Kevin Garnett led Boston to victory.Coming off a dominating performance that helped end the Atlanta Hawks’ season, Boston Celtics all-star Kevin Garnett did not let up on the Philadelphia 76ers in Game 1 of the Eastern Conference semifinals Saturday night.Garnett registered a season-high 29 points to go with 11 rebounds to lead the Celtics to a hard-fought 92-91 victory over the Sixers to take a 1-0 series lead. But it was not all Garnet. Point guard Rajon Rondo his eighth career playoff triple double of 17 assists, 13 points and 12 rebounds.With 3.4 seconds to play, Rondo received the inbounds pass and ran out the clock before a Philadelphia player could foul him to stop the clock.Philly got 19 points from Andre Iguodala scored 19 points and 16 from Evan Turner. The 76ers left the building thinking what could have been. They led 77-67 with 11 minutes to play.But it was then that Boston seized the game. The Celts went on a 23-7 to take an 90-84 advantage and Philadelphia never could regain the lead.The Sixers get another shot in Game 2 Monday in Boston.
ReferencesPro-Football-Reference.comAutocorrelation / Elo rating / Monte Carlo simulations / Regression to the mean / ESPN’s Total Quarterback Rating Multiply all of those factors together, and you have the total number of Elo points that should shift from the loser to the winner in a given game. (Elo is a closed system where every point gained by one team is a point lost by another.) Put another way: A team’s postgame Elo is simply its pregame Elo plus or minus the Elo shift implied by the game’s result — and in turn, that postgame Elo becomes the pregame Elo for a team’s next matchup. Circle of life.We also adjust each starting quarterback’s rating based on his performance in the game, adjusting for the quality of the opposing defense. (Read on for more details about how that process works.)Elo does have its limitations. Aside from changes at quarterback, it doesn’t know about trades or injuries that happen midseason, so it can’t adjust its ratings in real time for the absence of an important non-QB player. Over time, it will theoretically detect such a change when a team’s performance drops because of the injury, but Elo is always playing catch-up in that department. Normally, any time you see a major disparity between Elo’s predicted spread and the Vegas line for a game, it will be because Elo has no means of adjusting for key changes to a roster and the bookmakers do. (But this should be much less frequent after the addition of our QB adjustments, since oddsmakers don’t tend to shift lines much — or at all — in response to changes at non-QB positions.)The quarterback adjustmentNew for 2019, we added a way to account for changes in performance — and personnel — at quarterback, the game’s most important position. Here’s how it works:Both teams and individual quarterbacks have rolling ratings based on their recent performance.Performance is measured according to “VALUE,” a regression between ESPN’s Total QBR yards above replacement and basic box score numbers (including rushing stats) from a given game, adjusted for the quality of opposing defenses.The formula for VALUE is: -2.2 * Pass Attempts + 3.7 * Completions + (Passing Yards / 5) + 11.3 * Passing TDs – 14.1 * Interceptions – 8 * Times Sacked – 1.1 * Rush Attempts + 0.6 * Rushing Yards + 15.9 * Rushing TDs.3For seasons before game-level sack logs are complete (pre-1981), the sack term is zeroed out.This metric is also adjusted for opposing defensive quality by computing a rolling rating for team QB VALUE allowed, subtracting league average from the VALUE an opponent usually gives up per game, and using that to adjust a QB’s performance for the game in question. So for example, if a team usually gives up a VALUE 5 points higher than the average team, we would adjust an individual QB’s performance downward by 5 points of VALUE to account for the easier opposing defense. You can track these quarterback ratings on a team-by-team and division-by-division basis using this interactive page, which shows the relative quality of every QB in the league. The average team QB VALUE rating going into the 2019 season was about 49.5 (or about 163 Elo points), a leaguewide number that has increased substantially over the history of the NFL as passing has become more prevalent and efficient. So a rolling rating that would have made a QB one of the best in football in the 1990s would rank as only average now, even though the zero-point in our ratings remains the replacement-level performance of an undrafted rookie starter.One last note on these ratings involves how they are set initially. We’ll explain preseason team Elo ratings below, but here is how preseason ratings are set for the quarterback adjustment:Before a season, each starting quarterback is assigned a preseason rating based on either his previous performance or his draft position (in the case of rookies making their debut start).For veterans with between 10 and 100 career starts, we take their final rating from the end of the previous season and revert it toward the rating of the average NFL QB start by one-fourth before the following season.For players with fewer than 10 or more than 100 starts, we don’t revert their ratings at all.For rookies making their starting debuts, we assign them initial ratings based on draft position. An undrafted rookie is always assigned a rating of zero for his first start. The first overall pick, by comparison, gets a rating of +113 Elo points before his first start. The quarterback Elo adjustment is applied before each game by comparing the starting QB’s rolling VALUE rating with the team’s rolling rating and multiplying by 3.3.For example: when Aaron Rodgers was injured midway through the 2017 season, he had a rolling VALUE rating of 66. The Green Bay Packers’ team rolling VALUE rating was 68, and backup Brett Hundley had a personal rating of 14. So when adjusting the Packers’ Elo for their next game with Hundley starting instead of Rodgers, we would have applied an adjustment of 3.3 * (14 – 68) = -1764After rounding. to Green Bay’s base Elo rating of 1586 heading into its Week 7 game against the Saints. This effectively would have left the Packers as a 1409 Elo team with Hundley under center (before applying adjustments for home field, travel and rest), dropping Green Bay’s win probability from 63 percent to 39 percent for the game despite playing at home. In cases like these, the QB adjustment can have a massive effect! Model CreatorsNate Silver The founder and editor in chief of FiveThirtyEight. | @natesilver538Jay Boice A computational journalist for FiveThirtyEight. | @jayboiceNeil Paine A senior sportswriter for FiveThirtyEight. | @Neil_Paine The DetailsFiveThirtyEight has an admitted fondness for the Elo rating — a simple system that judges teams or players based on head-to-head results — and we’ve used it to rate competitors in basketball, baseball, tennis and various other sports over the years. The sport we cut our teeth on, though, was professional football. Way back in 2014, we developed our NFL Elo ratings to forecast the outcome of every game. The nuts and bolts of that system are described below.Game predictionsIn essence, Elo assigns every team a power rating (the NFL average is around 1500). Those ratings are then used to generate win probabilities for games, based on the difference in quality between the two teams involved, plus adjustments for changes at starting quarterback, the location of the matchup (including travel distance) and any extra rest days either team had coming into the contest. After the game, each team’s rating changes based on the result, in relation to how unexpected the outcome was and the winning margin. This process is repeated for every game, from kickoff in September until the Super Bowl.For any game between two teams (A and B) with certain pregame Elo ratings, the odds of Team A winning are:Pr(A)=110−EloDiff400+1Pr(A)=110−EloDiff400+1ELODIFF is Team A’s rating minus Team B’s rating, plus or minus the difference in several adjustments:A home-field adjustment of 55 points at base, depending on who was at home, plus 4 points of Elo for every 1,000 miles traveled. This means the Giants get a 55-point Elo bonus when “hosting” the Jets (despite both teams calling MetLife Stadium home), while the Patriots would get a 65-point Elo bonus when, say, the Chargers come to visit. There is no base home-field adjustment for neutral-site