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Publication Date: April 8, 2003
Why Are We Here And Not Over There?
Predictability across Different Sports Publication Date: April 8, 2003 Why Are We Here And Not Over There? There are lots of reasons why we end up as a fan of a specific sport (and, no, I'm not arguing that you're limited to just one, but most of us do tend to specialize at some point). NHL = 1230 games per season. NBA = 1230 games per season. And with a 162 game schedule the MLB offers 2430 games per season to bet on. Also factor in that easily the most popular sport for betting is the National Football League and you can conclude that the sharpest of.
There are lots of reasons why we end up as a fan of a specific sport (and, no, I'm not arguing that you're limited to just one, but most of us do tendto specialize at some point). A lot of them are aesthetic -- I lovedbasketball as a player, and it televises well, but give me a choice betweensitting in a gym in December or sitting out in a baseball stadium in May, and it's not a hard choice. Some of them have to do with our own physicalcharacteristics -- baseball and hockey require pretty good eyes at timesto follow well. Many times it just comes down to some formative memorythat builds a fire. For most folks, they don't even think about why theylike a sport, it just clicks with them.
Sport Verified is the best free football prediction site in the world and the site that predicts football matches correctly. We are the most accurate football prediction site providing our users with the most accurate football predictions around the world. We provide the best football predictions and sport. Basketball - probably the easiest due to difference in skill level between players. It's a lot more common for someone like Lebron or Harden to score 30 and single-handily win the game Baseball / Football - a bit tougher due to defense is independent with offense. A pitcher can throw a 1 hitter, but his offense could score 0 runs and still lose.
For a lot of these folks, some of this can be traced back to thepredictability of a sport -- how likely am I to know the end result whenthe game starts? Those who like a safe outcome, with just a dash of upsetthrown in to keep the mix from getting too bland, tend to become footballfans. Those who like to see merit rewarded but like a good bit of unpredictability tend to become baseball fans.
For this study, I've pulled together comprehensive score data for the lastfive years for a number of sports, and I want to answer three questions foreach of them. The first addresses the points above -- how predictable isthe sport? For that, I'm looking at this question: Given two teams whodiffer by a given amount in quality, as measured by the ISR's, which seemto work pretty well with all the sports given here with one caveat, howlikely is the weaker team to win? To look at this, I looked at the range ofquality within the sport -- how wide is the range between the best team andthe worst team? I also looked at the probability functions for each sport,similar to the 2% per ISR point rule of thumb that works pretty well forcollege baseball (in other words, a team with a 10-point ISR advantage willwin 70% of the time, ignoring the home field advantage), but couldn't finda good way to present that in an understandable manner; maybe some othertime.
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The second question concerns the notion of competitive balance -- howlikely is it that a team will be about as good one year as they were theyear before? For that, I'm comparing ISR's from year to year with acorrelation measure. Finally, I'm curious about how well the postseason isset up for the sport. In other words, how good are their champions? I'vedone this for eleven sports or variants of sports, and some of thecomparisons are interesting. I'd love to add soccer, softball, orvolleyball (or any other team sport you can point me to data for), butthese are the only ones I've been able to find sufficient scores for yet.
College Baseball
Average Range: 62.1 - 126.5
Competitive Balance: .87
Champions: 1/7/3/4/1/286
We'll start here, with the sport we know best (for those of you who arefans of other sports and got here through Google or whatever, read thisanyway) and explain the different measures.
The range is the average of the lows and the highs in absolute ISR measuresfor the five seasons. I don't discuss absolute ISR values very much(they're designed to balance around 100 and form a nice normal curve overthe sport), but they're useful here to show the magnitudes of relativequality in each sport. The tighter the range, the closer the worst andbest teams in the sport are, and the more likely an upset is in any givengame. College baseball is the most competitive (or most random) of thecollege sports.
The competitive balance measure listed here is the result of correlatingthe ISR value from one year to the next for all teams that played insuccessive seasons in the sport. .87 means that a team that successfulin one season is quite likely to be successful in the next.
On the championship line, the first five numbers represent the ISR rank ofthe national champion. If your goal for the postseason is to find out whothe best team is, 1 is good here. If you're a fan of 'the excitement ofupsets', higher is better, I suppose. For all its faults, the collegebaseball postseason has produced some fairly good national champions, butit turns out that it's unusual for a team lower than about #3 in its sportto win a title, so Miami's 1999 championship is still off the charts. Thelast number on the line is the number of teams who competed in 2002.
