I remember sitting in my living room during the 2017 NBA Finals, watching the Golden State Warriors complete their dominant playoff run with a 129-120 victory over the Cleveland Cavaliers in Game 5. As someone who's analyzed basketball statistics for over a decade, I found myself wondering what the actual championship odds were at various points throughout that season. The Warriors' journey to their second championship in three years wasn't just about talent - it was about beating probabilities that shifted dramatically from preseason through the final buzzer.
Looking back at the preseason odds, most sportsbooks had Golden State as overwhelming favorites, with some offering them at -200, meaning you'd need to bet $200 just to win $100. That's incredibly rare in professional sports, especially before a single game has been played. What many casual fans don't realize is that these odds aren't just predictions - they're carefully calculated probabilities designed to balance betting action while accounting for team strengths, injuries, and potential matchups. I've always found it fascinating how these numbers evolve throughout a season, reacting to every win, loss, and roster change.
The Warriors entered the playoffs with what I considered nearly perfect championship conditions. Their offensive rating of 115.6 was historically great, and they'd gone 67-15 during the regular season. But what really stood out to me was their depth - they had four future Hall of Famers in their prime, all healthy heading into the postseason. In my analysis experience, when you combine top-tier talent with health and cohesion at the right time, you get probabilities that tilt heavily in one direction. By the conference finals, some models gave them an 85% chance to win it all, though I thought that might be slightly conservative given how they were playing.
What's interesting is how these probabilities shift during actual games. I recall watching Game 3 of the Finals when the Cavaliers were up by six points late in the third quarter. For about fifteen minutes of game time, Cleveland's win probability according to advanced metrics jumped to nearly 65%. That's the thing about basketball - momentum swings can dramatically alter outcomes in ways that preseason predictions can't account for. The Warriors ultimately won that game 118-113, essentially sealing the series, but those moments of uncertainty are what make probability analysis so compelling.
The reference to TNT Tropang Giga's performance against San Miguel Beermen reminds me of how championship probabilities work across different leagues. That 61-41 halftime lead TNT built represents what probability models would call a "high confidence" situation, probably around 90% win probability at that point. But basketball being basketball, they nearly blew it, surviving 99-96. This mirrors what we saw in the 2017 NBA playoffs - even with overwhelming talent and favorable odds, nothing's guaranteed until the final buzzer.
From my perspective, the most accurate assessment of Golden State's championship odds came around the trade deadline. They'd integrated Kevin Durant into their system, shown consistent dominance against playoff teams, and avoided major injuries. At that point, I'd have given them about 70% championship probability, though different models varied between 65-75%. The Cavaliers, while formidable, were dealing with defensive issues that made them vulnerable against Golden State's offensive firepower.
What many fans don't consider is how championship odds incorporate potential playoff matchups. The Warriors' path through the West played perfectly to their strengths - they swept Portland, Utah, and San Antonio, never truly being tested until the Finals. Each series win adjusted their championship probability upward, though I'd argue the biggest jump came after they dismantled San Antonio in the conference finals. That series demonstrated they could handle disciplined, systematic basketball in addition to outscoring run-and-gun teams.
The financial aspect of these probabilities always intrigues me. By the time the Finals began, the Warriors were -250 favorites, reflecting both their dominant playoff run and the betting public's confidence in them. Sharp bettors I've spoken with told me they'd placed their Golden State futures bets much earlier in the season when the value was better. That's the key understanding probability - it's not just about who's most likely to win, but when the numbers offer the best risk-reward scenario.
Reflecting on that 2017 championship now, I believe the actual odds were closer to 80% in Golden State's favor once the playoffs began, higher than most public models suggested. Their combination of offensive efficiency, defensive versatility, and playoff experience created what I call a "perfect storm" scenario. The Cavaliers certainly had the talent to pull off the upset, particularly with LeBron James playing at an historic level, but the probabilities always favored the Warriors' superior depth and system.
In the end, probability analysis teaches us that while upsets happen, the most likely outcome usually prevails over a seven-game series. The 2017 Warriors didn't just win the championship - they validated the probability models that had favored them from the beginning. Yet as the TNT-San Miguel game demonstrates, and as I've seen throughout my career analyzing sports probabilities, even the most certain outcomes can become interesting when human elements like pressure, momentum, and sheer willpower enter the equation. That's why we watch the games rather than just reading the odds.