games such as the Super Bowl1Unless a team somehow makes the Super Bowl in its host year. or international games, although the travel-distance adjustment is included for the Super Bowl.A rest adjustment of 25 Elo points whenever a team is coming off of a bye week (including when top-seeded teams don’t play during the opening week of the playoffs). Our research shows that teams in these situations play better than would be expected from their standard Elo alone, even after controlling for home-field effects.A playoff adjustment that multiplies ELODIFF by 1.2 before computing the expected win probabilities and point spreads for playoff games. We found that, in the NFL playoffs, favorites tend to outplay underdogs by a wider margin than we’d expect from their regular-season ratings alone.A quarterback adjustment that assigns every team and each individual QB a rolling performance rating, which can be used to adjust a team’s “effective” Elo upward or downward in the event of a major injury or other QB change. (See below for more details about how this adjustment works.)We also tested effects for weather and coaches (including both head coaches and coordinators) but found that neither improved the predictive value of our model in backtesting by enough to warrant inclusion.Fun fact: If you want to compare Elo’s predictions with point spreads like the Vegas line, you can also divide ELODIFF by 25 to get the spread for the game. Just be sure to include all of the many adjustments above to get the most accurate predicted line.Once the game is over, the pregame ratings are adjusted up (for the winning team) and down (for the loser). We do this using a combination of factors:The K-factor. All Elo systems come with a special multiplier called K that regulates how quickly the ratings change in response to new information. A high K-factor tells Elo to be very sensitive to recent results, causing the ratings to jump around a lot based on each game’s outcome; a low K-factor makes Elo slow to change its opinion about teams, since every game carries comparatively little weight. In our NFL research, we found that the ideal K-factor for predicting future games is 20 — large enough that new results carry weight, but not so large that the ratings bounce around each week.The forecast delta. This is the difference between the binary result of the game (1 for a win, 0 for a loss, 0.5 for a tie) and the pregame win probability as predicted by Elo. Since Elo is fundamentally a system that adjusts its prior assumptions based on new information, the larger the gap between what actually happened and what it had predicted going into a game, the more it shifts each team’s pregame rating in response. Truly shocking outcomes are like a wake-up call for Elo: They indicate that its pregame expectations were probably quite wrong and thus in need of serious updating.The margin-of-victory multiplier. The two factors above would be sufficient if we were judging teams based only on wins and losses (and, yes, Donovan McNabb, sometimes ties). But we also want to be able to take into account how a team won — whether they dominated their opponents or simply squeaked past them. To that end, we created a multiplier that gives teams (ever-diminishing) credit for blowout wins by taking the natural logarithm of their point differential plus 1 point.MovMultiplier=ln(WinnerPointDiff+1)×2.2WinnerEloDiff×0.001+2.2MovMultiplier=ln(WinnerPointDiff+1)×2.2WinnerEloDiff×0.001+2.2This factor also carries an additional adjustment for autocorrelation, which is the bane of all Elo systems that try to adjust for scoring margin. Technically speaking, autocorrelation is the tendency of a time series to be correlated with its past and future values. In football terms, that means the Elo ratings of good teams run the risk of being inflated because favorites not only win more often, but they also tend to put up larger margins in their wins than underdogs do in theirs. Since Elo gives more credit for larger wins, this means that top-rated teams could see their ratings swell disproportionately over time without an adjustment. To combat this, we scale down the margin-of-victory multiplier for teams that were bigger favorites going into the game.2Special note: In the case of a tie, the multiplier becomes 1.525, or 2.2 times the natural log of 2 (which, based on the formula above, effectively assumes the absolute margin of victory in any game must be at least 1). For individual QBs, the rolling rating is updated every 10 games. (i.e., Rating_new = 0.9 * Rating_old + 0.1 * Game_VALUE ).For teams, the rolling rating is updated every 20 games.This implies that short-term “hot” and “cold” streaks by individual QBs have predictive value, which can trigger a nonzero pregame QB adjustment even when a team has had the same starter for each of its previous 20 games. Preseason QB ratings are also assigned at the team level. These consist of one-third weight given to the team’s previous end-of-season rolling QB rating and two-thirds weight given to the preseason rolling rating of the team’s projected top starter.Pregame and preseason ratingsSo all of that is how Elo works at the game-by-game level and what goes into our quarterback adjustments. But where do teams’ preseason ratings come from, anyway?We use two sources to set teams’ initial ratings going into a season:At the start of each season, every existing team carries its Elo rating over from the end of the previous season, except that it is reverted one-third of the way toward a mean of 1505. That is our way of hedging for the offseason’s carousel of draft picks, free agency, trades and coaching changes. We don’t currently have any way to adjust for a team’s actual offseason moves, aside from changes at quarterback, but a heavy dose of regression to the mean is the next-best thing, since the NFL has built-in mechanisms (like the salary cap) that promote parity, dragging bad teams upward and knocking good ones down a peg or two.For seasons since 1990, we also use Vegas win totals to help set preseason Elo ratings, converting over-under expected wins to an Elo scale. (This addition to the model helped significantly improve predictive accuracy in backtesting, by a little more than half the improvement that adding the QB adjustment did.) As a side note, this is partly why we mix the projected startIng QB’s rolling rating into the preseason team QB rating — we assume that changes at quarterback are “baked into” Vegas over/unders and must be adjusted for to avoid double-counting the improvement added by an upgrade at QB.These two factors are combined, with one-third weight given to regressed Elo and two-thirds weight given to Vegas-wins Elo. This blend is what forms a team’s preseason Elo rating.Note that I mentioned “existing” teams when mentioning end-of-season ratings from the previous year. Expansion teams have their own set of rules. For newly founded clubs in the modern era, we assign them a rating of 1300 — which is effectively the Elo level at which NFL expansion teams have played since the 1970 AFL merger. We also assigned that number to new AFL teams in 1960, letting the ratings play out from scratch as the AFL operated in parallel with the NFL. When the AFL’s teams merged into the NFL, they retained the ratings they’d built up while playing separately.For new teams in the early days of the NFL, things are a little more complicated. When the NFL began in 1920 as the “American Professional Football Association” (they renamed it “National Football League” in 1922), it was a hodgepodge of independent pro teams from existing leagues and opponents that in some cases were not even APFA members. For teams that had not previously played in a pro league, we assigned them a 1300 rating; for existing teams, we mixed that 1300 mark with a rating that gave them credit for the number of years they’d logged since first being founded as a pro team.InitRating=1300×23YrsSince1stSeason+1505×(1−23)YrsSince1stSeasonInitRating=1300×23YrsSince1stSeason+1505×(1−23)YrsSince1stSeasonThis adjustment applied to 28 franchises during the 1920s, plus the Detroit Lions (who joined the NFL in 1930 after being founded as a pro team in 1929) and the Cleveland Rams (who joined in 1937 after playing a season in the second AFL). No team has required this exact adjustment since, although we also use a version of it for historical teams that discontinued operations for a period of time.Not that there haven’t been