Major League Baseball
Average Range: 93.3 - 107.9
Competitive Balance: .55
Champions: 1/6/9/4/4/30
For all the complaints about 'faith and hope' (and the anti-trustexemption, which means we get to see these lies told directly to Congress),we have here the most highly competitive sport of them all. There's amoderate correlation between success from year to year (which is actuallygood, since you want well-run teams to continue to succeed and poorly-runteams to be forced to make changes), but in any given game, there's verylittle difference between the best and the worst. We also have the mostpoorly-designed postseason I can find.
Men's College Basketball
Average Range: 69.4 - 131.6
Competitive Balance: .79
Champions: 1/2/2/1/2/322
The range is actually closer than I expected, and the competitive balanceis at least a little more prone to volatility than college baseball. Forall the jokes about being a fan of, say, Vanderbilt football, it appearsthat there's actually little less likely to be rewarding than being a fanof a bad college baseball team (with the exception of college hockey, to benoted later).
For all the CBS chest-thumping about the unpredictability of March Madness,the postseason does a remarkable job of picking a team that's at least veryclose to being the best. The only team outside the top 10 in the last fiveyears to reach the title game is Indiana in 2002; two years of the lastfive have featured #1 and #2 playing for the title.
Women's College Basketball
Average Range: 65.3 - 139.9
Competitive Balance: .84
Champions: 1/2/1/3/1/324
As the budgets shrink a bit from the men and the limelight fades a little,things get a bit less competitive; as much as there are fabled programs inmen's basketball, there's really nothing there that compares with Tennesseeor Connecticut women's basketball.
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NBA
Average Range: 83.9 - 113.3
Competitive Balance: .69
Champions: 1/1/1/1/1/29
The less random nature of basketball relative to baseball helps out the NBAtremendously in the PR wars against MLB (although less so than awillingness not to repeatedly denigrate their own product). Thecompetitive balance correlation is higher than in baseball by quite a bit,but nobody's complaining in August that certain NBA teams have no chance tomake the playoffs, because they can let over half the league into thepostseason and still manage to quite predictably have the league's bestteam win the title. Side note: Nobody does NBA pools, and gambling'sillegal in this state, but take San Antonio this year, although it's closerthan usual.
WNBA
Average Range: 86.4 - 117.2
Competitive Balance: .54
Champions: 1/1/1/1/1/16
Even if the nature of the sport is to encourage teams to stay good oncethey're good, new leagues are not a great proving ground for it, so I'mnot sure there's much to be concluded here.
College Football
Most And Least Predictable Sports
Average Range: 47.4 - 132.7
Competitive Balance: .64
Champions: 1/1/3/1/1/152
As a minor side note, I'm not convinced that the ISR's are the best measuring tool for college football, since there are so few observationpoints in a season. The wide range is due to the fact that I don't havea source for scores that excludes 1AA teams. I'm actually somewhatsurprised that the top end is as low as it is; my impression (although Ihaven't followed football in over a decade) was that the best team almostalways won. I guess the relative rarity of undefeated teams would argueagainst that -- relatively speaking due to the number of games, the bestwomen's college basketball teams are actually more dominant than the bestcollege football teams.
For all the grousing about the lack of a real playoff, it's worth notingthat the best team almost always ends up as national champion; somethingthat's not as likely under any proposed playoff system.
NFL
Average Range: 81.6 - 116.4
Competitive Balance: .29
Champions: 1/4/1/4/1/32
Here we have an interesting paradox -- a sport where, by professional standards, there's a fairly wide range between the best and worst teamsin any given year, but being good one year is only a slight indicatorthat a team will be good the next year. It will be interesting to seeif the change in the way of producing the schedule will change thesenumbers.
Men's College Hockey
Average Range: 42.4 - 140.4
Competitive Balance: .93
Champions: 2/2/2/2/132
I'm on thin ice here, so to speak, since I know almost nothing abouthockey, but this looks like a sport with a huge gap between the haves andthe havenots that's unlikely to change. There's nothing inherent in thepostseason structure that I can see that would keep the #2 team winning, sothat may just be one of those weird coincidences. I don't have data for1998.
