals
Heat-Bucks: Heat wins, Experts 14 right, 0 wrong
Pacers-Hawks: Pacers win, Experts 13 right, 1 wrong
*******Nets-Bulls: Bulls win, Experts 9 right, 7 wrong
Knicks-Celtics: Knicks win, Experts 14 right, 0 wrong
Thunder-Rockets: Thunder wins, Experts 14 right, 0 wrong
Spurs-Lakers: Spurs win, Experts 13 right, 1 wrong
**************Nuggets-Warriors: Warriors win, Experts 0 right, 14 wrong
*********Clippers-Grizzlies: Grizzlies win, Experts 5 right, 9 wrong
Conference Semifinals
Heat-Bulls: Heat wins, Experts 14 right, 0 wrong
Thunder-Grizzlies: Grizzlies win, Experts 13 right, 1 wrong
Spurs-Warriors: Spurs win, Experts 14 right, 0 wrong
***********Knicks-Pacers: Pacers win, Experts 3 right, 11 wrong

The asterisks indicate the difficult series to predict. Not a single expert went out on a limb to predict the Warriors beating the Nuggets, so no one has a spotless record. The Nets and Bulls went to seven games and the experts were nearly evenly divided. In the other two tough series to predict, the Grizzlies were seriously underrated and the Pacers were ridiculously underrated.

Expert ratings after twelve series
Name: points out of 120 possible (percentage correct)
Legler: 106 (88%)
Ford: 100 (83%)
Haberstroh: 88 (73%)
Elhassan: 86 (72%)
Wallace: 85 (71%)
Barry: 84 (70%)
Arnovitz: 83 (69%)
Pelton: 83 (69%)
Adande: 82 (68%)
Abbott: 81 (68%)
Palmer: 81 (68%)
Stein: 79 (66%)
Gutierrez: 78 (65%)
Windhorst: 77 (64%)

I want to give Tim Legler and Chad Ford props for doing so well in the first two rounds, because as of this morning, they have not given predictions for either of the next two rounds and the first game of Spurs-Grizzlies starts in less than an hour. There are more than 14 experts total working at ESPN, but I only grade those that make a call on all series contested. If both of them are removed, I may change my grading system to include all predictions, even those by people with only a few. If I don't do that, all the experts will look like students struggling to avoid a C- grade or worse. Prediction is hard, but it isn't that hard.