plenty of other odd situations to account for. During World War II, the Chicago Cardinals and Pittsburgh Steelers briefly merged into a common team that was known as “Card-Pitt,” and before that, the Steelers had merged with the Philadelphia Eagles to create the delightfully monikered “Steagles.” In those cases, we took the average of the two teams’ ratings from the end of the previous season and performed our year-to-year mean reversion on that number to generate a preseason Elo rating. After the mash-up ended and the teams were re-divided, the Steelers and Cardinals (or Eagles) received the same mean-reverted preseason rating implied by their combined performance the season before.And I would be remiss if I didn’t mention the Cleveland Browns and Baltimore Ravens. Technically, the NFL considers the current Browns to be a continuation of the franchise that began under Paul Brown in the mid-1940s. But that team’s roster was essentially transferred to the Ravens for their inaugural season in 1996, while the “New Browns” were stocked through an expansion draft in 1999. Because of this, we decided the 1996 Ravens’ preseason Elo should be the 1995 Browns’ end-of-year Elo, with the cross-season mean-reversion technique applied, and that the 1999 Browns’ initial Elo should be 1300, the same as any other expansion team.Season simulationsNow that we know where a team and quarterback’s initial ratings for a season come from and how those ratings update as the schedule plays out, the final piece of our Elo puzzle is how all of that fits in with our NFL interactive graphic, which predicts the entire season.At any point in the season, the interactive lists each team’s up-to-date Elo rating (as well as how that rating has changed over the past week and how any changes at QB alter the team’s effective Elo), plus the team’s expected full-season record and its odds of winning its division, making the playoffs and even winning the Super Bowl. This is all based on a set of simulations that play out the rest of the schedule using Elo to predict each game.Specifically, we simulate the remainder of the season 100,000 times using the Monte Carlo method, tracking how often each simulated universe yields a given outcome for each team. It’s important to note that we run these simulations “hot” — that is, a team’s Elo rating is not set in stone throughout the simulation but changes after each simulated game based on its result, which is then used to simulate the next game, and so forth. This allows us to better capture the possible variation in how a team’s season can play out, realistically modeling the hot and cold streaks that a team can go on over the course of a season.Our simulations also project which quarterback will start each game by incorporating injuries, suspensions and starters being rested. For example, we might know that a quarterback is out for Weeks 1 and 2 but back for certain in Week 3. Or our forecast might have some uncertainty around a quarterback’s injury and project that he has only a 10 percent chance of playing next week but a 50 percent chance of playing the following week, and so on. In cases where we don’t know for sure which quarterback will start a game, the team’s quarterback adjustment is a weighted average of the possible starting quarterback adjustments.Late in the season, you will find that the interactive allows you to experiment with different postseason contingencies based on who you have selected to win a given game. This is done by drilling down to just the simulated universes in which the outcomes you chose happened and seeing how those universes ultimately played out. It’s a handy way of seeing exactly what your favorite team needs to get a favorable playoff scenario or just to study the ripple effects each game may have on the rest of the league.The complete history of the NFLIn conjunction with our Elo interactive, we also have a separate dashboard showing how every team’s Elo rating has risen or fallen throughout history. These charts will help you track when your team was at its best — or worst — along with its ebbs and flows in performance over time. The data in the charts goes back to 1920 (when applicable) and is updated with every game of the current season.An important disclaimer: The historical interactive ratings will differ from the ratings found in our current-season prediction interactive because the historical ratings do not contain our quarterback adjustments. (If you’re interested in looking at the historical QB adjustment data, it’s available on our data homepage.) The rolling rating represents the VALUE we’d expect a quarterback (whether at the individual or team level) to produce against a passing defense of average quality in the next start. To convert between VALUE and Elo, the rolling rating can be multiplied by 3.3 to get the number of Elo points a QB is expected to be worth compared with an undrafted rookie replacement. Version History2.0Quarterback adjustments are added, along with special adjustments for travel distance, bye weeks and playoff rating spreads.Sept. 4, 20191.1Ratings are extended back to 1920, with a new rating procedure for expansion teams and other special cases. Seasonal mean-reversion is set to 1505, not 1500.Sept. 10, 20151.0Elo ratings are introduced for the current season; underlying historical numbers go back to 1970.Sept. 4, 2014 Related ArticlesThe Complete History Of The NFLMay 1, 2018Introducing NFL Elo RatingsSept. 4, 2014The Best NFL Teams Of All Time, According To EloSept. 18, 2015Did The Packers Squander Aaron Rodgers?Dec. 5, 2018The Browns Are A Hot Super Bowl Pick For 2019. (Wait, What?)July 15, 2019
None of this isn’t to say that Phelps can’t surprise his doubters in 2016. But the age and steady progress of other swimmers will be working against him should he compete in Rio. Michael Phelps, the most decorated Olympian in history, announced this week that he was returning to competitive swimming. Phelps had retired following a six-medal performance at the 2012 Summer Olympics in London. Phelps and his coach, Bob Bowman, aren’t saying whether he’s gearing up for another run at the Olympics, but it’s hard not to speculate about one of the best athletes ever returning to competition. (Remember the hype surrounding a 38-year-old Michael Jordan’s return to basketball?)I’m not here to speculate about whether Phelps will make it to Rio de Janeiro in 2016. But if he represents the United States for a fifth time — he would be 31 — how might he perform?Putting aside conditioning concerns — Phelps only swam occasionally in the year following his retirement, though he is reportedly now working out with Bowman five days a week — the specter of age looms large. Thirty-one is ancient for an Olympic swimmer. Since 1968, only 17 athletes 31 and older have participated in any of the individual events Phelps would probably attempt (100- and 200-meter butterfly; 200-meter freestyle; and 200- and 400-meter individual medley). The average age of medalists in those events was 21.4.Of course, Phelps isn’t the typical Olympic swimmer. At his peak, the 2008 Games, he set the world record in four of the five individual events (he had to settle for just an Olympic record in the 100-meter butterfly; he broke the world record in that event in 2009). So, in 2016, Phelps might be a shadow of his former self, but even a diminished version of history’s best swimmer could be a force to be reckoned with.In the 2012 Olympics, Phelps took individual gold medals in the 100-meter butterfly and the 200-meter medley, and also grabbed silver in the 200-meter butterfly. If we look at how swimmers in those events tend to age, perhaps we can get an idea of whether Phelps is likely to be competitive if he takes to the water in 2016. Unfortunately, the data is sparse on competitors in their 30s, but here’s how the average male swimmer who participated in back-to-back Games tends to see his times change from one Olympics to the next (since 1968, with a minimum sample of four swimmers in each age group): In each graph, the trend is unsurprising: Swimmers get progressively worse with age. If Phelps follows the same paths, he could expect to post average times of 52.2 seconds in the 100-meter butterfly (which wouldn’t have gotten him out of the semifinals in London), 1:57.4 in the 200-meter butterfly (which would have missed qualifying out of Round 1 in 2012), and 1:58.1 in the 200-meter individual medley (which would have qualified for the final, but not earned a medal, in London). Obviously, there’s plenty of uncertainty around those extrapolations, but they give us a sense of how age may affect Phelps — even if he’s prepared and in shape for Rio.There’s one other factor working against Phelps: The rest of the field is getting faster. The average time for a finalist and a gold medalist has steadily decreased in each of Phelps’s best events since 1968:
Perfect brackets: They’re rather hard. You know this. Before we get into the whole “you have a one-in-who-gives-a-craptillion chance of winning” part of the story, though, let’s talk about why it’s so hard to grasp big numbers like this.Generally speaking, without a way to anchor a number to an everyday concept, people tend to have a hard time with Very Big Numbers. For some of them, like my favorite thing of all things the Powerball lottery, it’s still doable. For instance, your odds of winning the Powerball lottery are roughly equivalent to picking a random adult who lives in the U.S. and Canada and that person being you. It’s the probability of selecting a random person on earth, and that person having been in your freshman biology class. Powerball, with its 1 in 292 million probability of success, approaches the upper limit of what we can convey.My personal limit is 1 in 7 billion, because that is how many people are on earth — essentially the biggest number I feel I have any hope of grasping. Any more than that and you’ve got to do one of those “line up five decks of shuffled cards” monstrosities, and by then you’re just grasping at straws — we get it, dude, it’s unlikely.Last year I got to interview Randall Munroe — a guy who regularly confronts this kind of problem — and he talked about it better than anyone I can think of:One thing that bothers me is large numbers presented without context. We’re always seeing things like “This canal project will require 1.15 million tons of concrete.” It’s presented as if it should mean something to us, as if numbers are inherently informative. So we feel like if we don’t understand it, it’s our fault.But I have only a vague idea of what one ton of concrete looks like. I have no idea what to think of a million tons. Is that a lot? It’s clearly supposed to sound like a lot, because it has the word “million” in it.You should read that whole interview, because he’s got a brilliant take on a problem we deal with more often than we’d prefer to admit, but his key point is this: “A good rule of thumb might be, ‘If I added a zero to this number, would the sentence containing it mean something different to me?’ If the answer is ‘no,’ maybe the number has no business being in the sentence in the first place.”That being said, here is a series of sentences about the number 9.2 quintillion, and how you might work your head around that many possible brackets.We should start small, then work our way up. Let’s take the most basic entry point, a single round-of-32 game. There are two possible ways to fill in that part of the bracket. Now we’re getting to an increasingly hard part: calling a region perfectly. One region has two of those smaller chunks — with 128 combinations each — plus two choices in the last game. This gives us 128 times 128 times 2 possible configurations, or 32,768 ways to fill out a division. That’s 2^15, which, you guessed it, is the number of games in this chunk. You filled out eight of these. If everyone in a company of 5,600 people, which is a little smaller than ESPN, filled out a bracket randomly, there’s a 50-50 shot that at least one of them gets one division perfect. Next, we have a half of a region. We have two of those previous bracket chunks — each with eight possible configurations — and two ways to pick who goes on to the Elite Eight. This means we have 8 times 8 times 2 possible configurations, or 128 possible ways to fill out this section. Just another quick note: 128 is 2^7, seven being the number of games in this chunk of bracket. Maybe someone in your office got one of these perfectly! But it’s starting to get pretty hard, right? This brings us to the final bracket. With 63 games and 2 possible selections for each one, that’s 9,223,372,036,854,775,808 possible combinations. Your bracket is one of these, and the perfect bracket is one of these, but it is highly unlikely that they are the same bracket, is what I’m saying. Moving up to half a bracket: With 31 games to call, there are 2^31 possible combinations — 2,147,483,648, to be exact. That means that randomly guessing winners, you are about one-seventh as likely to get half a bracket right as you are to win the Powerball jackpot (1 in 292 million, you’ll recall). It is half as likely as randomly selecting a resident of the Americas and having that person be Bill Murray. Here is some perspective on that figure. (N.B. Probably this will not help at all.)If you had one cat for all the possible bracket combinations and piled them up, it would form a mass one-seventeenth the size of the largest thing in the asteroid belt, and something like 1.5 times the mass of a moon of Saturn that is rounded into a sphere shape by its own gravitation. However, some of the cats could get hurt! Don’t try this!If you had one penny for all the possible bracket combinations, first of all, your wish-making syntax with genies is AWFUL, but also your penny stash would be worth about 858 times the value of the global economy.If you were waiting for Comcast to show up and install your Internet and the technician said it would only be another 9,223,372,036,854,775,808 seconds, that would take 21 times the age of the universe and fall just barely outside the average Comcast response time.If you had one grain of sand for every possible bracket combination, you not only managed to get worse at asking for wishes, but would also have like several trillion pounds of sand.If you had one ant for every possible bracket combination, you are by now thankfully out of wishes, you dangerous incompetent, and would increase Earth’s ant population a thousandfold and move Ant-Man to the A-list. So, got that going for us.Still, while 9.2 quintillion is the number that gets thrown around, it sucks because it’s so huge and also, honestly, somewhat pointless. There’s a reason people mostly perform better than the expected rate of bracket busting: They aren’t selecting randomly. There are different probabilities for each game, and people are aware it’s not a coin flip between first-seed Kansas and 16th-seed Austin Peay.Estimates for the legitimate probability of a perfect bracket vary. Based on reporting from USA Today, Duke math professor Jonathan Mattingly puts it at 1 in 2.4 trillion — I love this estimate, and you’ll see why in just a second — while a professor at DePaul University puts it as low as 1 in 128 billion.I have no idea what it actually is, but using the pre-tournament probabilities of each team in the FiveThirtyEight interactive, I can tell you the probability of a perfect chalk bracket. That is, if in every game you selected the team that FiveThirtyEight gave the higher pre-tournament likelihood of winning, what’s your actual probability of getting a perfect bracket? Based on the assigned probabilities of advancement at each game, picking the likeliest team to advance and multiplying through all the pre-tourney probabilities, the odds that every one of our predictions would be right was 1 in 2,460,838,227,877 (2.5 trillion). This is delightful because it’s right in the ballpark of Mattingly’s estimate. Indeed, it’s basically right on the pitcher’s mound with it.So, the gist: Numbers are hard; big numbers are pointless and not attuned to the human brain; this should not make you feel bad; you should be proud if you nailed half of a region and thrilled if you got a whole one; and don’t hold your breath for anything more. See you next year or maybe earlier, if the Powerball gets big enough. Next, we go to one-fourth of a division: four teams vying for one spot in the Sweet 16 over three games. There are eight possible configurations of this bracket — two possible ways to fill in the first game, two ways to fill in the second, and then two possible ways to fill in the final game, given that you only have two choices from the first four teams. That’s eight configurations, or 2^3. Your probability of picking one of these perfectly is thus 1 in 8. Given that you filled out 16 of them, check your bracket. You probably got at least a few perfect!