Women's College Hockey
Average Range: 54.9 - 141.6
Competitive Balance: .92
Champions: NA/NA/NA/2/2/68
On the championship line, the first five numbers represent the ISR rank ofthe national champion. If your goal for the postseason is to find out whothe best team is, 1 is good here. If you're a fan of 'the excitement ofupsets', higher is better, I suppose. For all its faults, the collegebaseball postseason has produced some fairly good national champions, butit turns out that it's unusual for a team lower than about #3 in its sportto win a title, so Miami's 1999 championship is still off the charts. Thelast number on the line is the number of teams who competed in 2002.
Major League Baseball
Average Range: 93.3 - 107.9
Competitive Balance: .55
Champions: 1/6/9/4/4/30
For all the complaints about 'faith and hope' (and the anti-trustexemption, which means we get to see these lies told directly to Congress),we have here the most highly competitive sport of them all. There's amoderate correlation between success from year to year (which is actuallygood, since you want well-run teams to continue to succeed and poorly-runteams to be forced to make changes), but in any given game, there's verylittle difference between the best and the worst. We also have the mostpoorly-designed postseason I can find.
Men's College Basketball
Average Range: 69.4 - 131.6
Competitive Balance: .79
Champions: 1/2/2/1/2/322
The range is actually closer than I expected, and the competitive balanceis at least a little more prone to volatility than college baseball. Forall the jokes about being a fan of, say, Vanderbilt football, it appearsthat there's actually little less likely to be rewarding than being a fanof a bad college baseball team (with the exception of college hockey, to benoted later).
For all the CBS chest-thumping about the unpredictability of March Madness,the postseason does a remarkable job of picking a team that's at least veryclose to being the best. The only team outside the top 10 in the last fiveyears to reach the title game is Indiana in 2002; two years of the lastfive have featured #1 and #2 playing for the title.
Women's College Basketball
Average Range: 65.3 - 139.9
Competitive Balance: .84
Champions: 1/2/1/3/1/324
As the budgets shrink a bit from the men and the limelight fades a little,things get a bit less competitive; as much as there are fabled programs inmen's basketball, there's really nothing there that compares with Tennesseeor Connecticut women's basketball.
Most Predictable Sport To Bet On
NBA
Average Range: 83.9 - 113.3
Competitive Balance: .69
Champions: 1/1/1/1/1/29
The less random nature of basketball relative to baseball helps out the NBAtremendously in the PR wars against MLB (although less so than awillingness not to repeatedly denigrate their own product). Thecompetitive balance correlation is higher than in baseball by quite a bit,but nobody's complaining in August that certain NBA teams have no chance tomake the playoffs, because they can let over half the league into thepostseason and still manage to quite predictably have the league's bestteam win the title. Side note: Nobody does NBA pools, and gambling'sillegal in this state, but take San Antonio this year, although it's closerthan usual.
WNBA
Average Range: 86.4 - 117.2
Competitive Balance: .54
Champions: 1/1/1/1/1/16
Even if the nature of the sport is to encourage teams to stay good oncethey're good, new leagues are not a great proving ground for it, so I'mnot sure there's much to be concluded here.
College Football
Most And Least Predictable Sports
Average Range: 47.4 - 132.7
Competitive Balance: .64
Champions: 1/1/3/1/1/152
As a minor side note, I'm not convinced that the ISR's are the best measuring tool for college football, since there are so few observationpoints in a season. The wide range is due to the fact that I don't havea source for scores that excludes 1AA teams. I'm actually somewhatsurprised that the top end is as low as it is; my impression (although Ihaven't followed football in over a decade) was that the best team almostalways won. I guess the relative rarity of undefeated teams would argueagainst that -- relatively speaking due to the number of games, the bestwomen's college basketball teams are actually more dominant than the bestcollege football teams.
For all the grousing about the lack of a real playoff, it's worth notingthat the best team almost always ends up as national champion; somethingthat's not as likely under any proposed playoff system.
NFL
Average Range: 81.6 - 116.4
Competitive Balance: .29
Champions: 1/4/1/4/1/32
Here we have an interesting paradox -- a sport where, by professional standards, there's a fairly wide range between the best and worst teamsin any given year, but being good one year is only a slight indicatorthat a team will be good the next year. It will be interesting to seeif the change in the way of producing the schedule will change thesenumbers.