OSU redshirt junior Quarterback J.T. Barrett (16) breaks into open field during the fourth quarter against Northwestern on Oct. 29, 2016. The Buckeyes won 24-20. Credit: Mason Swires | Assistant Photo EditorIt might not have been the way that Ohio State football fans wanted it, but the Buckeyes walked away with the 24-20 victory over the Northwestern Wildcats Saturday night in the ‘Shoe. In a hard-fought game that OSU coach Urban Meyer called a “dogfight,” OSU regained a little of the swagger lost after falling to Penn State. In the press conference following the game, Meyer and players were berated with questions once again about all the things the team is doing wrong. It was an interesting take, considering the team had just beat a solid Northwestern squad.“You had a very balanced, ran for 200 and threw for 230. Most places that’s a pretty good day,” Meyer said. “I understand here it’s a little off a little bit. We’ve got to get that 500 number, I guess. But I’m very happy with it. I’ll enjoy myself tonight.”Sure, OSU didn’t exactly set the world on fire with an outstanding offense or make big, flashy plays on defense. But the effort was there from the No. 6 ranked team, and so were the plays when they were needed.Here are five takeaways from the Buckeyes’ bounce-back win against Northwestern.Curtis Samuel is important, but so is Mike WeberMeyer had some serious flak thrown his way after junior H-back Curtis Samuel touched the ball 10 times last week. After naming him the No. 1 playmaker for the Buckeyes in the offseason, most fans thought Meyer kept the ball out of his hands against Penn State.On Saturday, Samuel saw an increase in his touches by four. He ran the ball seven times as well as carried the ball seven times, but gained a full 40 yards less than he did last game.So what does that mean for the OSU offense when Samuel isn’t the leading rusher, but the team still finds a way to win?It means redshirt freshman running back Mike Weber had a pretty good day. As in 87 yards rushing, an average of 6.2 yards per carry and two scores.He also had three catches for 20 yards, and helped provide a mostly sound pocket for redshirt junior quarterback J.T. Barrett when he was asked to block. Overall, Weber provided the difference in terms of scoring, although Samuel scored the winning touchdown.Weber is the lead back in the OSU backfield, while Samuel continues to impress in his receiving ability. Meyer said he is a true hybrid back, the exact reason why his touches were split down the middle on Saturday.While the junior H-back is vital to the Buckeyes success, Weber has to be an integral part as well.The Silver Bullets are mastering the phrase “bend but don’t break”In back-to-back weeks, the OSU defense gave up some big plays that burnt the team. Be that as it may, there was a huge difference between the plays given up last week as opposed to this week: The defense eventually buckled down.Right before halftime in Happy Valley, the Buckeyes surrendered arguably the biggest play of the evening. Redshirt junior Gareon Conley smothered Penn State junior wideout Chris Godwin, but the ball found its way into the receiver’s hands, and the Nittany Lions brought the game to a 12-7 mark, with all the momentum gone for OSU right before the midway point.This week, OSU was presented with a similar scenario, as Northwestern received a punt on its own 40-yard line. With good field position and an offense that had 157 yards in the second quarter alone to that point, the Buckeyes appeared to be in trouble.Instead of trouble, OSU pushed the Wildcats back a yard and prevented a score.“At that point in the game, that’s more just the bond we have for each other,” redshirt sophomore safety Malik Hooker said. “We’re so strong and so close together on the defense overall that stuff like we know we’re competing (for) who’s going to make the play. We know that anybody’s liable to step up and make the play on the defensive side of the ball.”It hasn’t been the stifling defense the team enjoyed in the first few weeks, but it’s a defense that dominated against Oklahoma and helped bring home a win on Saturday. Bend but don’t break is not going to win a national championship, but it gives them a chance to keep the dream alive.Austin Carr from Northwestern is as real of a receiver as there is in the Big TenIt’s rare that a former walk-on player torches the OSU secondary. Unfortunately for the Buckeyes, senior wide receiver Austin Carr did just that on Saturday, hauling in eight passes for 158 yards. Although Carr failed to score, he did show off an impressive skill set, lining up in both the slot and on the outside. Running crossing post routes, he was able to find space in the middle of the field with linebackers picking up coverage along the way.This year, Carr has hauled in nine touchdowns and is well on track to rack up 1,000 yards. While the Buckeyes are hunting for a wide receiver to pick up big chunks of yardage at a time, Northwestern has Carr running rampant over Big Ten defenses.The offensive line has recovered some groundLast week was about as ugly as it gets for an any offensive line. OSU allowed 11 tackles for loss, while Barrett was sacked six times. Sophomore tackle Isaiah Prince gave up 14 hurries by himself last week, but fellow offensive linemen like redshirt junior guard Billy Price stood by his side.Northwestern had a much harder time getting in the backfield and penetrating the pocket, as the Buckeyes allowed four tackles for loss with just one sack. It was a game that was far from perfect, but had obvious improvements throughout.“There was a couple good points from last week. We struggled in a few aspects,” Price said. “And to have that confidence to go back out and to perform and to put the game as we offensive lineman call it on us, let’s go out and win on us. Don’t depend on a receiver out in the corner. Put the ball on us, put who our program is driven on — the offensive line. Isaiah did a lot better.”In all, the Buckeyes put up 431 yards of total offense. The success of an offensive unit is usually measured by the play of its blockers up front. It wasn’t a perfect day, but anything is an improvement from last week.Close game or not, the team can still winNorthwestern might not have been the game that could put OSU in a playoff position, but a strong showing and a blowout could have helped mightily down the road. Although the team had a relatively strong performance, the way the Buckeyes played is nowhere near good enough to be within the upper echelon of the NCAA at the end of the year.Sure, it wasn’t a 50-point drubbing, or a thrilling finish against a ranked opponent. But it was a win, which is the most important thing, right?OSU continues to be a question mark as the year progresses in terms of postseason play, but Saturday’s game proved the team is still more than capable of getting the job done no matter what. Meyer himself said a win on Saturday is something to be proud of.“Nothing was perfect, but we’re going to enjoy that win and go,” he said.