Men's College Hockey
Average Range: 42.4 - 140.4
Competitive Balance: .93
Champions: 2/2/2/2/132
I'm on thin ice here, so to speak, since I know almost nothing abouthockey, but this looks like a sport with a huge gap between the haves andthe havenots that's unlikely to change. There's nothing inherent in thepostseason structure that I can see that would keep the #2 team winning, sothat may just be one of those weird coincidences. I don't have data for1998.
Women's College Hockey
Average Range: 54.9 - 141.6
Competitive Balance: .92
Champions: NA/NA/NA/2/2/68
Remember how little I knew about hockey? Subtract some of that for women'shockey. As far as I can tell, there's only been a national championship fortwo years now, so there's not even much history to look at.
NHL
Average Range: 88.4 - 109.3
Competitive Balance: .66
Champions: 2/1/4/1/1/30
We've got very competitive individual games, and a small but acceptableamount of turnover from year to year in the good teams, along with apostseason that produces a surprisingly accurate result, given the amountof randomness in individual games. So why are these guys going broke?
Pitch Count Watch
Rather than keep returning to the subject of pitch counts and pitcherusage in general too often for my main theme, I'm just going to run astandard feature down here where I point out potential problems; feelfree to stop reading above this if the subject doesn't interest you.This will just be a quick listing of questionable starts that havecaught my eye -- the general threshold for listing is 120 actual pitchesor 130 estimated, although short rest will also get a pitcher listed if I catch it. Don't blame me; I'm just the messenger.
| Date | Team | Pitcher | Opponent | IP | H | R | ER | BB | SO | AB | BF | Pitches |
| Mar 28 | North Carolina-Charlotte | Zachary Treadway | St. Louis | 9.0 | 9 | 3 | 2 | 5 | 8 | 34 | 42 | 129 |
| Apr 4 | Campbell | Josh Blades | Central Florida | 7.2 | 12 | 4 | 4 | 5 | 4 | 32 | 38 | 147 |
| Apr 4 | Mercer | Brandon Davidson | Jacksonville | 7.0 | 5 | 3 | 3 | 4 | 7 | 23 | 28 | 124 |
| Apr 4 | Samford | Stephen Artz | Troy State | 8.0 | 13 | 5 | 5 | 3 | 6 | 35 | 39 | 147 (*) |
| Apr 4 | Pacific | Matthew Pena | Cal State Fullerton | 7.0 | 14 | 10 | 9 | 4 | 2 | 33 | 39 | 134 |
| Apr 4 | South Florida | Jon Uhl | East Carolina | 8.2 | 8 | 4 | 4 | 2 | 9 | 33 | 36 | 130 (*) |
| Apr 4 | North Carolina-Charlotte | Zachary Treadway | Tulane | 8.1 | 9 | 6 | 5 | 3 | 7 | 33 | 38 | 122 |
| Apr 4 | Houston | Brad Sullivan | Alabama-Birmingham | 5.2 | 4 | 3 | 3 | 6 | 5 | 19 | 27 | 124 |
| Apr 4 | Ohio | Chris Bova | Marshall | 9.0 | 5 | 1 | 1 | 1 | 12 | 30 | 35 | 141 |
| Apr 4 | Evansville | Tom Oldham | Creighton | 9.0 | 11 | 6 | 4 | 0 | 6 | 37 | 41 | 130 (*) |
| Apr 4 | Alabama | Taylor Tankersley | Auburn | 4.1 | 9 | 7 | 7 | 3 | 7 | 23 | 28 | 125 |
| Apr 4 | College of Charleston | Matt Soale | Davidson | 9.0 | 4 | 2 | 2 | 2 | 8 | 31 | 33 | 121 |