OSU recruits Trevon Grimes and Tyjon Lindsey visited Columbus for the OSU vs. Nebraska football game on Nov. 5. Lindsey has since decommitted. Credit: Giustino BovenziOn Nov. 5, the Ohio State Buckeyes were getting ready to take on the Nebraska Cornhuskers for an 8 p.m. showdown in Columbus. Not only were these two teams slugging it out to continue the quest for a national championship, but this game served as a massive recruiting battle for the Buckeyes. More than 20 four- and five-star high-school recruits paid visits, both official and unofficial, to Ohio Stadium to decide whether to commit to the Buckeyes.After the Buckeyes destroyed the Cornhuskers 62-3, recruits met with Urban Meyer and took pictures with their potential jersey numbers to cap off OSU’s full-on press to sway some of the nation’s top talent.Meyer often refers to recruiting as the “lifeblood of the program.” But how much money is spent to acquire that lifeblood?In a months-long project, The Lantern analyzed how much money was spent on recruiting by OSU and the rest of the Big Ten Conference.As the Big Ten team with the most wins and only football national championship in the past four years, the numbers show the Buckeyes spend, on average, on pace in comparison to the other schools in the Big Ten.Records show OSU spent just over $2 million on recruiting from 2012 to 2015. Though that might seem like a lot, other schools spent more.The Big Ten’s biggest spender, Nebraska, spent $3.46 million to expand its recruiting reach.The lowest-spending team, the Wisconsin Badgers, spent just $1.02 million.When you break down OSU’s $2.009 million, it averages out to $502,439 per year from 2012 to 2015. Divide spending by wins, and OSU spent $40,423 per win, giving them the second-lowest cost per win (CPW) rate in the conference.Bubba Bolden (left) and Tate Martell (right) visit Columbus for the OSU vs. Nebraska game on Nov. 5. Bolden has since committed to USC. Credit: Giustino Bovenzi“I don’t know what other people spend money on, but we’re really financially conscious just because one: There’s no need to be frivolous with money, and two: That’s something you want to do for your administration, for your athletic director,” OSU wide receivers coach Zach Smith said. “We don’t take first- class flights, we don’t stay in $400-a-night hotels, and I don’t know if that’s what they spend money on, but we’re real conscious because there’s no need for that. We’re just trying to do a job, and we have whatever we need to do that job.After analyzing yearly NCAA membership financial reports from fiscal 2012 to 2015, and conducting interviews with Big Ten officials, The Lantern also found that recruitment spending in the Big Ten rises each year.The findings were calculated from NCAA financial membership reports that detail each school’s complete financial budget for fiscal years 2012, 2013, 2014 and 2015. Some universities, like Penn State, post financial records online.Thirteen of the 14 members of the Big Ten provided data, while Northwestern University, a private institution, declined to participate. The university is not subject to open-records laws that apply to public schools. Since 2012, recruiting spending across the Big Ten increased 39 percent. That spending commitment by conference teams has amounted to more wins for some schools in the past four seasons. One might think spending money on recruiting is an easy way for a football program to improve its record. But, as the data shows, spending on recruiting doesn’t always result in wins.After coach Urban Meyer took over in Columbus at the end of 2011, the Buckeyes spent $344,987 in 2012. That number grew to $614,619 in three years, showing a 78 percent increase. This is the third-highest rise in the conference during that time, behind only Penn State and Rutgers.OSU officials turned down a request to speak with Meyer about the commitment to recruiting, saying that he would be unavailable to speak to such topics during football season.OSU Vice President and Athletic Director Gene Smith backed the Buckeyes’ spending increases, explaining why there has been a drastic change over the past four years.“We always invest in what is necessary to be successful and recruiting is a part of that,” Gene Smith said in an email. He added that rising travel costs and “hosting expenses” explain the conference’s 39 percent rise in spending.The NCAA does not impose financial limits on how much a university can spend on recruiting. However, spending is limited to the following expenses: travel and lodging for coaches, travel and lodging (coach class airfare and a standard hotel room) for prospects and their parents on official visits, reasonable entertainment expenses (including three tickets to a home sporting event) and up to three meals per day for the prospect and his parents for football recruits.Additionally, there are strict restrictions on the timeframe when a recruit can be contacted by coaches. A full breakdown of recruiting rules and a yearly recruiting calendar can be found on the NCAA website.Smith said these comparisons are like comparing apples to oranges, because, geographically speaking, it’s easier for OSU and more centrally located schools to recruit nationally than it is for a school in the more rural parts of the country.“What it costs OSU to recruit in our geography compared to what it costs Nebraska from Lincoln (Nebraska) or Penn State from Happy Valley (Pennsylvania) is totally different,” Smith said. “Planes, gas, meals per diet regulations, etc., are all different.”Smith’s explanation provided reasoning why the Cornhuskers, the conference’s highest spending team, spent nearly $3.5 million on recruiting.Since Lincoln, Nebraska, is the westernmost school in the conference, it costs more to bring in recruits for official visits and fly out to evaluate potential players. John Jentz, executive associate athletic director and CFO at Nebraska, confirmed travel as the main driver for higher costs.“We have made a conscious investment in expanding our reach to find the best matches for our program,” Jentz said. “(In Nebraska) we like to say, ‘We are in the middle of everywhere,’ but few of those everywheres are reachable by car.”Nebraska’s 34 wins in the Big Ten since 2012 makes it fourth-best in the conference, but its $886,819 spending average makes for a $107,998 CPW average, which is the fourth-highest in this study. Despite the high numbers, Jentz maintained Nebraska’s dedication to improve the football program.