| Apr 4 | Rice | Philip Humber | Hawaii | 8.0 | 6 | 3 | 3 | 1 | 11 | 29 | 31 | 125 |
| Apr 5 | Missouri | Garrett Broshuis | Texas Tech | 7.2 | 8 | 4 | 1 | 2 | 5 | 31 | 34 | 126 |
| Apr 5 | Cincinnati | B. J. Borsa | Southern Mississippi | 9.0 | 7 | 3 | 2 | 2 | 8 | 34 | 38 | 138 |
| Apr 5 | Eastern Michigan | Anthony Tomey | Ball State | 7.0 | 4 | 1 | 1 | 5 | 9 | 26 | 31 | 129 |
| Apr 5 | Eastern Michigan | Trevor Carpenter | Ball State | 6.0 | 8 | 5 | 4 | 1 | 7 | 27 | 28 | 128 |
| Apr 5 | Miami, Ohio | Graham Taylor | Arizona | 9.0 | 10 | 4 | 4 | 4 | 6 | 35 | 39 | 155 |
| Apr 5 | Ohio | Novosel | Marshall | 8.2 | 8 | 4 | 4 | 4 | 10 | 32 | 38 | 146 (*) |
| Apr 5 | Evansville | Mitch Prout | Creighton | 9.0 | 6 | 3 | 3 | 5 | 7 | 30 | 40 | 144 (*) |
| Apr 5 | Austin Peay State | D. Smith | Tennessee-Martin | 9.0 | 5 | 3 | 2 | 3 | 10 | 31 | 34 | 130 (*) |
| Apr 5 | Murray State | Kyle Perry | Eastern Kentucky | 9.0 | 11 | 8 | 5 | 2 | 3 | 36 | 42 | 132 |
| Apr 5 | Alabama | Johnson | Auburn | 7.0 | 5 | 1 | 1 | 2 | 9 | 25 | 27 | 120 |
| Apr 5 | Kentucky | Heath Castle | Mississippi State | 9.0 | 7 | 2 | 2 | 3 | 5 | 31 | 34 | 132 |
| Apr 6 | Texas | Justin Simmons | Baylor | 8.0 | 3 | 3 | 3 | 2 | 7 | 27 | 30 | 129 |
| Apr 6 | Cal State Northridge | Leo Rosales | Long Beach State | 9.0 | 6 | 2 | 1 | 1 | 9 | 32 | 35 | 121 |
| Apr 6 | William and Mary | Chris Shaver | James Madison | 8.2 | 9 | 3 | 3 | 4 | 5 | 29 | 35 | 122 |
| Apr 6 | Texas-Pan American | Travis Parker | Texas A&M-Corpus Christi | 10.0 | 9 | 2 | 2 | 4 | 4 | 37 | 41 | 145 (*) |
| Apr 6 | Texas A&M-Corpus Christi | Jimmy Hamon | Texas-Pan American | 9.0 | 6 | 2 | 1 | 4 | 11 | 32 | 38 | 148 (*) |
| Apr 6 | Yale | Mike Elias | Princeton | 10.1 | 7 | 7 | 7 | 5 | 4 | 36 | 43 | 144 (*) |
| Apr 6 | Evansville | Trevor Stocking | Creighton | 8.2 | 8 | 2 | 2 | 5 | 6 | 30 | 38 | 139 (*) |
| Apr 6 | College of Charleston | Brett Harker | Davidson | 8.0 | 9 | 3 | 0 | 0 | 5 | 34 | 34 | 126 |
| Apr 6 | Gonzaga | E. Clelland | Portland | 11.0 | 7 | 3 | 2 | 3 | 5 | 37 | 43 | 138 |
| Apr 6 | Hawaii | Chris George | Rice | 6.2 | 7 | 6 | 6 | 6 | 5 | 26 | 32 | 123 |
| Apr 7 | Washington State | Aaron MacKenzie | Stanford | 10.0 | 12 | 5 | 4 | 2 | 4 | 38 | 42 | 138 (*) |
| Apr 8 | James Madison | Leatherwood | Richmond | 7.1 | 7 | 3 | 3 | 5 | 6 | 28 | 35 | 130 (*) |
| Apr 8 | Georgetown | Salvitti | Maryland | 9.0 | 7 | 4 | 3 | 5 | 8 | 34 | 39 | 149 (*) |
| Apr 8 | Texas-Pan American | Aaron Guerra | Texas | 6.1 | 8 | 7 | 4 | 7 | 5 | 26 | 37 | 139 |
| Apr 9 | Southern Mississippi | Cliff Russum | Mississippi | 9.0 | 4 | 2 | 2 | 2 | 10 | 30 | 32 | 129 |
| Apr 10 | Sacred Heart | Chuck Ristano | Long Island | 9.0 | 8 | 0 | 0 | 0 | 10 | 33 | 35 | 122 |
(*) Pitch count is estimated.
The Treadway line from the 28th is a correction based on an actual pitch count.
The Most Predictable Sport
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Most Predictable Sport
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