“There is a recruiting budget established for each sport, each year,” Jentz said. “But if circumstances dictate more resources are needed for recruiting, we encourage identifying savings elsewhere to ensure success in recruiting.”The Cornhuskers are narrowly followed by the Penn State Nittany Lions, who spent a total of $3.441 million on recruiting over the four-year period. In fact, Penn State spent $1.391 million on recruiting in 2014 alone, the highest of any school in the Big Ten from 2012 to 2015.OSU coach Urban Meyer addresses the crowd at a Skull Session prior to OSU’s game against Nebraska on Nov. 5. Credit: Giustino BonvenziPenn State’s increased spending is explained by other circumstances. Specifically, 2012 was the first year of NCAA-imposed sanctions from the child sexual abuse scandal involving former assistant coach Jerry Sandusky.The number of scholarships dropped from 85 to 65 before the sanctions were gradually, and eventually, lifted. Despite the fact that traveling in general was reduced by the scholarship restrictions, selling a rebounding program to potential recruits is not an easy task.The team that spent the most on recruiting per win was the Purdue Boilermakers. With only 12 wins during four years, their relatively frugal spending on recruiting flips into a $238,795 CPW. These numbers also show how each team has a different philosophy when it comes to recruiting. For instance, Wisconsin tallied the second-most wins with 38 in the Big Ten through the 2012-2015 seasons. The Badgers spent $256,080 on average for recruiting, making its $26,940 CPW the lowest in the Big Ten. Wisconsin Athletics Director Barry Alvarez was unavailable for comment.Since accepting the job as the Buckeyes head coach, Urban Meyer has amassed 50 wins in his first four seasons. The Big Ten historically has been a conference that sticks to recruiting the Midwest. Meyer expanded the program’s reach across the country.OSU redshirt junior quarterback J.T. Barrett, a Wichita Falls, Texas, native, hoped to be recruited by the University of Texas, but never got the call from former coach Mack Brown and the Longhorns. Barrett was then lured to Columbus by then-OSU offensive coordinator, now Longhorns coach, Tom Herman.Meyer openly speaks of how Barrett’s recruitment was unorthodox, admitting that Barrett was the first quarterback prospect he’s ever offered a scholarship without seeing him throw. Statistically speaking, Barrett is among one of the greatest quarterbacks in Buckeye history.A RECRUITING STIGMARecruiting spending is a not topic athletic departments usually discuss with media outlets, partly because a recruiting violation could be uncovered. Think of Reggie Bush accepting benefits at USC, or “Tattoo-Gate” at OSU. In Bush’s case, the violations caused severe penalties for the Trojans, who then had to vacate numerous wins, including their 2004 National Championship and Bush’s Heisman Trophy.A more recent example comes from just last year before the 2016 NFL draft. Top prospect Laremy Tunsil of Ole Miss was outed by his stepfather, who released a bong mask video via Instagram. The hacked account also leaked screenshots of text conversations with a coach that detailed pay for Tunsil’s rent and his mother’s utilities. Tunsil later admitted to accepting illegal benefits during his playing days after he was drafted No. 13 overall by the Miami Dolphins.Most of the data the 13 participating schools provided was fiscal year figures that are reported as a lump sum of recruiting spending.Ohio State provided an additional report with more in-depth explanation of its recruiting spending, including a ledger of coaches’ traveling expenses.The detailed data showed expenditures from Meyer and nearly all of his assistants. The data was clean as far as showing any wrongdoings by the program, but maintaining this detailed data set does have its complications.OSU Athletics Chief Financial Officer Joe Odoguardi said OSU is working to create a newer and better system.“Right now we’re in the process of getting a new travel system that would allow us to (analyze) something like this better electronically, but unfortunately it’s being developed in-house and it’s been delayed for numerous reasons that are too long to explain,” Odoguardi said. “Once something like that is developed, something like this will be a lot easier to produce.”
Dealing with adversity is something that many athletes learn to cope with in their careers. Most, though, do not face potentially life-threatening situations.This was the case for Chad Hagan, the Ohio State football recruit listed at 6-feet-2-inches and 230 pounds, who last April found out he had an uncommon heart condition.“He was going in for a very minor procedure on his shin … when they went to anesthetize him, the anesthesiologist determined the irregularity in the heartbeat,” said Guy Montecalvo, Hagan’s football coach at Canon-McMillan high school in Canonsburg, Pa.The condition, Wolff-Parkinson-White Syndrome, causes irregular or rapid heartbeats, sometimes so fast that the chambers of the heart cannot fill back up with blood. This caused his heart to enlarge, which the doctors initially thought was a more serious condition.“Actually the heart had just grown larger to accommodate the more rapid, immature beats that did not allow the left side of the heart to pump out the necessary blood,” Montecalvo explained.He was able to return partway through his senior season, playing in five-and-a-half games, recording 497 yards and seven touchdowns on 87 carries and totaling 33 tackles on defense.During Hagan’s basketball season, another issue seemed to be developing with his rapid heartbeat. The doctors were again able to perform an operation, and Hagan was allowed to return to sports.While Hagan’s past has been difficult, his future with the Buckeyes looks bright.“The thing with Chad is, he could be an ultra-freak athlete,” said Kevin Noon, managing editor of Buckeyegrove.com. Registering a 4.4 40-yard dash and a 40-inch vertical, Hagan has all the physical tools to play and be successful at the college level.In terms of his past medical issues, it seems he will be alright as a Buckeye.“The doctors have pretty much given him a clean bill of health,” Montecalvo said. “He will continue to be monitored by a cardiologist … but as of now, the heart rate is good.”This is good news to Buckeye fans, as it seems Hagan has the potential to be a starter in the future in Ohio Stadium.While Hagan played both offense and defense in high school, it is on the defensive side of the ball where he is going to look to make his mark as a Buckeye. Some recruiting sites list him as a linebacker at the college level. Noon, though, thinks he has the ability to succeed as a safety.“As long as he proves he has the cover skills, I have no doubt that he’s got the rest of the physical attributes that he could probably be pretty dangerous as [a defensive back],” Noon said. “I think that would be the place he would make the biggest impact.”Montecalvo, though, thinks those that projected Hagan at the linebacker position have it right.“I think he could be a great outside linebacker. … He’s getting bigger every week,” Montecalvo said. “Ohio State initially recruited him as a safety, but that was back when he was 205 pounds after his junior year. … I believe he will be a solid 235- to 240-pound player and, needless to say, he can play a lot of places.”While placing him at a certain position may be problematic for recruiting experts, it seems like it will be a wonderful issue for OSU football coach Jim Tressel to deal with. The question then becomes how soon it will be until fans get to see Hagan on the field.“I would say he is a candidate to redshirt, but he does have the capability of being on the coverage team,” Noon said. “With the way the depth chart sets up along those lines, that a year on the scout team learning those positions [would be the best].”Regardless of when or where Ohio State fans see Hagan, it seems the Buckeyes have acquired not only a potentially great football player, but also a great person.“[Chad] is a very mature young man,” Montecalvo said. “He’s had to go through some very unique circumstances than most of the boys that I’ve coached. Consequently, that’s caused him to grow up and mature a little quicker than some people do. He’s the type of guy that people can lean on and depend on him reaching out to when they have problems.”
When an athlete posts multiple school records by the end of their college career, it would be expected to be hard to say goodbye. But for the Ohio State men’s tennis team, that goodbye became a new beginning. Former Buckeye tennis player, Justin Kronauge, is in his second year as the team’s assistant coach after completing one of the most illustrious athletic careers in the team’s history. Kronauge ended his playing career with the most single wins (147), most doubles wins (128) and most combined wins with 275 total victories for the Buckeyes, but still is as humble as can be. “I don’t even look at that stuff,” Kronauge said. “With such a good program like Ohio State, it’s an honor to hold those records.” Graduating with a degree in finance in 2010, Kronauge turned to coaching. The two-time All-American searched for a position on traveling and lower-level professional teams, but said he knew the atmosphere of the college game was the right fit for him, and the assistant coaching spot at OSU was calling. With a streak of seven straight Big Ten titles on the line, Kronauge said he is focused on preparing his team for the postseason. “Last year was our sixth straight, I’ve been a part of all of those,” Kronauge said. “It was special being on other end coaching, and making it to the Final Four of NCCAs last year was pretty exciting too.” Redshirt junior Devin McCarthy said he was happy to see Kronauge hired as an assistant coach for the team. McCarthy was a freshman when Kronauge was a senior for the Buckeyes and understood the honor it is to be coached by his former teammate. “It’s great to be able to go to someone who knows what you’re going through, he understands me as a player,” McCarthy said. “You look at his accolades, it’s pretty easy to listen to someone who has accomplished what he has.” Being a part of the team for four years, it was a pretty easy transition to becoming a coach, Kronauge said. “I feel like the guys had some respect from playing with me,” Kronauge said. “I grew up with some of them. They might give me a little harder time, but it’s alright, it’s give and take.” The team has won 143-consecutive home matches and 84-consecutive Big Ten victories with a win against the Minnesota Golden Gophers April 8, but the team doesn’t talk about the streaks, McCarthy said. “We don’t really want to jinx things,” McCarthy said. “We don’t want to be known as the team that lost it for all the guys like Justin. We are all working harder to make sure that doesn’t happen.” Kronauge has witnessed players in similar situations while playing for the Buckeyes, adding he is glad he can help guide them through it. “There was a lot of tight situations I was in when I was player,” Kronauge said. “I think my experience helps, and I can talk them through it.” Former teammate and senior Steven Williams described his coach as serious, respectful and hard working. “He has been able to balance being friends with the guys between playing and it being business,” Williams said. “He always had respect because he always kept it professional and looking out for the guys.” Kronauge competed in some lower-level professional tournaments across South America and the United States, but said he wishes to keep coaching in the future.
The coach of both the Ohio State men’s track and field and cross country teams, Ed Beathea, announced his resignation Tuesday, according to an OSU press release.The Indiana native is set to head back to Indiana University, where he spent 10 seasons as both an assistant coach and the Hoosiers’ associate head coach, and is slated to assume his former position as associate head coach for the 2014-2015 season, according to the Indiana athletics site.Beathea, who has been the coach of the men’s track and field program at OSU since 2012 and an associate coach in the program since 2006, is set to continue coaching the Buckeyes through the 2014 NCAA Outdoor Championships later this month.In a statement in the press release, Beathea expressed his gratitude for the eight years he spent at OSU as a coach in the track and field program, and expressed that it was the right time for him to move forward.“My family and I will always be grateful for the opportunity the Ohio State University has provided me and the university will provide us with fond memories,” Beathea said. “I am leaving this program in a very positive place. We have built a strong team that has proven the ability to compete at a national level. It was a difficult decision but in the end it is a good decision for me and my family. Thank you for supporting me and our program.”T.J. Shelton, the associate athletics director for sport administration at OSU, also made a statement in the release thanking Beathea for his time in Columbus.“The department of athletics would like to thank coach Ed Beathea for his leadership over the past eight years, including two as head coach of the men’s track field and cross country programs,” Shelton said. “We wish Ed and his family the best as they move forward with their next chapter of their lives. We will begin a national search immediately for the next head coach to lead our program.”Since taking over the program in 2012, Beathea has coached 2013 First Team All-American Michael Hartfield, 2014 Second Team All-American LaMar Bruton, and the 2014 Big Ten Indoor Champion in the 4×400 relay, Jordan Rispress.The 2014 NCAA Track and Field Championships are slated to run from June 11-14 in Eugene, Ore., and both Burton and Rispress are set to represent OSU at the event.
OSU’s Logan Stieber (right) wrestles with North Carolina State’s Kevin Jack in a 141-pound semifinal during the NCAA Division I Wrestling Championships on March 20 in St. Louis.Credit: Courtesy of TNSTwo weeks removed from making history with his fourth individual national title, Ohio State redshirt-senior Logan Stieber has put his collegiate accolades on the back burner for an even bigger desire — the 2016 Olympics.“It has always been a dream of mine to be an Olympian and to win gold,” Stieber said. “Doing that would be a great conclusion to my competitive career.”Stieber was awarded the Hodge Trophy, which is equivalent to what the Heisman is for football, on Monday. On that same day, he was also supporting his younger brother, Hunter, who was in surgery to attach a ligament in his right elbow.“The Hodge has been a goal of mine since my sophomore year,” Stieber said. “I would say it’s one of the highest honors I have received, and to have my brother come out of surgery OK as well, it made for a great day.”The four-time Big Ten and National Champion finished his career at OSU with a 119-3 record and was named the Big Ten Most Outstanding Wrestler and Most Outstanding Wrestler of the Big Ten Championships. Even after receiving these major individual awards, Stieber managed to keep his focus on his teammates, and is able to stay calm on the biggest of stages.“I have been blessed to be in a lot of big matches and moments in my life and I think I have learned from each one,” Stieber said. “That keeps me calm.”With a winning percentage of .975 — a school record — Stieber is used to being on top of the podium. Now he’s focused on remaining there as he looks to make the U.S. World Team this summer in hopes of qualifying for the Summer Olympics next year in Brazil.“I believe I can make the team and win gold,” Stieber said. Olympic wrestling uses the freestyle form of wrestling instead of the folkstyle used in college. Despite the different style, Stieber said, with the help of known World Team members such as former Buckeye Reece Humphrey, he will be able to make the transition quickly.“The freestyle circuit is different because of the amount of times you compete and the weigh-in rules are different,” Stieber said. “Also the training is more focused on skill and less on conditioning. I’ll be ready.”Looking back on his high school career and the way it ended, Stieber said he couldn’t have written a better script on how similarly he ended his collegiate career. Not only did he win four individual titles at both levels, but he led Monroeville and OSU to their first-ever team titles as well.“To have him win his fourth title on the same day as winning the team’s first is incredible,” Stieber’s father, Jeff, said. “It was always one of his biggest goals to do that and to see it happen is truly amazing.”Stieber finished his career on a 50-match winning streak dating back to December 2013, and won 96 of his 119 matches via bonus points. He tied for the most career falls in OSU history with 50 and also became just the second wrestler ever to win four Cliff Keen Las Vegas Collegiate Invitational titles.Once again, the individual accolades have piled up, but he stressed they don’t compare to the success he shares with his teammates.“Winning individual awards and achieving personal goals is something I obviously want to do, but being able to share a team title with my family and friends has been pretty cool,” Stieber said.Instead of taking it all in and enjoying the moment, wrestling season hasn’t ended for Stieber. He has already begun training for the 2015 Las Vegas/ASICS Open Wrestling Championships in May and even after he graduates, he still hopes to be a part of OSU and wants to continue to work with the team, he said. “I hope to keep wrestling in Columbus for a while and I want to see our team continue to get better and competing for titles.”